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Journal articles on the topic 'Two-factor analysis of variance'

Author: Grafiati

Published: 28 May 2022

Last updated: 31 July 2025

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1

Even-Tzur, Gilad. "Variance Factor Estimation for Two-Step Analysis of Deformation Networks." Journal of Surveying Engineering 130, no. 3 (2004): 113–18. http://dx.doi.org/10.1061/(asce)0733-9453(2004)130:3(113).

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Ding, Peng. "Two seemingly paradoxical results in linear models: the variance inflation factor and the analysis of covariance." Journal of Causal Inference 9, no. 1 (2021): 1–8. http://dx.doi.org/10.1515/jci-2019-0023.

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Abstract A result from a standard linear model course is that the variance of the ordinary least squares (OLS) coefficient of a variable will never decrease when including additional covariates into the regression. The variance inflation factor (VIF) measures the increase of the variance. Another result from a standard linear model or experimental design course is that including additional covariates in a linear model of the outcome on the treatment indicator will never increase the variance of the OLS coefficient of the treatment at least asymptotically. This technique is called the analysis

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Tsorin, I. B. "Application of variance analysis in experimental pharmacology." Pharmacokinetics and Pharmacodynamics, no. 1 (May 10, 2023): 3–23. http://dx.doi.org/10.37489/2587-7836-2023-1-3-23.

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The article discusses various types of variance analysis: one-factor, two-factor, repeated measurements, including detailed analysis of variance categorical data. The criteria of multiple comparisons are described: according to Bonferroni, according to Newman-Kales, according to Dunnet, according to Scheffe. All the methods considered are accompanied by examples of analysis of pharmacological data.

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Ahmed, Abdalla, and Walla Maruod. "Comparative analysis of varimax and Promax rotation methods in exploratory factor analysis." Edelweiss Applied Science and Technology 9, no. 5 (2025): 501–13. https://doi.org/10.55214/25768484.v9i5.6929.

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This study compares two widely used rotation techniques in exploratory factor analysis (EFA): Varimax, an orthogonal method, and Promax, an oblique method. Sample data from 394 students were analyzed using JASP software to evaluate the two methods. Both rotations identified latent constructs influencing academic achievement after factor extraction via principal axis factoring. Although both methods retained the same number of factors, the pattern and magnitude of variable loadings differed. The Kaiser-Meyer-Olkin (KMO) test indicated superior reliability for Promax, which achieved significantl

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Rein, Judith A. "Analyzing a Two-Factor within-Subjects Design Using Mystat." Perceptual and Motor Skills 77, no. 2 (1993): 440–42. http://dx.doi.org/10.2466/pms.1993.77.2.440.

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MYSTAT is used to analyze a two-way analysis of variance with repeated measures on both factors without running out of memory. The simple solution is executing the analysis in successive batches versus a simultaneous block.

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Kaya, Fahrettin. "Applying Permanova for Multivariate Analysis of Variance in Health Studies." Black Sea Journal of Engineering and Science 8, no. 2 (2025): 9–22. https://doi.org/10.34248/bsengineering.1611775.

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Abstract: Health data often do not meet the normality assumption, which limits the applicability of traditional analysis of variance methods. The aim of this study is to propose a methodological framework for analyzing such data by examining PERMANOVA (Permutational Multivariate Analysis of Variance), a method that does not require the normality assumption and is particularly suitable for complex datasets, within the context of maternal health data. In the context of maternal healthcare in Bangladesh, the effects of two independent variables—risk and age factors—on multivariate response variab

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Hsiung, Tung-Hsing, and Stephen Olejnik. "Contrast analysis for additive non-orthogonal two-factor designs in unequal variance cases." British Journal of Mathematical and Statistical Psychology 47, no. 2 (1994): 337–54. http://dx.doi.org/10.1111/j.2044-8317.1994.tb01041.x.

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Harrar, Solomon W., and Arne C. Bathke. "A modified two-factor multivariate analysis of variance: asymptotics and small sample approximations." Annals of the Institute of Statistical Mathematics 64, no. 1 (2010): 135–65. http://dx.doi.org/10.1007/s10463-010-0299-0.

