Journal articles: 'Latent values'

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Mezey, Paul G. "Unexpected expectation values for latent molecular properties." Journal of Mathematical Chemistry 50, no. 4 (2011): 843–49. http://dx.doi.org/10.1007/s10910-011-9928-y.

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Thompson, E. A., and C. J. Geyer. "Fuzzy p-values in latent variable problems." Biometrika 94, no. 1 (2007): 49–60. http://dx.doi.org/10.1093/biomet/asm001.

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Kapeli, Sarah Ann. "A latent profile analysis of Pacific health values." Pacific Health Dialog 21, no. 8 (2021): 531–44. http://dx.doi.org/10.26635/phd.2021.148.

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Introduction: Pacific health models that centre Pacific values, can serve as a tool to address Pacific disparities in healthcare. In this study, we broadly draw upon the health concepts of these models to determine how Pacific values are translate across Pacific health and wellbeing. Methods: Using data from the New Zealand Attitudes and Values Study, we identified proxy indicators of common Pacific values. With these proxy indicators we developed a LP Latent Profile Analysis A to uncover subgroups of Pacific peoples based on their orientation towards each proxy indicator and their association with psychological distress. Findings: We identified four subgroups of Pacific peoples: (1) 65% of Pacific peoples identified strongly with Pacific values with low associated psychological distress (2) 18% of Pacific peoples identified moderately with Pacific values with medium associated psychological distress (3) 5% of Pacific peoples identified less with Pacific values with low associated psychological distress (4) 12% of Pacific peoples identified ambivalent with Pacific values with high associated psychological distress. Conclusions: These results suggest that Pacific values and the utility of Pacific health models are an appropriate way of framing health and wellbeing for a vast majority of our Pacific population. However, we also need to recognise the incredible diversity among our Pacific community and be understanding and accommodating of the diverse ways that Pacific peoples can express what they consider valuable.

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Noven, Ragnhild C., Almut E. D. Veraart, and Axel Gandy. "A latent trawl process model for extreme values." Journal of Energy Markets 11, no. 3 (2018): 1–24. http://dx.doi.org/10.21314/jem.2018.179.

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Kim, Soyoung, and Juyeon Song. "Latent transition analysis between the latent profiles of parenting styles and the growth latent classes of adolescents’ task values." Studies on Korean Youth 31, no. 2 (2020): 123–54. http://dx.doi.org/10.14816/sky.2020.31.2.123.

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Tarka, Piotr. "Latent Variable Models – Issues on Measurement and Finding Exact Constructs in Customers’ Values." Przegląd Statystyczny. Statistical Review 2010, no. 4 (2010): 142–67. http://dx.doi.org/10.59139/ps.2010.04.10.

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In article author defines different measurement latent models and describes specify of measurement latent constructs. In literature some examples of these models are: the “true – score” model of classical test theory, the “domain score” model, item response model, factor analysis and latent class models. This work also presents method of estimation that should be undertaken in the identification process of latent constructs. Some aspects related with adjustments in the measurement model depending on distance between respondent and their responses, are also discussed. Author describes them from the prospect of 1) distance between respondent and response on the construct (variable) map; 2) distance between different responses on the construct map and 3) difference between different respondents. Next going on to further description, author considers two types of models based on metrical items characteristics: EFA and CFA. In the exploratory factor analysis as a key latent variable model in constructs detection and their formulation is defined where 4 latent constructs are extracted. These four detected constructs (based on earlier set of 22 value items) were given the following names: “Conservatism”, “Freedom-Independence”, “Hedonistic Consumerism”, and “Life Sensitiveness”. Secondly there is implemented CFA model which reduces number of value items from 22 to 14, containing only two latent constructs called “Conservatism” and “HedonisticConsumerism”. Additionally those constructs were in the end, described with selected AIOD variables where MDS was applied. And at last constructs were defined in context of their utility for marketing activity.

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Schoeller, Anthea, and Michael Franke. "Semantic values as latent parameters: Surprising few & many." Semantics and Linguistic Theory 25 (October 29, 2015): 143. http://dx.doi.org/10.3765/salt.v25i0.3058.

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Based on a concrete proposal for the semantics of vague quantiﬁers few and many suggests unspeciﬁed parameters which are hard to assess by introspection, we argue for the potential value of data-oriented computational modeling. We demonstrate how semantic values can be estimated from experimental data and a probabilistic model of language use.

