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Lee, Soo, Okan Bulut, and Youngsuk Suh. "Multidimensional Extension of Multiple Indicators Multiple Causes Models to Detect DIF." Educational and Psychological Measurement 77, no. 4 (2016): 545–69. http://dx.doi.org/10.1177/0013164416651116.
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A number of studies have found multiple indicators multiple causes (MIMIC) models to be an effective tool in detecting uniform differential item functioning (DIF) for individual items and item bundles. A recently developed MIMIC-interaction model is capable of detecting both uniform and nonuniform DIF in the unidimensional item response theory (IRT) framework. The goal of the current study is to extend the MIMIC-interaction model for detecting DIF in the context of multidimensional IRT modelling and examine the performance of the multidimensional MIMIC-interaction model under various simulation conditions with respect to Type I error and power rates. Simulation conditions include DIF pattern and magnitude, test length, correlation between latent traits, sample size, and latent mean differences between focal and reference groups. The results of this study indicate that power rates of the multidimensional MIMIC-interaction model under uniform DIF conditions were higher than those of nonuniform DIF conditions. When anchor item length and sample size increased, power for detecting DIF increased. Also, the equal latent mean condition tended to produce higher power rates than the different mean condition. Although the multidimensional MIMIC-interaction model was found to be a reasonably useful tool for identifying uniform DIF, the performance of the model in detecting nonuniform DIF appeared to be questionable.
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Chen, Yong, and Kai Jiang. "A multiple indicators multiple causes (mimic) model of the behavioral consequences of hotel guests." Tourism Management Perspectives 30 (April 2019): 197–207. http://dx.doi.org/10.1016/j.tmp.2019.02.014.
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Remeikiene, Rita, Martin Cepel, and Ligita Gaspareniene. "Evaluation of E-business micro and macro determinants by Multiple Indicators Multiple Causes model." Engineering Economics 30, no. 5 (2019): 591–600. http://dx.doi.org/10.5755/j01.ee.30.5.19639.
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The methods employed for the research include comparative and systematic literature analysis, statistical data analysis, expert evaluation and the Multiple Indicators Multiple Causes (MIMIC) model. There are several research gaps in the field of e-business: 1) there is no simplified factor model which would denote the development of e-business, including its causes and consequences, and which, due to its universality, could be adapted to any country; 2) the studies of e-business development lack a comprehensive assessment which would consider this phenomenon in both quantitative and qualitative terms.
On the basis of the theoretical analysis, a model for assessment of e-business development has been formed. The results of the empirical evaluation have revealed that in the group of micro environmental determinants development of e-business in Lithuania is, to the largest extent, determined by business managers’ motivation to reach the defined aims and their positive viewpoint that e-business may become a perfect auxiliary tool to ensure business competitiveness. In the group of macro environmental determinants, the determinants of socio-cultural environment can be indicated as the major ones that affect the development of e-business. Application of the MIMIC model has enabled to identify the following macro economical determinants (for the euro area): real effective exchange rate for the euro area; level of households with the Internet access; quantity of individuals using the Internet for ordering goods or services; government deficit/surplus; youth employment, and individuals using the Internet for interaction with public authorities.
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Proitsi, P., G. Hamilton, M. Tsolaki, et al. "A Multiple Indicators Multiple Causes (MIMIC) model of Behavioural and Psychological Symptoms in Dementia (BPSD)." Neurobiology of Aging 32, no. 3 (2011): 434–42. http://dx.doi.org/10.1016/j.neurobiolaging.2009.03.005.
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Qi, Chang, Brian C. Kelly, Yanhui Liao, et al. "A Multiple Indicators Multiple Causes (MIMIC) model of internal barriers to drug treatment in China." Drug and Alcohol Dependence 148 (March 2015): 143–49. http://dx.doi.org/10.1016/j.drugalcdep.2014.12.033.
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Son, Sookyoung, and Sehee Hong. "Multiple Group Analysis in Multilevel Data Across Within-Level Groups: A Comparison of Multilevel Factor Mixture Modeling and Multilevel Multiple-Indicators Multiple-Causes Modeling." Educational and Psychological Measurement 81, no. 5 (2021): 904–35. http://dx.doi.org/10.1177/0013164420987899.
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The purpose of this two-part study is to evaluate methods for multiple group analysis when the comparison group is at the within level with multilevel data, using a multilevel factor mixture model (ML FMM) and a multilevel multiple-indicators multiple-causes (ML MIMIC) model. The performance of these methods was evaluated integrally by a series of procedures testing weak and strong invariance models and the latent group mean differences testing after holding for factorial invariance. Two Monte Carlo simulation studies were conducted under the following conditions: number of clusters, cluster size, and the design type in groups. A multilevel one-factor confirmatory factor analysis (CFA) model as a research model in Study 1 was investigated to compare the results under different conditions with those of previous studies. A multilevel two-factor CFA model as a research model in Study 2 was evaluated by fitting alternative models that can be applied when the model is complicated. The results indicated that the two methods were reasonable in multilevel multiple groups analysis across within-level groups. However, pros and cons were found between the two methods. In the multilevel one-factor CFA model, ML MIMIC model was slightly better when the sample size is small. In the multilevel complex model, two alternative models of ML FMM were recommended because the weak invariance testing of ML MIMIC was considerably time-consuming. Finally, it was shown that information criteria, which are criteria for determining whether factorial invariance is established, need to be applied differently according to the sample size conditions. Guidelines for this situation are provided.
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Kunchai, Jetnipit, Dissakoon Chonsalasin, and Buratin Khampirat. "Psychometric Properties and a Multiple Indicators Multiple Cause Model of the Career Aspiration Scale with College Students of Rural Thailand." Sustainability 13, no. 18 (2021): 10377. http://dx.doi.org/10.3390/su131810377.
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To help address educational inequalities in student backgrounds and career plans, the measurement of career aspirations can provide crucial information about inequality related to career opportunities. Therefore, this study analyzed the factor structure and psychometric properties of the Career Aspiration Scale-Revised (CAS-R) and the effects of sociodemographic variables on the CAS-R. The study participants were 590 undergraduates at three community colleges in rural Thailand. Confirmatory factor analysis (CFA) was conducted to investigate the validity of the CAS-R three-factor model. The Multiple Indicators Multiple Causes (MIMIC) model with and without differential item functioning (DIF) were applied to investigate the effects of sociodemographic factors as covariates on the CAS-R and specific item response. The CFA results supported the 18-item CAS-R’s three-factor structure because the items well represented latent factors and because the subscales met research standards for reliability and validity. The MIMIC model showed that only the year of study (first-year students) had a positive direct effect on leadership, achievement, and educational aspirations. The MIMIC model with DIF indicated that gender, year of study, major, and paternal education caused inequality in 10 items. Overall, the results show that the 18-item CAS-R has strong psychometric properties and can accurately assess the career aspirations of Thai students. The MIMIC model’s application allowed researchers to show that sociodemographic background affected the leadership, achievement, and education subscales. Obtaining information on the CAS-R scale’s measurements would be useful for researchers, practitioners, and career counselors interested in helping students develop career aspirations and choices.
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Iliceto, Paolo, Maurizio Pompili, Sally Spencer-Thomas, et al. "Occupational stress and psychopathology in health professionals: An explorative study with the Multiple Indicators Multiple Causes (MIMIC) model approach." Stress 16, no. 2 (2012): 143–52. http://dx.doi.org/10.3109/10253890.2012.689896.
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Normand, Sébastien, Amori Yee Mikami, Victoria Savalei, and Joanna Guiet. "A Multiple Indicators Multiple Causes (MIMIC) model of friendship quality and comorbidities in children with attention-deficit/hyperactivity disorder." Psychological Assessment 32, no. 7 (2020): 698–704. http://dx.doi.org/10.1037/pas0000824.