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Amador-Campos, Juan Antonio, Maria Forns-Santacana, Bernardí Martorell-Balanzó, Joan Guàrdia-Olmos, and Maribel Peró-Cebollero. "Confirmatory Factor Analysis of Parents' and Teachers' Ratings of DSM-IV Symptoms of Attention Deficit Hyperactivity Disorder in a Spanish Sample." Psychological Reports 97, no. 3 (2005): 847–60. http://dx.doi.org/10.2466/pr0.97.3.847-860.

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Confirmatory factor analysis examined the factor structure of DSM-IV Attention Deficit Hyperactivity Disorder symptoms and analyzed the differences in informants' ratings of ADHD symptoms by children's age and sex. A sample of 1,018 Spanish school children, 574 girls and 444 boys, ages 4 to 12 years, was rated by teachers and parents. Confirmatory factor analysis showed a similar fit for the three-factor model of Inattention, Hyperactivity, and Impulsivity (teachers: CFI = .976, RMR = .041, % of total variance = 83.2; parents: CFI = .969, RMR = .037, % of total variance = 82.7) and for the two

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Milanes-Baños, Norma A. "Step-by-step one-way ANOVA analysis with the Jamovi program." Mexican Journal of Medical Research ICSA 12, no. 23 (2024): 22–26. http://dx.doi.org/10.29057/mjmr.v12i23.10664.

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ANOVA is the acronym for Analysis of Variance, which stands for Analysis of Variance, and is used to establish statistically significant differences between the means of two groups. Currently there are several programs that synthesize this work allowing us to analyse statistical data in a simpler way. In this manuscript we will address a one-way or one-factor analysis of variance, which means that we must have an explanatory variable, also known as an independent variable, which must have two or more categories, we must also have a dependent or response variable of the type quantitatively disc

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Richter, Scott J., and Mark E. Payton. "Performing Two-Way Analysis of Variance Under Variance Heterogeneity." Journal of Modern Applied Statistical Methods 2, no. 1 (2003): 152–60. http://dx.doi.org/10.22237/jmasm/1051747980.

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Hudiburg, Richard A. "Using MYSTAT to Analyze Simple Main Effects in Analysis of Variance." Perceptual and Motor Skills 79, no. 1 (1994): 265–66. http://dx.doi.org/10.2466/pms.1994.79.1.265.

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Research designs with two factors having a significant interaction effect are analyzed for simple main effects using MYSTAT. The coding used performs a series of one-way analyses of variance for each main-effect factor at only one level of the second factor.

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Overall, John E., Robert S. Atlas, and Janet M. Gibson. "Tests That are Robust against Variance Heterogeneity in k × 2 Designs with Unequal Cell Frequencies." Psychological Reports 76, no. 3 (1995): 1011–17. http://dx.doi.org/10.2466/pr0.1995.76.3.1011.

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Heterogeneity of variance produces serious bias in conventional analysis of variance tests of significance when cell frequencies are unequal. Welch in 1938 and 1947 proposed an adjusted t test for the difference between two means when cell frequencies and population variances are both unequal. This article describes two ways to use the Welch t to evaluate the significance of the main effect for two treatments across k levels of a concomitant factor in a two-way design. Monte Carlo results document the bias in conventional analysis of variance tests and the stable and appropriately conservative

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Woods-Groves, Suzanne, Ronald C. Eaves, and Thomas O. Williams. "Exploratory Factor Analysis of the Human Behavior Rating Scale: A Rural Population." Psychological Reports 109, no. 3 (2011): 785–802. http://dx.doi.org/10.2466/03.09.10.20.pr0.109.6.785-802.

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The construct validity of Eaves' Human Behavior Rating Scale (HBRS) was investigated. The HBRS is a scale with 91 Likert-type items designed to measure five factors: arousal (persistence and curiosity), affect (externalizing and internalizing), and cognition. Forty-four teachers of Grades 6, 7, and 8 from two low socioeconomic and rural southern counties completed the HBRS for 320 of their students. Three parcels were submitted for analysis for each of the five dimensions. A five-factor, then a two-factor, solution were analyzed using exploratory factor analysis. A principal-axis factor analys

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Kostiukov, Ivan. "DIELECTRIC DISSIPATION FACTOR IN THREE-CORE POWER CABLES." Measuring Equipment and Metrology 82, no. 2 (2021): 50–56. http://dx.doi.org/10.23939/istcmtm2021.02.050.