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Arguea, Nestor M., and Cheng Hsiao. "Market Values of Environmental Amenities: A Latent Variable Approach." Journal of Housing Economics 9, no. 1-2 (2000): 104–26. http://dx.doi.org/10.1006/jhec.2000.0261.

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Cole, Matthew, Bonita Stanton, Linette Deveaux, et al. "LATENT CLASS ANALYSIS OF RISK BEHAVIORS AMONG BAHAMIAN YOUNG ADOLESCENTS: RELATIONSHIP BETWEEN VALUES PRIORITIZATION AND LATENT CLASS." Social Behavior and Personality: an international journal 35, no. 8 (2007): 1061–76. http://dx.doi.org/10.2224/sbp.2007.35.8.1061.

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To explore an association between values and risk behaviors among early adolescents, baseline data from 689 Bahamian youth (median age = 10) were collected from the Portrait Values Questionnaire (Schwartz et al., 2001) and The Bahamian Youth Health Risk Behavioral Inventory. Latent class analysis identified three classes of youth in differing patterns of risk behavior: (7.8%) high levels of drug and delinquency risk behaviors; (2.8%) high levels of sexual risk behavior; (89.4%) low risk takers. Results showed low risk takers included more females, while at least twice as many males comprised the two risk behavior classes. ANOVA found Benevolence, Conformity, Security, Tradition and Universalism values were associated with low risk takers, and logistic regressions for ordered categorical (ordinal) dependent variables showed both values and latent class predicted intentions for future risk behavior. Latent class analysis and values assessment are discussed as tools to guide adolescent riskreduction interventions.

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Gorter, R., J.-P. Fox, G. Ter Riet, MW Heymans, and JWR Twisk. "Latent growth modeling of IRT versus CTT measured longitudinal latent variables." Statistical Methods in Medical Research 29, no. 4 (2019): 962–86. http://dx.doi.org/10.1177/0962280219856375.

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Latent growth models are often used to measure individual trajectories representing change over time. The characteristics of the individual trajectories depend on the variability in the longitudinal outcomes. In many medical and epidemiological studies, the individual health outcomes cannot be observed directly and are indirectly observed through indicators (i.e. items of a questionnaire). An item response theory or a classical test theory measurement model is required, but the choice can influence the latent growth estimates. In this study, under various conditions, this influence is directly assessed by estimating latent growth parameters on a common scale for item response theory and classical test theory using a novel plausible value method in combination with Markov chain Monte Carlo. The latent outcomes are considered missing data and plausible values are generated from the corresponding posterior distribution, separately for item response theory and classical test theory. These plausible values are linearly transformed to a common scale. A Markov chain Monte Carlo method was developed to simultaneously estimate the latent growth and measurement model parameters using this plausible value technique. It is shown that estimated individual trajectories using item response theory, compared to classical test theory to measure outcomes, provide a more detailed description of individual change over time, since item response patterns (item response theory) are more informative about the health measurements than sum scores (classical test theory).

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Murugan, N. Senthil Vel, V. Vallinayagam, and K. Senthamarai Kannan. "Analysis of Liver Cancer DNA Sequence data using Latent values." i-manager’s Journal on Mathematics 1, no. 2 (2012): 34–37. http://dx.doi.org/10.26634/jmat.1.2.1850.

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Han, Jun. "Starting Values for EM Estimation of Latent Class Joint Model." Communications in Statistics - Simulation and Computation 38, no. 7 (2009): 1519–34. http://dx.doi.org/10.1080/03610910903019913.

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Djordjevic, Miodrag, Miroslav Ristic, and Bogdan Pirkovic. "Identifying latent components of the TINAR(1) model." Filomat 35, no. 13 (2021): 4469–82. http://dx.doi.org/10.2298/fil2113469d.

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In this paper we give a solution for the problem of identifying and predicting latent components of the integer-valued time series with skewed Skellam marginal distribution. At the beginning, expressions for latent components identification and prediction are derived. These expressions give us a possibility of revealing the values of two hidden, immeasurable components which affect the integer-valued time series with skewed Skellam marginals. Yule-Walker estimators of the unknown parameters are obtained. Also, quality of identification and lag-one prediction is tested on simulated data. At the very end, the model validation is performed in application on the real-life data.