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Lim, Young-Jin. "Relations between virtues and positive mental health in a Korean population: A Multiple Indicators Multiple Causes (MIMIC) model approach." International Journal of Psychology 50, no. 4 (2014): 272–78. http://dx.doi.org/10.1002/ijop.12096.
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Ogg, Julia, Melanie M. McMahan, Robert F. Dedrick, and Linda Raffaele Mendez. "Middle school students' willingness to engage in activities with peers with ADHD symptoms: A multiple indicators multiple causes (MIMIC) model." Journal of School Psychology 51, no. 3 (2013): 407–20. http://dx.doi.org/10.1016/j.jsp.2013.01.002.
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Ayotte, Brian J., Jason C. Allaire, and Keith E. Whitfield. "Understanding Within-Group Variability of Everyday Cognition in Aging Black/African American Adults: A Mimic (Multiple Indicators, Multiple Causes) Model Approach." Experimental Aging Research 38, no. 5 (2012): 488–510. http://dx.doi.org/10.1080/0361073x.2012.726022.
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Mourao, Paulo Reis. "Exploring the Likelihood of a Country Being a Tax Haven Using MIMIC Models." Econometric Research in Finance 5, no. 1 (2020): 17–32. http://dx.doi.org/10.2478/erfin-2020-0002.
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AbstractThe multiple indicators multiple causes (MIMIC) framework is used to analyze dimensions related to causation and indicators of tax haven status. Robust results were obtained that identify a country’s tax burden and area as causes of a country adopting policies usually observed in tax havens. The level of social security contributions as a proportion of public revenues and the ratio of indirect to direct taxes were found to be statistically significant indicators of tax havens. Data from 68 countries for more than twenty years were analyzed, enabling the results to contribute to a deepening of the current debate about tax havens and their socio-economic profiles.
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Rahman Maxim, Maruf, and Abu Sadat Muhammad Ashif. "A new method of measuring stock market manipulation through structural equation modeling (SEM)." Investment Management and Financial Innovations 14, no. 3 (2017): 54–61. http://dx.doi.org/10.21511/imfi.14(3).2017.05.
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This paper proposes a new model of measuring a latent variable, stock market manipulation. The model bears close resemblance with the literature on economic well-being. It interprets the manipulation of a stock as a latent variable, in the form of a multiple indicators and multiple causes (MIMIC) model. This approach exploits systematic relations between various indicators of manipulation and between manipulation and multiple causes, which allows it to identify the determinants of manipulation and an index of manipulation simultaneously. The main reason of stock market manipulation comes from the fact that information availability is not universally equal. The manipulation is thus critically linked to the creation, arrival and dissemination of information or rumors/mis-information. Thus, the immediate impact of manipulation is on the time profile of returns, or excess returns, from an asset and the excess volatility of returns in excess of the volatility explained by the fundamentals. In this basic setup, the model used these two variables as the indicators of stock market manipulation. The main intuition of the MIMIC approach is that some variables, or statistics, related to peace are indicators of manipulation, while others signify effects or outputs of causal factors, or inputs, of manipulation. In other words, distinction can be made between causes of manipulation and indicators of manipulation. The causal factors used in this model are classified into five different domains namely pure economic factors as determinants of manipulation, labor market conditions, international factors, quality of governance factors and systematic risk factors.
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Guan, Ming. "Associations Between Perceptions of the Work Environment and Job Burnout Based on MIMIC Models Among 679 Knowledge Workers." SAGE Open 11, no. 1 (2021): 215824402199938. http://dx.doi.org/10.1177/2158244021999384.
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In the current times, knowledge work and knowledge worker play an important role in organizational development. The purpose of this paper is to examine the associations between perceptions of the work environment and job burnout among 679 knowledge workers with a publicly available data. Based on the exploratory factor analysis, five multiple indicators multiple causes (MIMIC) models are acceptable and confirm, including socioeconomic factors→perceptions of the work environment model, socioeconomic factors→job burnout model, perceptions of the work environment←socioeconomic factors→job burnout model, perceptions of the work environment→job burnout model, and job burnout→perceptions of the work environment model. The results from MIMIC models indicated job burnout has significant associations with perceptions of the work environment. The implications of these results for well-beings among the knowledge workers are discussed.
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Wahyudi, Hasbi. "Pengaplikasian Multiple Indicator Multiple Causes (MIMIC) Model dalam Mendeteksi Differential Item Functioning (DIF) pada Alat Ukur Social Quality of Life." Jurnal Pengukuran Psikologi dan Pendidikan Indonesia (JP3I) 8, no. 1 (2019): 25–36. http://dx.doi.org/10.15408/jp3i.v8i1.12851.
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AbstractThis study aims to detect DIF (differential item functioning) on a quality of life measurement tool that measures one aspect, namely social quality of life. Social quality of life contains 24 items developed from the Patient Reported Outcomes Measurement Information System (PROMIS) by a National Institutes of Health (NIH). This measuring tool measures the quality of life in the social function domain of adolescent patients suffering from diseases or chronic medical conditions. Detection of DIF in this study uses a special case approach from CFA, namely CFA with covariate or multiple indicator multiple causes (MIMIC) models. This study involved 322 participants, 117 (36%) male participants and 205 (64%) female participants, with an age range between 13-23 years in Riau Province. Based on the results of the first order CFA on a set of social quality of life items there are 22 valid items. Then the MIMIC model analysis results found that the model is fit with data where the value of RMSEA = 0.048, so it is known two items that contain DIF, namely item 5 (0.135, P = 0.002) "I have a close friend" and item 23 (0.308, P = 0.002 ) "I hope to have lots of friends".Keywords: Social quality of life, MIMIC model, differential item functioningAbstrakPenelitian ini bertujuan untuk mendeteksi DIF (differential item functioning) pada alat ukur quality of life yang mengukur salah satu aspek yaitu social quality of life. Social quality of life berisi 24 item yang dikembangkan dari Patient Reported Outcomes Measurement Information System (PROMIS) oleh sebuah badan National Institutes of Health (NIH). Alaalat ukur ini mengukur kualitas hidup pada domain fungsi sosial pasien remaja yang menderita penyakit atau kondisi medis kronis. Pendeteksian DIF pada penelitian ini menggunakan pendekatan kasus khusus dari CFA, yakni CFA with covariate atau multiple indicator multiple causes (MIMIC) model. Penelitian ini melibatkan 322 partisipan, yakni sebanyak 117 (36%) partisipan laki-laki dan 205 (64%) partisipan perempuan, dengan rentang usia antara 13-23 tahun di Propinsi Riau. Berdasarkan hasil first order CFA pada sekumpulan item-item social quality of life terdapat 22 item yang valid. Kemudian hasil analisis model MIMIC ditemukan bahwa model fit dengan data dimana nilai RMSEA = 0.048, sehingga diketahui dua item yang mengandung DIF, yaitu item 5 (0.135, P = 0.002) “saya memiliki teman dekat” dan item 23 (0.308, P = 0.002) “saya berharap mempunyai banyak teman”.Kata kunci: Social quality of life, MIMIC model, differential item functioning
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Nchor, Dennis, and Václav Adamec. "Unofficial Economy Estimation by the MIMIC Model: the Case of Kenya, Namibia, Ghana and Nigeria." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 63, no. 6 (2015): 2043–49. http://dx.doi.org/10.11118/actaun201563062043.