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This article is devoted to the analysis of components of variance of the results of measurements of dielectric dissipation factor of insulation layers between the conductive elements of the construction of three core power cables with paper impregnated insulation in a common sheath. The analysis of components of variance was carried out by applying presented relations for the direct calculation of the dielectric dissipation factor. The accuracy of presented relations for the calculation of variance components was verified. The results of carried out analysis have shown that the variance of the

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Bruno, C., M. E. Videla, and M. Balzarini. "TEST OF INTERACTION IN THE ANALYSIS OF MOLECULAR VARIANCE." Journal of Basic and Applied Genetics 30, no. 1 (2019): 17–23. http://dx.doi.org/10.35407/bag.2019.xxx.01.03.

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The genomic diversity, expressed in the differences between molecular haplotypes of a group of individuals, can be divided into components of variability between and within some factor of classification of the individuals. For such variance partitioning, molecular analysis of variance (AMOVA) is used, which is constructed from the multivariate distances between pairs of haplotypes. The classical AMOVA allows the evaluation of the statistical significance of two or more hierarchical factors and consequently there is no interaction test between factors. However, there are situations where the fa

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Epstein, Richard S., Carol S. Fullerton, and Robert J. Ursano. "Factor Analysis of the General Health Questionnaire." Psychological Reports 75, no. 2 (1994): 979–83. http://dx.doi.org/10.2466/pr0.1994.75.2.979.

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We present the factor structure of the General Health Questionnaire-60 as derived from a population of 2115 Army soldiers. An eight-factor principal components analysis provided the most clinically relevant solution and explained 58.0% of the variance. We distinguished two types of depressive symptomatology, suggesting the questionnaire may be useful in differentiating shame-ridden dysphoria from anergic disinterest.

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Narantuya, B., and D. Tseveennamjil. "Four factor analysis of variance of fibre diameter." Mongolian Journal of Agricultural Sciences 15, no. 2 (2015): 159–65. http://dx.doi.org/10.5564/mjas.v15i2.565.

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As for the research methodology, we used sample of cashmere of goats, from some soums of Khentii province. We formulated the definition that is expressed by the values of different experiments of 4 factor analysis of variance. When we calculated, we used the formulation of 4 factor analysis of variance. Fibre diameter of goats of Khentii aimag that went under the research fluctuated between 13.70-18.10μm, average was 115.63±0.005μm; female goats' fibre diameter fluctuated between 13.7-18.10 μm and average was 15.66±0.13 μm; while male goats' fibre diameter fluctuated between 13.8-17.40 μm and

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Chen, Binbin, Shih-Feng Huang, and Guangming Pan. "High dimensional mean–variance optimization through factor analysis." Journal of Multivariate Analysis 133 (January 2015): 140–59. http://dx.doi.org/10.1016/j.jmva.2014.09.006.

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Bhandary, Madhusudan. "Test for Generalized Variance in Factor Analysis Model." Communications in Statistics - Simulation and Computation 35, no. 4 (2006): 969–73. http://dx.doi.org/10.1080/03610910600880419.

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Wiernik, Brenton M., Michael P. Wilmot, and Jack W. Kostal. "How Data Analysis Can Dominate Interpretations of Dominant General Factors." Industrial and Organizational Psychology 8, no. 3 (2015): 438–45. http://dx.doi.org/10.1017/iop.2015.60.

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A dominant general factor (DGF) is present when a single factor accounts for the majority of reliable variance across a set of measures (Ree, Carretta, & Teachout, 2015). In the presence of a DGF, dimension scores necessarily reflect a blend of both general and specific factors. For some constructs, specific factors contain little unique reliable variance after controlling for the general factor (Reise, 2012), whereas for others, specific factors contribute a more substantial proportion of variance (e.g., Kinicki, McKee-Ryan, Schriesheim, & Carson, 2002). We agree with Ree et al. that

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Clemens, Elysia V., John C. Carey, and Karen M. Harrington. "The School Counseling Program Implementation Survey: Initial Instrument Development and Exploratory Factor Analysis." Professional School Counseling 14, no. 2 (2010): 2156759X1001400. http://dx.doi.org/10.1177/2156759x1001400201.