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MORENO, German, Julio M. SINGER, and Edward J. STANEK III. "BEST LINEAR UNBIASED LATENT VALUES PREDICTORS FOR FINITE POPULATION LINEAR MODELS WITH DIFFERENT ERROR SOURCES." REVISTA BRASILEIRA DE BIOMETRIA 39, no. 4 (2021): 571–86. http://dx.doi.org/10.28951/rbb.v39i4.553.

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We develop best linear unbiased predictors (BLUP) of the latent values of labeled sample units selected from a finite population when there are two distinct sources of measurement error: endogenous, exogenous or both. Usual target parameters are the population mean, the latent values associated to a labeled unit or the latent value of the unit that will appear in a given position in the sample. We show how both types of measurement errors affect the within unit covariance matrices and indicate how the finite population BLUP may be obtained via standard software packages employed to fit mixed models in situations with either heteroskedastic or homoskedastic exogenous and endogenous measurement errors.

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Moors, Guy, Ingrid Vriens, and John Gelissen. "Similarities Between Ranking and Rating Measures of Values Preferences." Methodology 13, no. 3 (2017): 113–22. http://dx.doi.org/10.1027/1614-2241/a000135.

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Abstract. The form-resistant hypothesis states that alternative ways of measuring the same values should be small if method-specific features are taken into account. However, previous research that compared rating and ranking questionnaires for measuring values has shown mixed results. We suggest that adopting a latent class segmentation approach helps to explain these mixed results by identifying segments with similar item preference structures and segments linked to one format only. Our approach is applied to a Dutch survey on work values. In both ranking and rating mode, we find two similar segments reflecting the intrinsic and extrinsic preference structure, while other segments differed between modes. In line with the modified form-resistant hypothesis, the results suggest the same latent preference structure has guided particular segments in a population to respond similarly to rating and ranking questions.

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Lim, Young-Myoung, Ah-Ram Kim, and Ji-Hyuk Park. "Differences in Subjective Health and Comprehensive Behavioral Tendencies Based on Health Lifestyle Values System Types in Middle-Aged and Older Adults." Korean Society of Occupational Therapy 32, no. 1 (2024): 133–44. http://dx.doi.org/10.14519/kjot.2024.32.1.09.

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Objective: To classify latent profiles of the value systems reflected in the healthy lifestyles of middle-aged and older adults using latent profile analysis (LPA) and analyze differences in related influencing factors, subjective health, and comprehensive behavioral tendencies. Methods: Yonsei Lifestyle Profile-Values, Self-Rated Health, and Yonsei Lifestyle Profile-ABCD data were collected from 300 middle-aged and older adults through an online research company. LPA was conducted on the collected lifestyle value system data. Multinomial logistic regression analysis was used to examine factors influencing the classified latent profiles, and one-way ANOVA was conducted to assess differences in the dependent variables between profiles. Results: Three latent profiles based on value system characteristics were identified: ‘Low Health Values System (Profile1),’ ‘High Health Values System (Profile2),’ and ‘Moderate Health Values System (Profile3).’ Educational attainment and age significantly influenced these latent profiles. Additionally, significant differences were observed in subjective health and overall behavioral tendencies among the profiles. Conclusion: Our findings suggest that middle-aged and older adults who prioritize health in their value systems are more likely to adopt healthier behaviors in their daily lives. This highlights the importance of considering value systems when designing intervention strategies and directions aimed at promoting healthy lifestyles from a health management perspective.

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Huang, Jing Yu, Shi Lei Lv, Chen Xi Zhang, and Zhi Wei Wang. "Thermal Properties Analysis of Several N-Alkanes Eutectic Mixtures Applied in Building Envelopes." Advanced Materials Research 512-515 (May 2012): 3007–10. http://dx.doi.org/10.4028/www.scientific.net/amr.512-515.3007.

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This study focuses on the preparation, thermal properties of alkanes eutectic mixtures (n-Octadecane/n-Eicosane, n-Octadecane/n-Docosane and n-Heptadecane /n-Eicosane) as candidate phase change material (PCM) for low temperature latent heat storage systems in building envelopes. Their melting temperature and latent heat were tested by Differential scanning calorimetry (DSC). The testing values were closed to calculation values of accepted theory that ensured the reliability of those datas. The results indicated n-Octadecane/n-Docosane eutectic mixture was more promising PCM for buildings in terms of melting temperature (25.3°C) and latent heat values of melting (158.2J/g).