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This study investigates the size and trend of the underground economies in selected African countries. Underground economies are present in all countries, but they are endemic in developing economies. Their presence is not necessarily bad for the economies, in which they prevail. It could however cause huge losses to government revenue and could also constitute serious violation of Labor regulations. The study uses the Multiple Indicators and Multiple Causes model (MIMIC), a variant of Simultaneous Equations Model (SEM). It involves two sets of variables: the observed variables and the indicator variables. The former include size of government, indirect tax rates, total tax rates, business regulation, interest rate on deposits, unemployment rate, quality of public services, and GDP per capita. The indicator variables were Labor participation rate in the official economy, the amount of cash held outside the banking system and growth in GDP per capita. This study found the average level of underground economies in Kenya, Namibia, Ghana and Nigeria as 33.7%, 29.1%, 36% and 47%, respectively. The estimated results show that the causes of shadow economic activities vary among the countries. The data was obtained from the World Bank country indicators and the International Financial Statistics.
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Dell’Anno, Roberto, Adriana AnaMaria Davidescu, and Nguling’wa Philip Balele. "Estimating shadow economy in Tanzania: an analysis with the MIMIC approach." Journal of Economic Studies 45, no. 1 (2018): 100–113. http://dx.doi.org/10.1108/jes-11-2016-0240.
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Purpose The purpose of this paper is to estimate the Tanzanian shadow economy (SE) from 2003 to 2015 and test the statistical relationships between the SE and its potential causes and indicators. Design/methodology/approach The econometric analysis is based on a multiple indicators multiple causes (MIMIC) model. To calibrate the SE from the estimates, the authors adopt the value of 55.4 percentage of the SE to official GDP from the literature for the base year 2005. Findings The SE ranges from 52 to 61 per cent of official GDP and slightly decreases from 2013 to 2015. Increase in inflation, unemployment and government spending were the main drivers of the SE dynamics. Research limitations/implications Given the challenges facing estimation of the SE (e.g. small sample size, exogenous estimate to calibrate the model, meaning of the latent variable), quantification of SE should be considered to be rough measures. Practical implications To lower the size of the SE, the government needs to keep inflation and unemployment stable over time, to reduce government spending because it creates pressure on tax collection due to the limited tax base. Originality/value This is the first study specifically focused on Tanzanian SE based on the MIMIC approach. Existing estimates of Tanzanian SE are calculated by monetary models or apply a common MIMIC specification to the worldwide context.
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Jamali, Jamshid, Seyyed Mohammad Taghi Ayatollahi, and Peyman Jafari. "The Effect of Small Sample Size on Measurement Equivalence of Psychometric Questionnaires in MIMIC Model: A Simulation Study." BioMed Research International 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/7596101.
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Evaluating measurement equivalence (also known as differential item functioning (DIF)) is an important part of the process of validating psychometric questionnaires. This study aimed at evaluating the multiple indicators multiple causes (MIMIC) model for DIF detection when latent construct distribution is nonnormal and the focal group sample size is small. In this simulation-based study, Type I error rates and power of MIMIC model for detecting uniform-DIF were investigated under different combinations of reference to focal group sample size ratio, magnitude of the uniform-DIF effect, scale length, the number of response categories, and latent trait distribution. Moderate and high skewness in the latent trait distribution led to a decrease of 0.33% and 0.47% power of MIMIC model for detecting uniform-DIF, respectively. The findings indicated that, by increasing the scale length, the number of response categories and magnitude DIF improved the power of MIMIC model, by 3.47%, 4.83%, and 20.35%, respectively; it also decreased Type I error of MIMIC approach by 2.81%, 5.66%, and 0.04%, respectively. This study revealed that power of MIMIC model was at an acceptable level when latent trait distributions were skewed. However, empirical Type I error rate was slightly greater than nominal significance level. Consequently, the MIMIC was recommended for detection of uniform-DIF when latent construct distribution is nonnormal and the focal group sample size is small.
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Dong, Guang-Hui, Zhengmin Qian, Qiang Fu, et al. "A Multiple Indicators Multiple Cause (MIMIC) Model of Respiratory Health and Household Factors in Chinese Children: The Seven Northeastern Cities (SNEC) Study." Maternal and Child Health Journal 18, no. 1 (2014): 129–37. http://dx.doi.org/10.1007/s10995-013-1245-6.
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Dell’Anno, Roberto, and Friedrich Schneider. "The Shadow Economy of Italy and other OECD Countries: What Do We Know?" Journal of Public Finance and Public Choice 21, no. 2 (2003): 97–120. http://dx.doi.org/10.1332/251569203x15668905422009.
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Abstract Various methods to estimate the size of the shadow economy are discussed and the results of the shadow economy of 21 OECD countries are presented. Then the specific case of Italy is investigated and the aim of this section is to produce an estimate of the Italian shadow economy with the MIMIC (Multiple Indicators and Multiple Causes) method. The procedure to obtain the underground economy as a share of official GDP is presented. The paper ends with some general conclusions about the reliability of the model approach and the efficacy of economic policies to reduce the shadow economy.
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Dell'Anno, Roberto, and Omobola Adu. "The size of the informal economy in Nigeria: a structural equation approach." International Journal of Social Economics 47, no. 8 (2020): 1063–78. http://dx.doi.org/10.1108/ijse-12-2019-0747.
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PurposeThis paper contributes to the literature concerning the Nigerian informal economy (IE) by estimating its size from 1991 to 2017 and identifying the major causes.Design/methodology/approachA structural equation approach in the form of the multiple indicators multiple causes (MIMIC) method is used to estimate the size of the Nigerian IE.FindingsThe results indicate that vulnerable employment and urban population as a percentage of the total population are the main drivers of the IE in Nigeria. The IE in Nigeria ranges from 38.83% to 57.55% of gross domestic product (GDP).Research limitations/implicationsAs a result of the empirical challenges in the estimation of the IE, the estimates of Nigeria's IE are considered to be rough estimates.Originality/valueThe authors calibrated the MIMIC model with the official estimate of the informal sector published by the Nigerian National Bureau of Statistics (NBS). This was an attempt to combine the national accounting approach, to estimate the size of IE, with the MIMIC approach, and to estimate the trend of informality.
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Žunić, Marijana, and Krunoslav Teslak. "Ograničavajući čimbenici izostanka aktivnosti na šumoposjedima u Republici Hrvatskoj – MIMIC model." Šumarski list 143, no. 1-2 (2019): 7–17. http://dx.doi.org/10.31298/sl.143.1-2.1.
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The purpose of this paper was to determine the share of active and inactive forest owners in Croatia and to identify potential causes for underuse of wood resources and their most important predictors based on inactive forest owners sample. We interviewed 1007 randomly selected forest owners on Croatian territory with a telephone survey. Of the total sample, 60% of forest owners believe that they efficiently manage their forests while 40% are inactive (Table 1). In order to determine the most important reasons and causes for inactive forest owners not cutting more, additional questions were asked. They were provided by 19 statements describing possible reasons for underuse of wood resources. Then, on Likert’s scale from 1 (not important at all) to 5 (very important) they expressed their level of agreement with a particular statement (Table 2). The statements were condensed into three dimensions by explanatory factor analysis with eigenvalue approach. Factors were interpreted as: (1) factor of qualifications and knowledge constraints, (2) factor of passiveness and forest conservation and (3) factor of physical constraints (Table 2). Statistically acceptable model was established by confirmatory factor analysis approach (Figure 2). The pronounced processes of structural changes in forest ownership composition, as well as in socio-demographic and forest property characteristics, are evident across Europe consequently influencing the intensity of private forest management. Within the aforementioned, we used gender, age, education, working status, the distance between the forest and the place of residence, the size of the settlement and the knowledge of forest property boundary lines as independent variables for management constraining factors model construction (Figure 1). Socio-demographic and forest property characteristics have been modeled with the extracted management constraining factors by applying a Multiple Indicators Multiple Causes (MIMIC) model (Figure 3). MIMIC model revealed that gender, age, and lack of boundary lines knowledge were the most important predictors for management constraining factors (Table 4). The notable part of forest owners in Croatia do not manage their forests because of insufficient knowledge and qualifications.