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This article details the initial development of the School Counseling Program Implementation Survey and psychometric results including reliability and factor structure. An exploratory factor analysis revealed a three-factor model that accounted for 54% of the variance of the intercorrelation matrix and a two-factor model that accounted for 47% of the variance. Cronbach's alpha reliability estimates for subscales ranged from .79 to .87. Subscales of the instrument may be used to assess ASCA National Model program implementation, programmatic orientation, school counseling services, and school c

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Harrar, Solomon W., and Arne C. Bathke. "Erratum to: A modified two-factor multivariate analysis of variance: asymptotics and small sample approximations." Annals of the Institute of Statistical Mathematics 64, no. 5 (2012): 1087. http://dx.doi.org/10.1007/s10463-012-0364-y.

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24

Egburonu, Onyeike D., and Omotayo A. Abidoye. "Application of Faulkenberry (2018) Bayes Factor to a Balanced Two Way Analysis of Variance with Random Effects." Tanzania Journal of Science 47, no. 5 (2021): 1728–42. http://dx.doi.org/10.4314/tjs.v47i5.20.

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The Analysis of Variance technique estimates variance components by comparing their mean squares to their expected values. Nevertheless, this method could give variance component estimates that are found outside the parameter space, i.e. negative estimates. In a bid to overcome this deficiency, alternate approaches are essential, and likelihood-based approaches have become common over time. Bayesian techniques have also been proposed and Bayes factors developed for examining various models. We applied the Bayes factor proposed by Faulkenberry (2018) to a Balanced Two Way ANOVA under three (3)

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Bakhla, Ajay Kumar, Christoday R. J. Khess, Vijay Verma, Mahesh Hembram, Samir Kumar Praharaj, and Subhas Soren. "Factor Structure of CIWA-Ar in Alcohol Withdrawal." Journal of Addiction 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/745839.

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Objective. To identify the underlying factor structure of alcohol withdrawal syndrome, as measured with CIWA-Ar.Methods. Exploratory factor analysis was conducted on the items of CIWA-Ar. On 201 alcohol-dependent male patients seeking treatment for alcohol withdrawal at 36 hours of abstinence.Results. A three-factor solution was obtained that accounted for 68.74% of total variance. First factor had loading from four items (34.34% variance), second factor also had four items (24.25% variance), and the third had two items (10.04% variance).Conclusions. Factor analysis reveals the existence of mu

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Saltychev, Mikhail, Ryan Mattie, Zachary McCormick, and Katri Laimi. "Confirmatory factor analysis of 12-Item World Health Organization Disability Assessment Schedule in patients with musculoskeletal pain conditions." Clinical Rehabilitation 31, no. 5 (2016): 702–9. http://dx.doi.org/10.1177/0269215516652930.

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Objective: To investigate the factor structure of the 12 item World Health Organization Disability Assessment Schedule (WHODAS) 2.0. Design: Cross-sectional cohort survey study. Setting: Physical and Rehabilitation Medicine outpatient university clinic. Subjects: The 408 consecutive patients with chronic musculoskeletal pain. Main measures: Exploratory and confirmatory factor analysis. Results: A two-factor model most accurately fit the observed data of musculoskeletal pain patients (root mean square error of approximation 0.049, relative Chi square value 1.99). Twelve WHODAS 2.0 items were di

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Wagner, John G. "Inter- and Intrasubject Variation of Digoxin Renal Clearance in Normal Adult Males." Drug Intelligence & Clinical Pharmacy 22, no. 7-8 (1988): 562–67. http://dx.doi.org/10.1177/106002808802200708.