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Le, Thu, Daniel Bolt, Eric Camburn, Peter Goff, and Karl Rohe. "Latent Factors in Student–Teacher Interaction Factor Analysis." Journal of Educational and Behavioral Statistics 42, no. 2 (2017): 115–44. http://dx.doi.org/10.3102/1076998616676407.

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Classroom interactions between students and teachers form a two-way or dyadic network. Measurements such as days absent, test scores, student ratings, or student grades can indicate the “quality” of the interaction. Together with the underlying bipartite graph, these values create a valued student–teacher dyadic interaction network. To study the broad structure of these values, we propose using interaction factor analysis (IFA), a recently developed statistical technique that can be used to investigate the hidden factors underlying the quality of student–teacher interactions. Our empirical study indicates there are latent teacher (i.e., teaching style) and student (i.e., preference for teaching style) types that influence the quality of interactions. Students and teachers of the same type tend to have more positive interactions, and those of differing types tend to have more negative interactions. IFA has the advantage of traditional factor analysis in that the types are not presupposed; instead, the types are identified by IFA and can be interpreted in post hoc analysis. Whereas traditional factor analysis requires one to observe all interactions, IFA performs well even when only a small fraction of potential interactions are actually observed.

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Stout, Jason E., Yanjue Wu, Christine S. Ho, et al. "Evaluating latent tuberculosis infection diagnostics using latent class analysis." Thorax 73, no. 11 (2018): 1062–70. http://dx.doi.org/10.1136/thoraxjnl-2018-211715.

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BackgroundLack of a gold standard for latent TB infection has precluded direct measurement of test characteristics of the tuberculin skin test and interferon-γ release assays (QuantiFERON Gold In-Tube and T-SPOT.TB).ObjectiveWe estimated test sensitivity/specificity and latent TB infection prevalence in a prospective, US-based cohort of 10 740 participants at high risk for latent infection.MethodsBayesian latent class analysis was used to estimate test sensitivity/specificity and latent TB infection prevalence among subgroups based on age, foreign birth outside the USA and HIV infection.ResultsLatent TB infection prevalence varied from 4.0% among foreign-born, HIV-seronegative persons aged <5 years to 34.0% among foreign-born, HIV-seronegative persons aged ≥5 years. Test sensitivity ranged from 45.8% for the T-SPOT.TB among foreign-born, HIV-seropositive persons aged ≥5 years to 80.7% for the tuberculin skin test among foreign-born, HIV-seronegative persons aged ≥5 years. The skin test was less specific than either interferon-γ release assay, particularly among foreign-born populations (eg, the skin test had 70.0% specificity among foreign-born, HIV-seronegative persons aged ≥5 years vs 98.5% and 99.3% specificity for the QuantiFERON and T-SPOT.TB, respectively). The tuberculin skin test’s positive predictive value ranged from 10.0% among foreign-born children aged <5 years to 69.2% among foreign-born, HIV-seropositive persons aged ≥5 years; the positive predictive values of the QuantiFERON (41.4%) and T-SPOT.TB (77.5%) were also low among US-born, HIV-seropositive persons aged ≥5 years.ConclusionsThese data reinforce guidelines preferring interferon-γ release assays for foreign-born populations and recommending against screening populations at low risk for latent TB infection.Trial registration numberNCT01622140.

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Vecherin, A. V. "Latent Profiles Analysis of Personal Determinants of Overcoming Adversity (Russian and Uzbek Samples)." Bulletin of Kemerovo State University 22, no. 4 (2021): 972–81. http://dx.doi.org/10.21603/2078-8975-2020-22-4-972-981.

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The article introduces an analysis of latent profiles of personal determinants of overcoming adversity. The research included 989 Russian respondents aged 18–78 years and 272 Uzbek respondents aged 18–48. The study involved the following methods: Proactive Coping Questionnaire (PCI), Uncertainty Tolerance Questionnaire (MSTAT–II), Positive and Negative Emotions Questionnaire (PANAS). The statistical analysis of latent profiles (LPA) made it possible to describe the best model, which included five latent profiles. This model demonstrated similar profiles in the Russian and Uzbek samples. Profiles with high proactive, reflexive, preventive coping, and strategic planning values accompanied by low social and emotional support values, had a high level of positive and low values of negative decompensation. Profiles with low proactive, reflexive, preventive coping, and strategic planning values combined with high social and emotional support values were associated with high problem avoidance, low tolerance to uncertainty, and a negative decompensation.