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Wang, Shi, Yizhou Yuan, and Hua Wang. "Corruption, Hidden Economy and Environmental Pollution: A Spatial Econometric Analysis Based on China’s Provincial Panel Data." International Journal of Environmental Research and Public Health 16, no. 16 (2019): 2871. http://dx.doi.org/10.3390/ijerph16162871.
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Previous studies show that the environmental quality is significantly influenced by corruption and the hidden economy separately. However, what is the impact of their interaction effect on environmental quality? Based on Multiple Indicators Multiple Causes (MIMIC) model, this study calculates the scale of hidden economy in Chinese provinces firstly. Then, we apply the method of spatial econometrics to analyze the interaction effect of corruption and the hidden economy on environmental pollution with China’s provincial panel data from 1998 to 2017. The results indicate that the interaction effect between corruption and hidden economy significantly increases pollutant discharge, suggesting that both anti-corruption and control of the hidden economy may improve environmental quality directly and indirectly.
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Buček, Jakub. "Determinants of the Shadow Economy in the Czech Regions: A Region-Level Study." Review of Economic Perspectives 17, no. 3 (2017): 315–29. http://dx.doi.org/10.1515/revecp-2017-0016.
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Abstract This paper investigates the size and development of the shadow economy in the Czech Republic on the state-level base over the 2005-2014 period. The multiple indicators multiple causes (MIMIC) model is used to assess the estimation of the shadow economy size. I investigate how labour market, number of people with at least one distraint, and the burden of taxation might contribute to the existence of the shadow economy. While the former two are important determinants of the shadow economy, I find no evidence to prove any significant impact of distraints on the shadow economy size. As for the country’s particular regions, I find that those surrounding big cities, especially Prague, have, on average, a smaller shadow economy size, whereas regions in the borderlands (former Sudetenland) suffer from a larger shadow economy.
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Wang, Ange, Hongzhi Guan, Yan Han, and Yangliu Cao. "Private Parking Space Sharing Intention in China: An Empirical Study Based on the MIMIC Model." Discrete Dynamics in Nature and Society 2021 (July 12, 2021): 1–13. http://dx.doi.org/10.1155/2021/9283686.
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The shared parking scheme improves the utilization rate of existing parking resources and contributes to the sustainable development of cities, but many private parking spaces that are not included in the shared parking scheme have a low utilization rate in China. In order to better promote the shared parking scheme, it is necessary to study the intention of the owners of private parking spaces to share their parking spaces. Therefore, this paper used the Unified Theory of Acceptance and Use of Technology (UTAUT) and Benefit-Risk Analysis Model (BRA) as the combined theoretical framework (C-UTAUT-BRA). Hypothesis testing using the Multiple Indicators and Multiple Causes (MIMIC) model was performed using an empirical assessment of the shared parking scheme in China. The results show that (1) the sharing behavioral intention (BI) is directly affected by perceived benefit (PB), perceived risk (PR), social influence (SI), and facilitating condition (FC) and indirectly affected by effort expectancy (EE), of which the total effect of PB is the largest; (2) exogenous variables have an indirect effect on BI through other psychological latent variables; among them, different sociodemographic and economic characteristics have a significant influence on different latent variables, while the built environment has no significant effect on latent variables. This research contributes to theory building in shared parking participation intention and informs business and government leaders on how to promote the shared parking scheme through the action mechanism of influencing factors on BI.
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Nazier, Hanan, and Racha Ramadan. "What empowers Egyptian women: resources versus social constrains?" Review of Economics and Political Science 3, no. 3/4 (2018): 153–75. http://dx.doi.org/10.1108/reps-10-2018-015.
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Purpose This paper aims to tackle an important question related to women’s economic empowerment in highly patriarchal societies like Egypt. The paper discusses individual, household, wealth and location factors determining women empowerment, as measured by two dimensions: decision-making power and mobility. Design/methodology/approach Using the “Egypt Labor Market Panel Survey” (ELMPS) 2012, a Multiple Indicators Multiple Causes (MIMIC) model was estimated to study the main economic resources and social constraints that determine women empowerment as measured by the power of women over household decisions and her freedom of movement in Egypt. Findings Three key messages could be delivered. First, women’s own economic resources as captured by her employment status are an important source of her empowerment. Second, contrary to theoretical prediction education is not playing its expected role in developing awareness and transforming ideas concerning gender roles in Egypt. Third, the importance of social local context is fundamental for Egyptian women empowerment. Originality/value This study is an attempt to address some of the gaps in the literature for the Egyptian case, where there is a lack in rigorous studies measuring women empowerment and examining its determinates. This is done by first, tackling multiple dimension of women’s empowerment, decision-making inside households and freedom of mobility. Second, using MIMIC model, which is a modeling approach that allows for studying the relations between several causes of a given latent variable, such as “Empowerment” in our case, and a number of its possible indicators, without a directly observable measure of the latent variable. Third, using the most recent set of data; the ELMPS 2012 which has a special focus on women’s resources and agency that permits greater content validity of the multidimensional setup. Forth, the macro level differences in women’s status are tackled through using location dummy variables. Finally, given the important correlation between wealth level and women empowerment, the paper is considered a first attempt to analyze such impact by including a variable that captures the wealth level of the woman’s household as one determinant of empowerment.
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Sun, Huiqian, Peng Jing, Mengxuan Zhao, Yuexia Chen, Fengping Zhan, and Yuji Shi. "Research on the Mode Choice Intention of the Elderly for Autonomous Vehicles Based on the Extended Ecological Model." Sustainability 12, no. 24 (2020): 10661. http://dx.doi.org/10.3390/su122410661.
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Due to the elderly’s limited physical ability, their mode choice behavior with particular demand for the traffic system is significantly distinguished compared to young people. The emergence of Autonomous Vehicles (AVs) and Shared Autonomous Vehicles (SAVs) will allow the elderly to travel independently and offer more mode choices. However, emerging vehicles will continue to coexist with other traditional modes such as public transport. This paper aims to explore the internal mechanism of the elderly’s choice behavior among public transport, AVs, and SAVs. We integrated the relevant factors by expanding the ecological model and used the Multiple Indicators and Multiple Causes (MIMIC) model to analyze the constructs’ relationship. The results show that the elderly believe that public transport, AVs, and SAVs are useful and convenient travel modes for themselves, affecting intention significantly. In addition, the elderly’s well-being and social influence during travel are also significant constructs for their behavioral intention. The research could provide academic supports for the traffic management departments when making relevant policies and measures for the elderly.
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Peng, Jing, Juan Zhi-cai, and Gao Lin-jie. "Application of the Expanded Theory of Planned Behavior in Intercity Travel Behavior." Discrete Dynamics in Nature and Society 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/308674.
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Congestion in intercity corridors of metropolitan area has been increasing steadily. To alleviate congestion, many major investment projects, such as the high speed railway projects, were proposed by agency. To evaluate the adequacy and efficiency of these projects, the intercity travel behavior should be analyzed in metropolitan area. The paper constructed a Multiple Indicators and Multiple Causes (MIMIC) model according to an expanded theory of planned behavior (TPB) to study the travel behavior of choosing from the choice set of the traditional train, the high speed railway and the coach by demographic and psychological factors. Through empirical data collection and analysis, we found that demographic factors of travelers indeed positively engender the latent variables in MIMIC, and descriptive norm and habit had direct or indirect significant effect on travel behavior and intention. On the basis of the effect of psychological constructors of the expanded TPB on the intercity travel behavior and differentiation of traveler's demographic characteristics, the agency can make reasonable policies and proper information for the intercity transportation. The results will support the basic theory of optimizing the transportation system in metropolitan area. Implications for researchers and suggestions for future research are also addressed in this study.