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Three methods of estimating inter- and intrasubject variances and coefficients of variation of digoxin renal clearance are discussed and illustrated. All three methods gave essentially the same values for intrasubject variation; two of the methods (II and III), based on two-factor and one-factor analyses of variance, respectively, gave the same estimates of intersubject variation. The preferred method I involves directly calculating variances from the rows and columns of the tabular data, where the rows are repetitive treatments in the same subject and the mean variance represents intrasubject

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Edwim, Anselmo Ramírez Martínez. "Incubación de huevos de gallina mediante incubadoras caseras." Revista Multidisciplinaria de Investigación (REMI) 2, Ciencias Sociales, Economía, Ingeniería y Arquitectura, etc (2023): 27–32. https://doi.org/10.5281/zenodo.8339284.

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<strong>Objective</strong>: optimize the hatching of chicken eggs through the use of homemade incubators. <strong>Method:</strong> an experimental design of two factors is considered, material from which the incubator will be built and the soaking factor, the previous factors will be applied to 8 fertile eggs in each of the 9 treatments. The materials for the incubators are considered, cardboard, plastic and durapax, each of them will be introduced with an incandescent bulb that will generate the necessary heat for incubation and as for the soaking factor, it will be applied: medium, one and t

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Houston, John, Paul Harris, Sandra McIntire, and Dientje Francis. "Revising the Competitiveness Index Using Factor Analysis." Psychological Reports 90, no. 1 (2002): 31–34. http://dx.doi.org/10.2466/pr0.2002.90.1.31.

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The Competitiveness Index is a 20-item true-false measure designed to assess the desire to win in interpersonal situations. To develop a more psychometrically sound form of the scale, 213 undergraduates were administered the original form and a modified version containing a 5-point Likert-type scale. An initial principal component analysis using a varimax rotation of the modified version yielded a four-factor solution accounting for 54.5% of the explained variance. Based on a subsequent reliability analysis, six items were dropped from the modified scale. A second analysis produced a two-facto

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Choi, Jaesung. "Projection analysis for two-way variance components." Journal of the Korean Data and Information Science Society 25, no. 3 (2014): 547–54. http://dx.doi.org/10.7465/jkdi.2014.25.3.547.

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Emsley, David. "Variance analysis and performance: two empirical studies." Accounting, Organizations and Society 25, no. 1 (2000): 1–12. http://dx.doi.org/10.1016/s0361-3682(99)00019-7.

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Pandis, Nikolaos. "Two-way analysis of variance: Part 1." American Journal of Orthodontics and Dentofacial Orthopedics 148, no. 6 (2015): 1078–79. http://dx.doi.org/10.1016/j.ajodo.2015.09.015.

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Pandis, Nikolaos. "Two-way analysis of variance: Part 2." American Journal of Orthodontics and Dentofacial Orthopedics 149, no. 1 (2016): 137–39. http://dx.doi.org/10.1016/j.ajodo.2015.10.007.

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Jonecis, A. Dayap. "Assessment of seasonal variations in surface water quality of Laguna Lake Stations using factor analysis." Journal of Biodiversity and Environmental Sciences (JBES) 22, no. 2 (2023): 63–73. https://doi.org/10.5281/zenodo.10212358.

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Laguna Lake is one of the lakes that largely contribute to the socio-economic and environmental needs of the Philippines as it supports fisheries and aquaculture, recreation, power generation, and industries. In this study, the two-year (2018-2019) water quality monitoring data from Laguna Lake Development Authority was subjected to multivariate factor analysis. Initially, the dataset was divided into two categories, representing the dry and wet seasons. Factor analysis was then performed in order to identify major contributing factors that significantly influence the water quality of the lake

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Zid, Azlina, Siti Aishah Wahab, Jamatul Shahidah Shaari, Maizan Mohd Nor, Mohammad Adzly Rajli, and Rozita Amiruddin. "FOOTBALL COACHING LEADERSHIP STYLE IN MALAYSIA: AN EXPLORATORY FACTOR ANALYSIS." Malaysian Journal of Sport Science and Recreation 19, no. 2 (2023): 257–68. http://dx.doi.org/10.24191/mjssr.v19i2.24001.