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Vecherin, A. V. "Latent Profiles Analysis of Personal Determinants of Overcoming Adversity (Russian and Uzbek Samples)." Bulletin of Kemerovo State University 22, no. 4 (2021): 972–81. http://dx.doi.org/10.21603/2078-8975-2020-22-4-972-981.

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The article introduces an analysis of latent profiles of personal determinants of overcoming adversity. The research included 989 Russian respondents aged 18–78 years and 272 Uzbek respondents aged 18–48. The study involved the following methods: Proactive Coping Questionnaire (PCI), Uncertainty Tolerance Questionnaire (MSTAT–II), Positive and Negative Emotions Questionnaire (PANAS). The statistical analysis of latent profiles (LPA) made it possible to describe the best model, which included five latent profiles. This model demonstrated similar profiles in the Russian and Uzbek samples. Profiles with high proactive, reflexive, preventive coping, and strategic planning values accompanied by low social and emotional support values, had a high level of positive and low values of negative decompensation. Profiles with low proactive, reflexive, preventive coping, and strategic planning values combined with high social and emotional support values were associated with high problem avoidance, low tolerance to uncertainty, and a negative decompensation.

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Choi, Youseok, and Ji-young Lim. "Differences in Marital Satisfaction and Intention for Subsequent Childbirth by Latent Profile of Family Values among Parents with Young Children in Korea." Behavioral Sciences 14, no. 10 (2024): 868. http://dx.doi.org/10.3390/bs14100868.

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Background: The focus is on family values, marital satisfaction, and the intention for subsequent childbirth. By classifying parents based on family values and examining marital satisfaction and the intention for subsequent childbirth within these groups, the study will provide insights into future childbirth trends and identify factors influencing the intention for subsequent childbirth among different groups. Methods: This study was conducted with parents of children aged 0 to 5 attending six daycare centers in Korea, using a questionnaire to gather responses regarding family values, intention for subsequent childbirth, and marital satisfaction. Descriptive statistics were employed to analyze the characteristics of the key variables, and latent profile analysis was conducted to classify latent groups based on family values. In the verification of differences, the three-step approach was used. Results: First, the latent profile analysis revealed three groups: the ‘neutral values group’ with lower emphasis on gender roles compared to other group, the ‘individualistic values group’ with lower values on marriage and children but higher emphasis on gender roles, and the ‘family-centered values group’ characterized by higher levels of various sub-factors in overall family values. Second, comparing marital satisfaction and intention for subsequent childbirth among latent groups, the FCVG showed significantly higher levels than the TVG and the IVG. Conclusions: In their marriages, couples differed in the values they held regarding parenting, marriage, and children. Therefore, maintaining strong values in marriage and parenting and establishing a family serve as the foundation for realizing new selfhood through parenthood. Simultaneously, forming values within the new roles of being a spouse and a parent is crucial.

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Frate, Flavia, Renata Martins Correa, Katia Astorino Carvalhaes, and Arnoldo De Hoyos Guevara. "PERSONAL VALUES SCALE: BRAZILIAN ENTREPREUNERS’ STARTUPS SAMPLE VALIDATION." Journal on Innovation and Sustainability RISUS 12, no. 1 (2021): 144–51. http://dx.doi.org/10.23925/2179-3565.2021v12i1p144-151.

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This study aims to validate the personal values that push up entrepreneurs to idealize startups in Brazil. The research respondents are incubated at SEBRAE’s centers, a Brazilian support service for micro and small companies, in Alto do Tietê region, São Paulo, Brazil. The empirical quantitative research used the PQV values scale, the Portrait Questionnaire Value, which evaluates individual values based on Schwartz's model of human values. Continuing the studies of this author, this research is made considering ten types of personal values and four areas that present the following indicators: 1. Conservation (conformity, tradition and security); 2. Openness to change (self-direction, stimulation and hedonism); 3. Self-enhancement (achievement and power); 4. Self-transcendence (benevolence and universalism or philanthropy). The scale contains 40 statements and describes people with different aims, interests and aspirations. A multidimensional scale (MDS), with the aid of R software, analyzed the results in order to position the values dimensions. The hypothesis that the predominant latent values are from the openness to change area was confirmed. Thus, the conclusion is that personal values related to openness to change, such as: self-determination, stimulation and hedonism or pleasure, are latent values in the entrepreneurs interviewed. These values are related to freedom, creativity, audacity and pleasure in their projects.