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Hagum, Cathrine Nyhus, and Shaher A. I. Shalfawi. "The Factorial Validity of the Norwegian Version of the Multicomponent Training Distress Scale (MTDS-N)." International Journal of Environmental Research and Public Health 17, no. 20 (2020): 7603. http://dx.doi.org/10.3390/ijerph17207603.
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Background: Athlete self-report measures (ASRM) are methods of athlete monitoring, which have gained considerable popularity in recent years. The Multicomponent Training Distress Scale (MTDS), consisting of 22 items, is a promising self-report measure to assess training distress among athletes. The present study aimed to investigate the factorial validity of the Norwegian version of MTDS (MTDS-N) among student-athletes (n = 632) attending the optional program subject “Top-Level Sports” in upper secondary schools in Norway. Methods: A confirmatory factor analysis (CFA) was conducted to assess the six-factor model proposed by Main and Grove (2009). McDonald’s omega (ω) along with confidence intervals (CIs) were used to estimate scale reliability. After examining the fit of the CFA model in the total sample, covariates were included to investigate group differences in latent variables of MTDS-N, resulting in the multiple indicators multiple causes (MIMIC) model. Further, direct paths between the covariates and the factor indicators were included in an extended MIMIC model to investigate whether responses to items differed between groups, resulting in differential item functioning (DIF). Results: When modification indices (MIs) were taken into consideration, the alternative CFA model revealed that MTDS-N is an acceptable psychometric tool with a good fit index. The factors in MTDS-N all constituted high scale reliability with McDonald’s ω ranging from 0.725–0.862. The results indicated statistically significant group differences in factor scores for gender, type of sport, hours of training per week, school program, and school level. Further, results showed that DIF occurred in 13 of the MTDS-N items. However, after assessing the MIMIC model and the extended MIMIC model, the factor structure remained unchanged, and the model fit remained within acceptable values. The student-athletes’ reports of training distress were moderate. Conclusion: The MTDS-N was found to be suitable for use in a Norwegian population to assess student-athletes’ training distress in a reliable manner. The indications of group effects suggest that caution should be used if one is interested in making group comparisons when the MTDS-N is used among student-athletes in Norway until further research is conducted.
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Květon, Petr, Martin Jelínek, Iva Burešová, and Kateřina Bartošová. "Czech adaptation of the Brunel Mood States for adolescent athletes." Studia sportiva 14, no. 1 (2020): 47–57. http://dx.doi.org/10.5817/sts2020-1-6.
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The Brunel Mood States is a 24-items long questionnaire (formerly referred to as the Profile of Mood States for Adolescents POMS-A) used to capture emotional profile of an individual. It has been used in various settings including sport psychology, where it is considered a valid indicator for overtraining syndrome. The aim of this study was to develop the Czech adaptation of BRUMS and verify its psychometric properties in adolescent athletes. The data were collected from a sample of 246 participant (50.8% females; age range 14-19 years). Confirmatory factor analysis was used to evaluate original six-dimensional structure (with factors of Depression, Tension, Confusion, Anger, Fatigue, and Vigor). Even though this model showed acceptable fit to the data, Depression and Tension factors were empirically indistinguishable. Therefore, we proposed and verified alternative five-factor model with these two factors collapsed. Measurement invariance across gender was assessed using the Multiple Indicators Multiple Causes (MIMIC) model. Although three items showed signs of differential item functioning, the Czech adaptation of the instrument can in general be considered a measurement invariant.
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Lyulyov, Oleksii, and Bogdan Moskalenko. "Institutional Quality and Shadow Economy: An Investment Potential Evaluation Model." Virtual Economics 3, no. 4 (2020): 131–46. http://dx.doi.org/10.34021/ve.2020.03.04(7).
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The article summarizes some arguments as regards the scientific challenge on improving approaches to evaluating the country’s investment potential. The main objective of the research is to identify the features and perspectives of applying the variables such as the shadow economy and the integrated institutional quality index into a model evaluating the country’s investment potential. To solve this task, systematization of the related theoretical and methodological materials has been done. The methodological tools of the research are carried out in the following logical sequence: systematization of existing statistical methods for estimating the shadow economy; time data series analysis; and regression analysis. The scope of the shadow economy could be estimated as a dependent variable, with both its determinants and indicators detected and measured. The macro methods, such as Multiple Indicators Multiple Causes (MIMIC) are suitable approaches from an econometric standpoint to evaluate the shadow economy. Institutional quality is crucially an important variable for empirical studies related to evaluating the country’s investment potential. The proposed approach considers significance and direction of the six Worldwide Government Indicators’ (WGI) impact on foreign direct investment net inflow, eliminating the issue of their multicollinearity. However, political instability and high frequency of foreign and domestic policy changes during the last decades distort statistical significance of the results obtained. FDI inflow, as well as the quality of governance, and the shadow economy, is influenced by many other factors, both internal and external, so to build a qualitative model for evaluating the country’s investment potential of the national economy it is necessary to expand the set of factors for analysis. The results of the research can be useful for a more accurate investment potential evaluation on the macroeconomic level, and forecasting foreign direct investment inflows for the following time periods.
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Pasovic, Edin, and Adnan S. Efendic. "Informal Economy in Bosnia and Herzegovina – An Empirical Investigation." South East European Journal of Economics and Business 13, no. 2 (2018): 112–25. http://dx.doi.org/10.2478/jeb-2018-0015.
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Abstract This paper explores the size of the informal economy in Bosnia and Herzegovina (BiH) over the period 1998- 2016, based on an indirect method of measurement known as the MIMIC approach (Multiple Input Multiple Causes). As the underlying determinants of the informal economy in BiH we include tax burden, the level of unemployment, the size of the agricultural sector and the level of government subsidies. We estimate that the average size of the informal economy for the observed period was 34% of GDP, with the largest percentage in 1998 (43%) and the smallest in 2009 and 2016 (30%). There is a modest decreasing trend in the size of the informal economy over time. Our model identifies two structural brakes over the observed period. The first is positive and is linked to the introduction of the value added tax in 2006 (a decrease in 2007-2009 follows). The second captures a short-run negative effect of the latest global economic crisis in 2009 (an increase between 2010-2011). To further asses these results and check their consistency with available primary data, we investigate the size of the undeclared work, assess tax morality and the additional income of families coming from informal sector. These indicators provide consistent results with those of the MIMIC approach.
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Sunderland, M., T. Slade, and R. F. Krueger. "Examining the shared and unique relationships among substance use and mental disorders." Psychological Medicine 45, no. 5 (2014): 1103–13. http://dx.doi.org/10.1017/s0033291714002219.
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Background.Co-morbidity among use of different substances can be explained by a shared underlying dimensional factor. What remains unknown is whether the relationship between substance use and various co-morbid mental disorders can be explained solely by the general factor or whether there remain unique contributions of specific substances.Method.Data were from the 2007 Australian National Survey of Mental Health and Wellbeing (NSMHWB). A unidimensional latent factor was constructed that represented general substance use. The shared and specific relationships between lifetime substance use indicators and internalizing disorders, suicidality and psychotic-like experiences (PLEs) were examined using Multiple Indicators Multiple Causes (MIMIC) models in the total sample. Additional analyses then examined the shared and specific relationships associated with substance dependence diagnoses as indicators of the latent trait focusing on a subsample of substance users.Results.General levels of latent substance use were significantly and positively related to internalizing disorders, suicidality and psychotic-like experiences. Similar results were found when examining general levels of latent substance dependence in a sample of substance users. There were several direct effects between specific substance use/dependence indicators and the mental health correlates that significantly improved the overall model fit but they were small in magnitude and had relatively little impact on the general relationship.Conclusions.The majority of pairwise co-morbid relationships between substance use/dependence and mental health correlates can be explained through a general latent factor. Researchers should focus on investigating the commonalities across all substance use and dependence indicators when studying mental health co-morbidity.