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This study aims at identifying the constructs in the Leadership Scale for Sport (LSS) from the perspective of Malaysian football players. To date, empirical study of factor analysis on coaching leadership style construct in a sports setting is limited. There are 330 professional football players from the Malaysian Super and Premier League who were involved in this study. Leadership Scale for Sport (LSS) by Chelladurai and Saleh (1980) was used, and the exploratory factor analysis was done to obtain information on this current study. The findings showed that from 40 items that measure the five

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Caiyun, Yu, and Maziha Mustapha Siti. "Validity and Reliability Analysis of Student Autonomy, Student Engagement, and English Learning Motivation Scales." International Journal of Social Science and Education Research Studies 05, no. 05 (2025): 445–51. https://doi.org/10.5281/zenodo.15469970.

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Abstract : This pilot study aimed to evaluate the reliability and construct validity of three instruments—Learner Autonomy Scale (LAS), Utrecht Work Engagement Scale for Students (UWES-S), and English Learning Motivation Scale (ELMS)—in the context of higher vocational college EFL students in Shandong Province. A total of 120 valid responses were collected and analyzed using SPSS Statistics 26. Reliability analysis showed high internal consistency for all three instruments, with Cronbach’s alpha values exceeding 0.90. Exploratory Factor Analysis (EFA) was conducted to assess

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Gygi, Jasmin T., Thomas Ledermann, Alexander Grob, Myriam Rudaz, and Priska Hagmann-von Arx. "The Reynolds Intellectual Assessment Scales: Measurement Invariance Across Four Language Groups." Journal of Psychoeducational Assessment 37, no. 5 (2018): 590–602. http://dx.doi.org/10.1177/0734282918780565.

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The Reynolds Intellectual Assessment Scales (RIAS) measures general intelligence and its two main components, verbal and nonverbal intelligence, each comprising of two subtests. The RIAS has been recently standardized in Denmark, Germany, Switzerland, and Spain. Using the standardization samples of the U.S. ( n = 2,438), Danish ( n = 983), German ( n = 2,103), and Spanish ( n = 1,933) versions of the RIAS, this study examined measurement invariance across these four language groups for a single-factor structure, an oblique two-factor structure with a verbal and nonverbal factor, and a bifactor

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Asghar, Amber, Aamir Sanaullah, Muhammad Hanif, and Laila A. Al-Essa. "Enhancing Precision in Population Variance Vector Estimation: A Two-Phase Sampling Approach with Multi-Auxiliary Information." Sains Malaysiana 53, no. 7 (2024): 1693–702. http://dx.doi.org/10.17576/jsm-2024-5307-16.

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To enhance precision in estimating unknown population parameters, an auxiliary variable is often used. However, in scenarios where required information on an auxiliary variable is partially or fully unavailable, two-phase sampling is commonly employed. The challenge of estimating the variance vector using multi-auxiliary variables is a less explored area in current literature. This paper addresses the estimation of vector of unknown population variances for multiple study variables by using an estimated vector of variances derived from multi-auxiliary information. This approach is particularly

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Yakubu, A. "Principal component analysis of the conformation traits of Yankasa sheep." Biotehnologija u stocarstvu 29, no. 1 (2013): 65–74. http://dx.doi.org/10.2298/bah1301065y.

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This study was preformed to evaluate the biometric traits of 227 Yankasa sheep in northern Nigeria under a multivariate approach. The body measurements taken were: withers height, rump height, body length, heart girth, tail length, face length, shoulder width, head width, rump width, ear length, foreleg length, hind leg length and rump length. The animals were divided into two age groups: <15.5 and 15.5 - 28.3 months old, respectively. General linear model was used to study age group effect while principal component factor analysis was performed to define body shape upon the correlation mat

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ÇANGA, Demet, and Ercan EFE. "İki Faktörlü Varyans Analizinde Kontrast Kodlama: Pamuk Verilerine Bir Uygulama." Karadeniz Fen Bilimleri Dergisi 12, no. 1 (2022): 229–45. http://dx.doi.org/10.31466/kfbd.1016490.