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Lorenzo-Seva, Urbano, and Joost R. Van Ginkel. "Multiple Imputation of missing values in exploratory factor analysis of multidimensional scales: estimating latent trait scores." Anales de Psicología 32, no. 2 (2016): 596. http://dx.doi.org/10.6018/analesps.32.2.215161.

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<p>Researchers frequently have to analyze scales in which some participants have failed to respond to some items. In this paper we focus on the exploratory factor analysis of multidimensional scales (i.e., scales that consist of a number of subscales) where each subscale is made up of a number of Likert-type items, and the aim of the analysis is to estimate participants’ scores on the corresponding latent traits. Our approach uses the following steps: (1) multiple imputation creates several copies of the data, in which the missing values are imputed; (2) each copy of the data is subject to independent factor analysis, and the same number of factors is extracted from all copies; (3) all factor solutions are simultaneously orthogonally (or obliquely) rotated so that they are both (a) factorially simple, and (b) as similar to one another as possible; (4) latent trait scores are estimated for ordinal data in each copy; and (5) participants’ scores on the latent traits are estimated as the average of the estimates of the latent traits obtained in the copies. We applied the approach in a real dataset where missing responses were artificially introduced following a real pattern of non-responses and a simulation study based on artificial datasets. The results show that our approach was able to compute factor score estimates even for participants that have missing data.</p>

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Foxall, Eric. "The SEIS model, or, the contact process with a latent stage." Journal of Applied Probability 53, no. 3 (2016): 783–801. http://dx.doi.org/10.1017/jpr.2016.40.

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AbstractThe susceptible→exposed→infectious→susceptible (SEIS) model is well known in mathematical epidemiology as a model of infection in which there is a latent period between the moment of infection and the onset of infectiousness. The compartment model is well studied, but the corresponding particle system has so far received no attention. For the particle system model in one spatial dimension, we give upper and lower bounds on the critical values, prove convergence of critical values in the limit of small and large latent time, and identify a limiting process to which the SEIS model converges in the limit of large latent time.

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Haerdy, Ratu Sonya Mentari, and Hanson Endra Kusuma. "THE RELATIONSHIP BETWEEN MOSQUE CHARACTERISTICS, ACTIVITIES, AND PERCEPTIONS OF SPIRITUAL VALUES." Journal of Islamic Architecture 7, no. 1 (2022): 19–27. http://dx.doi.org/10.18860/jia.v7i1.13083.

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A mosque is one of the art products formed by the spiritual values of Islamic religion. At this time, mosques are not always related to religious activities. Therefore, Everyone can visit mosques. The mosque is used as a place of worship and social-cultural interaction. This study aims to reveal the relationship between the characteristics of the mosque, the activities, and the user's perception of spiritual values. In this study, respondent data was collected by distributing online questionnaires with the results of 198 respondents. The data is then analyzed by quantitative methods through factor analysis to determine latent variables. Furthermore, a multivariate correlation analysis between latent variables was conducted to find the relationship between variables. The findings revealed the highest and most significant correlation between the characteristics of the mosque and ritual worship activities on the perception of solemnity during worship. Meanwhile, the mosque features also highly correlate with recreational activities, giving rise to the perception of openness to the mosque building.

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Woodley, Ewan J. "Knowing Your Audience: Exploring the Latent Attitudes and Values of Environmental Stakeholders." Environmental Values 28, no. 6 (2019): 633–39. http://dx.doi.org/10.3197/096327119x15678473650956.

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Woldu, Henok G., Sarah Zalwango, Leonardo Martinez, et al. "Defining an intermediate category of tuberculin skin test: A mixture model analysis of two high-risk populations from Kampala, Uganda." PLOS ONE 16, no. 1 (2021): e0245328. http://dx.doi.org/10.1371/journal.pone.0245328.