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Wong, Ming-Yu Claudia, Pak-Kwong Chung, and Ka-Man Leung. "Examining the Exercise and Self-Esteem Model Revised with Self-Compassion among Hong Kong Secondary School Students Using Structural Equation Modeling." International Journal of Environmental Research and Public Health 18, no. 7 (2021): 3661. http://dx.doi.org/10.3390/ijerph18073661.
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The association between physical activity in achieving mental health benefits and subjective well-being is consistently identified by empirical research. The causation of a positive self-concept created by physical exercise is empirically supported by Sonstroem and Morgan’s (1988) exercise and self-esteem model (EXSEM). However, various drawbacks of maintaining high self-esteem have been identified; thus, the concept of self-compassion was conjectured to be a form of “true self-esteem.” Hence, the current study aimed to investigate the relationship between physical activity and self-compassion by examining the exercise and self-esteem model revised with self-compassion (EXSEM-SC). This study recruited secondary school students from Hong Kong using convenience sampling. The structural equation modeling (SEM) approach, including path analysis and multiple indicators, multiple causes (MIMIC) modeling, were used to reveal the results of the study. The results (n = 1097) indicated that the relationship between physical activity and self-compassion could be demonstrated by the EXSEM-SC, with a satisfactory goodness-of-fit index in the SEMs. The SEM also demonstrated the direct paths from physical activity to self-compassion and mental well-being, indicating the significant effect of physical activity on self-compassion.
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Hetzel, Christian, Torsten Alles, and Ingo Froböse. "„Berliner Inventar zur Angehörigenbelastung – Demenz Praxisversion (BIZA-D-PV)“ auch für den nicht demenziellen Bereich?" Diagnostica 65, no. 3 (2019): 153–65. http://dx.doi.org/10.1026/0012-1924/a000221.
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Zusammenfassung. Pflegende Angehörige sind eine vulnerable Zielgruppe mit zunehmender Bedeutung. Es gibt insbesondere im nicht-demenziellen Bereich wenig Evidenz zu Unterstützungs- und Entlastungsangeboten. Für indikationsübergreifende Evaluationsstudien hat das mehrdimensionale Berliner Inventar zur Angehörigenbelastung – Demenz Praxisversion (BIZA-D-PV) konzeptionelles Potenzial. Es soll die Teststatistik des BIZA-D-PV im nicht-demenziellen und im demenziellen Bereich geprüft werden. Das Instrument hat 33 Items in 7 Skalen. Die Datenbasis waren 161 pflegende Angehörige im nicht-demenziellen Bereich und 133 im demenziellen Bereich. Es wurden explorative Faktorenanalysen und ein Multiple Indicators Multiple Causes (MIMIC) Modell eingesetzt. Die faktorielle Validität und die Reliabilitäten sind in beiden Stichproben vergleichbar und gut. Populationsheterogenität sowie Relationen der Skalen insbesondere mit selbstberichteter Depressivität deuten auf Konstruktvalidität hin. Das BIZA-D-PV ist auch im nicht-demenziellen Bereich ein reliables und faktoriell valides Instrument. Hinweise auf Konstruktvalidität liegen vor, bedürfen aber der weiteren Fundierung.
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Gökcan, Mustafa, and Derya Çobanoğlu Aktan. "Investigation of the variables related to TEOG English achievement using Language Acquisition Theory of Krashen." Pegem Eğitim ve Öğretim Dergisi 8, no. 3 (2018): 531–66. http://dx.doi.org/10.14527/pegegog.2018.021.
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In this study, the effects of students’ attitude towards English, foreign language anxiety, exposure to English, school type (i.e. state or private), parents’ English proficiency and education level on the students’ English achievement in TEOG exam are investigated. To achieve this goal, a multiple indicators and multiple causes (MIMIC) model has been developed, and tested based on Stephen Krashen’s language acquisition theory and the literature. According to the research results, attitudes towards English, school type, amount of English exposure, parents’ education level and English proficiency have meaningful and positive effects on English proficiency, while language anxiety has a meaningful but negative effect on it. Moreover, it was found that the effects of parents’ education level and English proficiency and the students’ attitudes towards English on English proficiency are mediated by exposure to English. Therefore, Krashen’s second language acquisition theory stating that those who have positive attitudes towards English will seek more comprehensible input and so will be more exposed to English and consequently will acquire English more is validated.
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Karalunas, Sarah L., Karen L. Bierman, and Cynthia L. Huang-Pollock. "Test–Retest Reliability and Measurement Invariance of Executive Function Tasks in Young Children With and Without ADHD." Journal of Attention Disorders 24, no. 13 (2016): 1891–904. http://dx.doi.org/10.1177/1087054715627488.
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Objective: Measurement reliability is assumed when executive function (EF) tasks are used to compare groups or to examine relationships between cognition and etiologic and maintaining factors of psychiatric disorders. However, the test–retest reliabilities of many commonly used EF tasks have rarely been examined in young children. Furthermore, measurement invariance between typically developing and psychiatric populations has not been examined. Method: Test–retest reliability of a battery of commonly used EF tasks was assessed in a group of children between the ages of 5 and 6 years old with ( n = 63) and without ( n = 44) ADHD. Results: Few individual tasks achieved adequate reliability. However, confirmatory factor analysis (CFA) models identified two factors, working memory and inhibition, with test–retest correlations approaching 1.0. Multiple indicators multiple causes (MIMIC) models confirmed configural measurement invariance between the groups. Conclusion: Problems created by poor reliability, including reduced power to detect group differences, index change over time, or to identify relationships with other measures, may be mitigated using latent variable approaches.
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Haegert, David G. "Multiple Sclerosis: A Disorder of Altered T-Cell Homeostasis." Multiple Sclerosis International 2011 (2011): 1–6. http://dx.doi.org/10.1155/2011/461304.
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Uncertainty exists as to whether similar or different mechanisms contribute to the pathogenesis of different subtypes of multiple sclerosis (MS). Detailed analysis of naive T cell homeostasis shows that patients with relapsing-remitting MS (RRMS) and with primary progressive MS (PPMS) have early-onset thymic involution that causes reduced thymic output. The reduced thymic output leads to secondary peripheral homeostatic alterations in naïve CD4 T-cells, which closely mimic T-cell alterations observed in an experimental animal model of diabetes mellitus. Homeostatic T-cell receptor (TCR) signalling and proliferation of naïve T cells are induced by self-peptides. Consequently, the findings of increased TCR signalling of naïve CD4 T-cells, without increased proliferation, in PPMS, and the increased homeostatic proliferation of naïve CD4 T-cells in RRMS favour the development of autoimmunity. Thus, it seems highly likely that peripheral T-cell alterations secondary to a thymic abnormality contribute to the pathogenesis of both MS subtypes.
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Sánchez-Domínguez, Ricardo, Luis Villalobos-Gallegos, Violeta Felix-Romero, Silvia Morales-Chainé, and Rodrigo Marín-Navarrete. "Effect of substance use on condom use in the Theory of Planned Behavior: Analysis of differential item functioning." Salud mental 40, no. 1 (2017): 5–14. http://dx.doi.org/10.17711/sm.0185-3325.2017.002.