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Bu çalışmada, ortalamalar arasındaki belirli farklılıkları araştırmak için belirlenen belirli soruları içeren kontrast tahminlerinden oluşan iki yönlü faktöriyel bir tasarımda kontrast analizinin nasıl yapıldığı ayrıntılı olarak incelenmiştir. Bu amaçla temel etkileri belirlemek için hipotezler belirlendikten sonra her bir hipoteze uygun kontrast katsayıları oluşturulmuş ve kontrast analizi yapılmıştır. Araştırmada KSÜ Ziraat Fakültesi Tarla Bitkileri Bölümü'nde yapılan pamuk denemelerinden elde edilen verilerin bir kısmı izin alınarak kullanılmıştır. Pamuk çeşitleri, yılları ve etkileşim etki

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Abidoye, Adekunle Omotayo. "Application of Minimum Bayes Factor to A Balanced Two-Way ANOVA With Random Effects." Indonesian Journal of Contemporary Multidisciplinary Research 2, no. 3 (2023): 331–48. http://dx.doi.org/10.55927/modern.v2i3.3408.

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It is a common practice in statistical analysis to draw conclusions based on significance. P-values often reflect the probability of incorrectly concluding that a null hypothesized model is true; they do not provide information about other types of error that are also important for interpreting statistical results. Standard model selection criteria and test procedures are often inappropriate for comparing models with different numbers of random effects, due to constraints on the parameter space of the variance components. In this paper, we focused on a minimum Bayes factor proposed by Held and

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Abidoye A. O, Egburonu O. D, Adewara, A.A, and Popoola J. "Application of Minimum Bayes Factor to a Balanced Two-Way Anova with Random Effects." Formosa Journal of Multidisciplinary Research 2, no. 3 (2023): 585–604. http://dx.doi.org/10.55927/fjmr.v2i3.3376.

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It is a common practice in statistical analysis to draw conclusions based on significance. P-values often reflect the probability of incorrectly concluding that a null hypothesized model is true; they do not provide information about other types of error that are also important for interpreting statistical results. Standard model selection criteria and test procedures are often inappropriate for comparing models with different numbers of random effects, due to constraints on the parameter space of the variance components. In this paper, we focused on a minimum Bayes factor proposed by Held and

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Abidoye, Adekunle Omotayo, Adewara A.A, Popoola J, and Egburonu O. D. "Application of Minimum Bayes Factor to a Balanced Two-Way Anova with Random Effects." East Asian Journal of Multidisciplinary Research 2, no. 3 (2023): 1085–104. http://dx.doi.org/10.55927/eajmr.v2i3.3375.

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It is a common practice in statistical analysis to draw conclusions based on significance. P-values often reflect the probability of incorrectly concluding that a null hypothesized model is true; they do not provide information about other types of error that are also important for interpreting statistical results. Standard model selection criteria and test procedures are often inappropriate for comparing models with different numbers of random effects, due to constraints on the parameter space of the variance components. In this paper, we focused on a minimum Bayes factor proposed by Held and

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Uzundzalieva, Katya, Gergana Desheva, Evgenia Valchinova, and Bozhidar Kyosev. "Comparative Evaluation of Einkorn Accessions (Triticum monococcum L.) of Some Main Agricultural Characters." АГРОЗНАЊЕ 17, no. 1 (2017): 69. http://dx.doi.org/10.7251/agren1601069u.

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A set of 15 landraces was estimated by seven agronomical characters. The analysis of variance showed that the most relative variable character during the period of study was the grain yield, followed by the spike length and the thousand kernel weight. The accessions with the shortest stem were B3000126 (90 cm) and B3000128 (95 cm), while B4E0040 and B3000130 had dense and long spikes. The highest thousand kernel weight was observed in B3E0024 (37.66 g), followed by B3000126 (36.60 g). B3000024 and B3000082 possessed high production potential. PC-analysis was applied to arrange accessions by th

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Lowe, Deborah A., Christopher M. Nguyen, Christopher T. Copeland, and John F. Linck. "Factor Analysis of the Texas Functional Living Scale in an Outpatient Clinical Sample." Archives of Clinical Neuropsychology 35, no. 1 (2019): 116–21. http://dx.doi.org/10.1093/arclin/acz005.