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One principle of tuberculosis control is to prevent the development of tuberculosis disease by treating individuals with latent tuberculosis infection. The diagnosis of latent infection using the tuberculin skin test is not straightforward because of concerns about immunologic cross reactivity with the Bacille Calmette-Guerin (BCG) vaccine and environmental mycobacteria. To parse the effects of BCG vaccine and environmental mycobacteria on the tuberculin skin test, we estimated the frequency distribution of skin test results in two divisions of Kampala, Uganda, ten years apart. We then used mixture models to estimate parameters for underlying distributions and defined clinically meaningful criteria for latent infection, including an indeterminate category. Using percentiles of two underlying normal distributions, we defined two skin test readings to demarcate three ranges. Values of 10 mm or greater contained 90% of individuals with latent infection; values less than 7.2 mm contained 80% of individuals without infection. Contacts with values between 7.2 and 10 mm fell into an indeterminate zone where it was not possible to assign infection. We conclude that systematic tuberculin skin test surveys within populations at risk, combined with mixture model analysis, may be a reproducible, evidence-based approach to define meaningful criteria for latent tuberculosis infection.

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Roman, Alexander, Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva, and Eyup B. Unlu. "Oracle-Preserving Latent Flows." Symmetry 15, no. 7 (2023): 1352. http://dx.doi.org/10.3390/sym15071352.

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A fundamental task in data science is the discovery, description, and identification of any symmetries present in the data. We developed a deep learning methodology for the simultaneous discovery of multiple non-trivial continuous symmetries across an entire labeled dataset. The symmetry transformations and the corresponding generators are modeled with fully connected neural networks trained with a specially constructed loss function, ensuring the desired symmetry properties. The two new elements in this work are the use of a reduced-dimensionality latent space and the generalization to invariant transformations with respect to high-dimensional oracles. The method is demonstrated with several examples on the MNIST digit dataset, where the oracle is provided by the 10-dimensional vector of logits of a trained classifier. We find classes of symmetries that transform each image from the dataset into new synthetic images while conserving the values of the logits. We illustrate these transformations as lines of equal probability (“flows”) in the reduced latent space. These results show that symmetries in the data can be successfully searched for and identified as interpretable non-trivial transformations in the equivalent latent space.

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Raykov, Tenko, Natalja Menold, and George A. Marcoulides. "Studying Latent Criterion Validity for Complex Structure Measuring Instruments Using Latent Variable Modeling." Educational and Psychological Measurement 78, no. 5 (2017): 905–17. http://dx.doi.org/10.1177/0013164417698017.

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Validity coefficients for multicomponent measuring instruments are known to be affected by measurement error that attenuates them, affects associated standard errors, and influences results of statistical tests with respect to population parameter values. To account for measurement error, a latent variable modeling approach is discussed that allows point and interval estimation of the relationship of an underlying latent factor to a criterion variable in a setting that is more general than the commonly considered homogeneous psychometric test case. The method is particularly helpful in validity studies for scales with a second-order factorial structure, by allowing evaluation of the relationship between the second-order factor and a criterion variable. The procedure is similarly useful in studies of discriminant, convergent, concurrent, and predictive validity of measuring instruments with complex latent structure, and is readily applicable when measuring interrelated traits that share a common variance source. The outlined approach is illustrated using data from an authoritarianism study.

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Valera, Isabel, Francisco J. R. Ruiz, Pablo M. Olmos, Carlos Blanco, and Fernando Perez-Cruz. "Infinite Continuous Feature Model for Psychiatric Comorbidity Analysis." Neural Computation 28, no. 2 (2016): 354–81. http://dx.doi.org/10.1162/neco_a_00805.

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We aim at finding the comorbidity patterns of substance abuse, mood and personality disorders using the diagnoses from the National Epidemiologic Survey on Alcohol and Related Conditions database. To this end, we propose a novel Bayesian nonparametric latent feature model for categorical observations, based on the Indian buffet process, in which the latent variables can take values between 0 and 1. The proposed model has several interesting features for modeling psychiatric disorders. First, the latent features might be off, which allows distinguishing between the subjects who suffer a condition and those who do not. Second, the active latent features take positive values, which allows modeling the extent to which the patient has that condition. We also develop a new Markov chain Monte Carlo inference algorithm for our model that makes use of a nested expectation propagation procedure.