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Introduction. Substance use is one of the factors associated with lower condom use in young adults, which increases the likelihood of HIV infection. The Theory of Planned Behavior (TPB) is one of the most useful models for explaining this phenomenon since it considers the aim of engaging in a behavior based on attitudes, subjective norms and self-efficacy. Objective. To develop a questionnaire and to evaluate the Differential Item Functioning (DIF) caused by substance use in TPB indicators, using the Multiple Indicators Multiple Causes Analysis (MIMIC). Method. The study was conducted in two phases with Mexico City college students age 18 to 25. Results. Adequate goodness of fit was obtained in all three models of the TPB: attitudes χ2S-B(2) = 3.902, p < .001; CFIs = .999; TLIs = .996; RMSEAs = .037, 90% CI ≤ .001-.095; subjective norms χ2S-B(7) = 9.103, p < 0.245; CFIs = .999; TLIs = .998; RMSEAs = .022, 90% CI ≤ .001-.056; and self-efficacy χ2S-B(25) = 65.115, p < .001; CFIs = .982; TLIs = .974; RMSEAs = .050, 90% CI = .036-.066; in one item in attitudes and two items in subjective norms a DIF effect was observed, while no item proved significant regarding self-efficacy. Discussion and conclusion. There is little evidence in the detection of DIF due to substance use in TPB indicators in condom use, and this is the first study to conduct this type of analysis. Items presenting DIF open the door to future research due to the importance of assessing how the indicator behaves with a population displaying a particular trait.
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Merfazi, Muhammad, Sugiarto Sugiarto, and Renni Anggraini. "PERSEPSI MASYARAKAT TERHADAP KEBIJAKAN TRANS KOETARADJA PADA KORIDOR PUSAT KOTA – MATA IE DAN PUSAT KOTA – AJUN – LHOKNGA MENGGUNAKAN INDIKATOR VARIABEL LATEN." Jurnal Arsip Rekayasa Sipil dan Perencanaan 2, no. 1 (2019): 58–67. http://dx.doi.org/10.24815/jarsp.v2i1.13204.
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Community dependence on private transportation modes is a major factor in congestion in Banda Aceh. For this reason, the Aceh government implemented the operation policy of Trans Koetaradja to reduce the impact of congestion. Community perception is one of the important aspects in policy making, because by involving the community, decision makers will be able to capture the views, needs and expectations of the community. The purpose of this study is to examine public perceptions of the Trans Koetaradja policy as a case study at 2 (two) corridors, City Center - Mata Ie and City Center - Ajun - Lhoknga. The data collection method used was Stated Preference (SP) with a total of 220 respondents by stratified random sampling. The SP questionnaire contains information about socio-economic, travel behavior, and respondents' perceptions. The result of perception showed that all psychological questions had a good value above 2.5 (average) which was 2.81 (70.20%) from the reference of the 1-4 Likert scale with the indicator with the highest level of acceptance of 3.32 that was a private vehicle needed in everyday life. Data processing and analysis used the Multiple Indicators Multiple Causes (MIMIC) model which was one of the branches of Structural Equation Modeling (SEM), the regression parameters calibrated using Lisrel 9.3 software to produce a measurement model that was the perception of "personal mode dependence (t-value, 5.13)", whereas in the structural model produced five multiple regression equations with the most significant factor affecting each latent variable was "education".
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Pérez, Efrén O. "The Origins and Implications of Language Effects in Multilingual Surveys: A MIMIC Approach with Application to Latino Political Attitudes." Political Analysis 19, no. 4 (2011): 434–54. http://dx.doi.org/10.1093/pan/mpr029.
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The study of Latino public opinion has renewed interest in the relationship between language and survey response. However, extant research generally relies on statistical methods that cannot distinguish between two related yet distinct types of language effects in Latino surveys: (1) differences inattitudeand (2) differences inmeasuresof attitude. The former reflects varied levels of a latent attitude between English and Spanish interviewees. The latter—formally known as Differential Item Functioning (DIF)—refers to linguistic differences in the interpretation of survey items, which lead Latino respondents to misreport their level of attitude. This paper proposes Multiple Indicators Multiple Causes models to decouple these two types of language effects. Using this modeling framework, I examine language differences in measures of subjective and factual political attitudes from theLatino National Survey(2006). I find that the language of interview systematically colors Latinos' interpretation of survey items, even after controlling for measurement error and individual differences in the latent variable being assessed. I then show through an applied analysis how ignoring language DIF can yield misleading inferences about hypothesized relationships between variables. Together, these findings highlight a need for greater theoretical work on the psychological origins of language effects in multilingual political surveys.
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Rodríguez-Moreno, Javier, Ana María Ortiz-Colón, Eulogio Cordón-Pozo, and Miriam Agreda-Montoro. "The Influence of Digital Tools and Social Networks on the Digital Competence of University Students during COVID-19 Pandemic." International Journal of Environmental Research and Public Health 18, no. 6 (2021): 2835. http://dx.doi.org/10.3390/ijerph18062835.
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The pandemic caused by COVID-19 has generated a transformation in students’ competences and university education, especially in the use of digital tools. This study aims to analyze the use of digital tools and social networks of university students during the COVID-19 pandemic. For the collection of information, a validated Likert questionnaire (10-point scale) was adopted. The instrument consisted of a total of 66 items comprising a total of seven dimensions. The sample contained 581 students pursuing degrees in Childhood Education and Primary Education. The analysis of the available information was carried out in two different stages. First, we started by performing an exploratory factorial analysis (EFA) to determine the underlying structure of the Digital Competence of Higher Education Students (DCHES) scale factor. In the second phase, we used SEM (structural equation modeling), a statistical approach to test the relationships between observed and latent variables. More specifically, we estimated a multiple indicators multiple causes (MIMIC) model. The results showed the importance of two of the considered covariates in explaining the variability of the different dimensions of the scale analyzed (DCHES) considering the use of social networks and digital tools of university students. In this sense, both the degree to which virtual tools are used to develop teamwork and the degree of use of YouTube when communicating most fully explained the level of digital skills among the university students studied.
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Ficko, Andrej. "Private Forest Owners’ Social Economic Profiles Weakly Influence Forest Management Conceptualizations." Forests 10, no. 11 (2019): 956. http://dx.doi.org/10.3390/f10110956.
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Although several private forest owner studies have dealt with how private forest owners understand forest management, little is known about the determinants of specific forest management concepts. The study expands previous latent variable models of the perception of forest management by European private forest owners by looking at how age, income, education, annual cut, and holding size and type influence specific understandings of forest management. We applied a multiple indicators multiple causes (MIMIC) structural equation model on a representative sample of 754 private forest owners from Slovenia. The MIMIC model confirmed the influence of six covariates on three concepts of forest management: the maintenance concept, the ecosystem-centered concept, and the economics-centered concept. The strongest determinants of perception were education and holding type. The maintenance concept was predominantly associated with less educated older full-time or part-time farmers working on smaller family farms and doing regular cuts. The perception of forest management as an economics-centered activity increased with increased education and dependence on income from intensive cuts. The ecosystem-centered concept was most strongly associated with younger, better-educated owners with smaller holdings and, surprisingly, not to non-farmers but to small-scale family farmers. However, the proportion of the variance of latent variables explained by the six covariates was low, ranging from 2.4% to 5.1%. Taking into account the influence of education and holding type on private forest owners’ perception of forest management, by increasing the level of education and raising the proportion of absentee owners in Europe, we expect a shift from the maintenance concept toward either an economics-centered or ecosystem-oriented concept for forest management. Despite the weak influence of private forest owners’ social economic profiles on forest management conceptualizations, governments should be aware of the trend and actively seek to prevent the polarization of forest management concepts.
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Chalimourdas, Theodoros, Silia Vitoratou, Efstathia Matsouka, et al. "Psychometric Properties, Factor Structure, and Evidence for Measurement Invariance in the Greek Version of the Disgust Scale-Revised (DS-R)." Diseases 7, no. 2 (2019): 33. http://dx.doi.org/10.3390/diseases7020033.