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Abstract Objective Prior factor analysis of the Texas Functional Living Scale (TFLS), a performance-based measure of functional abilities, in a military veteran sample supported four factors discrepant from the published subscales. This study analyzed TFLS factor structure in a non-veteran clinical sample. Method Two hundred seventy adult outpatients completed the TFLS during neuropsychological evaluation. Principal axis factor analysis with oblique promax rotation was conducted with age and education effects partialed out. Results Parallel analysis indicated five factors for extraction that a

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Yoon, Sun-Joong, and So Hyun Kang. "Common Factors and Local Factors in Variance Risks: Evidence from S&P500 and KOSPI200 Index Options." Journal of Derivatives and Quantitative Studies 20, no. 2 (2012): 133–64. http://dx.doi.org/10.1108/jdqs-02-2012-b0001.

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This paper conducts a factor analysis using the implied variances of S&P 500 index options and KOSPI 200 index options. After estimating the factors that influence variance risks, we rotate the factors to decompose them into a common factor and local factors. The results show that 10~12 percent of variance risks in both markets is explained by the common factor and 65 percent of S&P 500 implied variances and 70 percent of KOSPI 200 implied variances are explained by each local factor, which is in contrast to the results for bond markets that the most variation of interest rates could b

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Lustosa, Lygia Paccini, Silvia Lanziotti Azevedo da Silva, Taís Almeida Marra, João Marcos Domingues Dias, Leani Souza Máximo Pereira, and Rosangela Correa Dias. "FACTOR ANALYSIS OF THE MINNESOTA LEISURE TIME ACTIVITIES QUESTIONNAIRE - BRAZILIAN PORTUGUESE." Revista Brasileira de Medicina do Esporte 24, no. 3 (2018): 220–24. http://dx.doi.org/10.1590/1517-869220182403156284.

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ABSTRACT Introduction: Accurate measures of physical activity to establish dose-response relationship in health outcomes are still controversial. Scales that estimate caloric expenditure are proposed with a view to categorizing the phenomenon globally. Objective: To carry out a factor analysis of the structure of the Minnesota Leisure Time Activities Questionnaire - Brazilian Portuguese, and propose a new adapted version for the Brazilian elderly community. Methods: Participants were elderly female members of the community, without any distinction in terms of ethnic group and/or social class,

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Hudiburg, Richard A. "Factor Analysis of the Computer Technology Hassles Scale." Psychological Reports 71, no. 3 (1992): 739–44. http://dx.doi.org/10.2466/pr0.1992.71.3.739.

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Factor analysis of the responses from 470 subjects to Hudiburg's 1989 Computer Technology Hassles Scale allowed for the identification of eight factors, defined as Computer Runtime Problems, Computer Information Problems, Everyday Computer Technology, Computers' Impact on Society, Computer as Person, Computer Processing Speed, Computer Costs, and Computerized Correspondence. The first two factors, Computer Runtime Problems and Computer Information Problems, were well defined in terms of variance accounted for and internal consistency. It was suggested that these two factors be used to form a s

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K, S. Bharath Kumar. "Consumer Attitude towards Sustainable products Factor Analysis approach." Journal of Research and Review in Sales and Marketing 1, no. 2 (2024): 35–46. https://doi.org/10.5281/zenodo.13954949.

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<em>The paper delves in understanding the attitude of consumer towards the sustainable products. Present day market mainly focusing on sustainable products where it has high profit margin with higher price of products due to its sourcing and manufacturing process. But people suddenly shifting towards sustainable side is not so easy. Research Understands factors influencing the consumer to buy the sustainable products. Initially all the possible variables were chosen to run factor analysis with 140 responses and then variables were reduced to 4 components and carried out to regression analysis.

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Slinker, B. K., and S. A. Glantz. "Missing data in two-way analysis of variance." American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 258, no. 2 (1990): R291—R297. http://dx.doi.org/10.1152/ajpregu.1990.258.2.r291.

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We previously described a regression approach to analysis of variance computations that permitted analysis of unbalanced designs and experiments with missing data in two-way (or higher) analyses of variance Am. J. Physiol. 255 (Regulatory Integrative Comp. Physiol. 24): R353-R367, 1988. That approach can only be used correctly under a set of narrow, and relatively uninteresting, circumstances. In fact, in the example we worked, we extended that approach beyond its intended scope and incorrectly computed F statistics for testing hypotheses about the main effects of strain of rat and nephron sit

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