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The Disgust Scale has been designed to measure disgust propensity—the individual ease in experiencing disgust. The present study aimed to explore the validity, reliability, the factor structure, and the measurement invariance of the Greek version of the Disgust Scale-Revised (DS-R). A sample of 754 healthy participants completed the Greek version of the DS-R. A subset (n = 363) also completed the revised Symptom checked list and the Eysenck Personality Questionnaire, in order to examine the concurrent validity. Exploratory and Confirmatory factor analyses in different subsets were used to examine the factor structure. Multiple indicators–multiple causes model (MIMIC) models were used to assess the measurement invariance across gender and age. Demographic influences were assessed using t-tests, ANOVA, and Pearson’s correlations. Exploratory factor analysis concluded to two and three factor models, with a factor structure similar to the ones proposed in the literature. Confirmatory factor analysis and bi-factor analysis provided evidence in favor of the three-factor solution. Measurement invariance test revealed differences in six items across gender, and three items across age. The psychometric properties of the factors were satisfactory. Demographic influences on the responses were present, especially with respect to gender. The Greek version of the DS-R demonstrated satisfactory psychometric properties, making it suitable for use for the Greek population.
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Grzelak, Aleksander, Jakub Staniszewski, and Michał Borychowski. "Income or Assets—What Determines the Approach to the Environment among Farmers in A Region in Poland?" Sustainability 12, no. 12 (2020): 4917. http://dx.doi.org/10.3390/su12124917.
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The theory about the impact of farm size, income and assets on the environmental approach of farmers is ambiguous. We contribute to the existing discussion in two ways. Firstly, we look for the determinants of the environmental approach. Secondly, we treat farm size as a heterogeneous factor, affected not only by the value of assets but also flows of incomes. The main objective of the article is, therefore, to recognize the impact of assets and income on the environmental approach of agricultural producers. We analyze the results of surveys carried out in 2020 on a group of 120 farms from the Wielkopolska region (Poland), using structural equation modelling (generalized structural equation modelling (GSEM)-multiple indicators and multiple causes (MIMIC) model). Our results indicate that both the income and assets of the agricultural producers have a positive impact on their approach to the environment. However, to a greater extent, the farmer’s approach to the environment is influenced more by income than by assets. This may be influenced by the capitalization of subsidies in the price of agricultural land, which makes this element of farm assets detached from real processes. It is easier for farms with a higher income and assets to realize the orientation towards sustainability.
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Jeong, Yerim, Yaebon Kim, and Sujin Yang. "First-Time Mothers’ Grit, Spousal Support, and Age, and Their Relationships with Nurturing Passion, Postpartum Depression, and Happiness." Journal of The Korean Society of Maternal and Child Health 25, no. 3 (2021): 177–83. http://dx.doi.org/10.21896/jksmch.2021.25.3.177.
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Purpose: This study aimed to examine whether first-time mothers’ grit, spousal support, and age can make significant differences in latent means of child-rearing passion, postpartum depression, and happiness. Methods: Data were collected from April 2 to July 16, 2019. Two hundred sixteen first-time mothers of infants and toddlers aged 0–2 years participated in a self-reported questionnaire study in which scales of nurturing passion, postpartum depression, happiness, grit, and spousal support were included. The collected data were analyzed with IBM SPSS ver. 18.0 (IBM Co., Armonk, NY, USA) for descriptive statistics and Pearson correlation analyses. In addition, Mplus (ver. 7.0) was used for the Multiple Indicators Multiple Causes (MIMIC) model approach. Results: The MIMIC model yielded an appropriate fit to the data (χ<sup>2</sup>=103.74, degrees of freedom=53, comparative fit index=0.96, root mean square error of approximation=0.07, standardized root mean square residual=0.05). The paths from grit and spousal support all had significantly positive beta coefficients (p<0.05) to child-rearing passion (β=0.3 and β=0.26, respectively) and happiness (β=0.22 and β=0.39, respectively), while the corresponding paths to postpartum depression were all negatively significant (β= -0.24 for both). These results suggest that unlike chronological maturity (i.e., age), grittier individuals with stronger spousal support display greater passion for child-rearing, as well as greater happiness. In a similar vein, they suffered less from postpartum depression. Conclusion: These results imply that grit can be employed to enhance first-time mothers’ child-rearing passion and happiness as it can also concurrently offset the effects of a negative labor and child-birth experience on first-time mothers’ mental health, e.g., in terms of reducing postpartum depression.
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Gurnani, A., and B. Gavett. "The Colorado Cognitive Assessment (CoCA): Development of an Advanced Test of Cognitive Status." Archives of Clinical Neuropsychology 34, no. 6 (2019): 844. http://dx.doi.org/10.1093/arclin/acz035.12.
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Abstract Objective Current brief tests of cognition provide a rough indication of overall cognitive functioning that assist with making gross clinical judgments (e.g., demented vs. not demented). The purpose of the present study was to develop and preliminarily validate a brief tool, The Colorado Cognitive Assessment (CoCA) to facilitate early and accurate diagnosis of mild and atypical presentations of dementia. A related goal was to compare its psychometric properties with The Montreal Cognitive Assessment (MoCA). Method Participants were 150 community dwelling adults over the age of 50 without a known mental health or neurological condition. Confirmatory factor analysis (CFA) was used to assess model fit of the CoCA and MoCA. Measurement invariance (MI) was evaluated using the multiple-indicators multiple-causes modeling (MIMIC) approach. Results The CFA model of the CoCA revealed excellent fit; χ2(44) = 47.506, p = .332; CFI = 0.987; TLI = 0.983; RMSEA = 0.023 (90% CI [0.000, 0.061]); SRMR = 0.048. MI analyses revealed that items on the CoCA were invariant to sex, age, education, and mood. In comparison, a CFA model of the MoCA had worse fit; χ2(14) = 28.536, p = .012; CFI = 0.817, TLI = 0.725; RMSEA = 0.083 (90% CI [0.038, 0.127]); SRMR = 0.062; and was biased by age, education, and depressive symptomatology. The global factor score reliability of the CoCA (r = .84) was better than the MoCA (r = .74). Conclusion Results provide preliminary evidence for the CoCA as a reliable and comprehensive cognitive instrument with further cross-sectional and longitudinal research needed for its validation.
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Francoeur, Richard. "Symptom profiles of subsyndromal depression in disease clusters of diabetes, excess weight, and progressive cerebrovascular conditions: a promising new type of finding from a reliable innovation to estimate exhaustively specified multiple indicators–multiple causes (MIMIC) models." Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy Volume 9 (December 2016): 391–416. http://dx.doi.org/10.2147/dmso.s118432.
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Uysal, Nermin Kibrislioglu, and Kubra Atalay Kabasakal. "The Effect of Background Variables on Gender DIF." European Journal of Multidisciplinary Studies 5, no. 1 (2017): 490. http://dx.doi.org/10.26417/ejms.v5i1.p490-490.
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The purpose of this study is to investigate the presence of differential item functioning (DIF) between gender groups in PISA 2015 science items in nine selected countries. Moreover, the effect of socioeconomic status, reading ability, science self-efficacy and science motivation on the presence of gender-related DIF are examined, respectively. One cluster from computer-based assessment (CBA) is taken into consideration. The countries are selected among the ones that implemented CBA, on the basis of their rank in science achievement. Multiple Indicator Multiple Causes method (MIMIC) is used in our analysis. DIF analysis in the MIMIC involves fit comparisons of both full and reduced models to determine if the items can measure the latent trait equally among the specified groups. The MIMIC analysis is conducted in two steps. First, the items is being tested for showing DIF among gender groups. Then the socioeconomic status, the reading ability, the science self-efficacy and the motivation are added to the model to test gender-related DIF items and their effects, respectively. According to results of the study, gender-related DIF appeared in all of the selected countries vary between two and six items. In four of the countries none of the selected variables significantly affect the presence of gender-related DIF. Instead, in the remaining countries the number of gender-related DIF items is reduced by adding different combinations of the selected variables to the model. The effect of variables which reduce the number of gender-related DIF items will discussed within each country.