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COLIZZA, V., A. BARRAT, M. BARTHÉLEMY, and A. VESPIGNANI. "EPIDEMIC PREDICTABILITY IN META-POPULATION MODELS WITH HETEROGENEOUS COUPLINGS: THE IMPACT OF DISEASE PARAMETER VALUES." International Journal of Bifurcation and Chaos 17, no. 07 (2007): 2491–500. http://dx.doi.org/10.1142/s0218127407018567.

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We study the predictability of epidemic forecasts in a data-driven meta-population model considering the complete air transportation system and the associated urban areas. We define the predictability as the robustness of the system evolution with respect to the stochastic fluctuations. As a quantitative measure of predictability we consider the information similarity of the time series characterizing different epidemic outbreaks with the same initial conditions. We study the predictability as a function of the parameters describing the basic susceptible-latent-infected and recovered disease dynamics. We find that the overall predictability is determined by the level of sampling of the underlying travel pattern by infected and latent individuals.

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Murawaki, Yugo. "Bayesian Learning of Latent Representations of Language Structures." Computational Linguistics 45, no. 2 (2019): 199–228. http://dx.doi.org/10.1162/coli_a_00346.

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We borrow the concept of representation learning from deep learning research, and we argue that the quest for Greenbergian implicational universals can be reformulated as the learning of good latent representations of languages, or sequences of surface typological features. By projecting languages into latent representations and performing inference in the latent space, we can handle complex dependencies among features in an implicit manner. The most challenging problem in turning the idea into a concrete computational model is the alarmingly large number of missing values in existing typological databases. To address this problem, we keep the number of model parameters relatively small to avoid overfitting, adopt the Bayesian learning framework for its robustness, and exploit phylogenetically and/or spatially related languages as additional clues. Experiments show that the proposed model recovers missing values more accurately than others and that some latent variables exhibit phylogenetic and spatial signals comparable to those of surface features.

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Kock, Ned. "Hypothesis Testing with Confidence Intervals and P Values in PLS-SEM." International Journal of e-Collaboration 12, no. 3 (2016): 1–6. http://dx.doi.org/10.4018/ijec.2016070101.

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E-collaboration researchers usually employ P values for hypothesis testing, a common practice in a variety of other fields. This is also customary in many methodological contexts, such as analyses of path models with or without latent variables, as well as simpler tests that can be seen as special cases of these (e.g., comparisons of means). The author discusses here how a researcher can use another major approach for hypothesis testing, the one building on confidence intervals, in analyses of path models with latent variables employing partial least squares structural equation modeling (PLS-SEM). The author contrasts this approach with the one employing P values through the analysis of a simulated dataset, created based on a model grounded on past theory and empirical research. The model refers to social networking site use at work and its impact on job performance. The results of the analyses suggest that tests employing confidence intervals and P values are likely to lead to very similar outcomes in terms of acceptance or rejection of hypotheses.

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Oberski, Daniel L., Jeroen K. Vermunt, and Guy B. D. Moors. "Evaluating Measurement Invariance in Categorical Data Latent Variable Models with the EPC-Interest." Political Analysis 23, no. 4 (2015): 550–63. http://dx.doi.org/10.1093/pan/mpv020.

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Many variables crucial to the social sciences are not directly observed but instead are latent and measured indirectly. When an external variable of interest affects this measurement, estimates of its relationship with the latent variable will then be biased. Such violations of “measurement invariance” may, for example, confound true differences across countries in postmaterialism with measurement differences. To deal with this problem, researchers commonly aim at “partial measurement invariance” that is, to account for those differences that may be present and important. To evaluate this importance directly through sensitivity analysis, the “EPC-interest” was recently introduced for continuous data. However, latent variable models in the social sciences often use categorical data. The current paper therefore extends the EPC-interest to latent variable models for categorical data and demonstrates its use in example analyses of U.S. Senate votes as well as respondent rankings of postmaterialism values in the World Values Study.

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RAJEEVAN, M., and K. C. SINHA RAY. "Inter-seasonal and inter-annual variations of mean and eddy atmospheric energetics over India." MAUSAM 47, no. 1 (2021): 41–46. http://dx.doi.org/10.54302/mausam.v47i1.3680.

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Using daily upper air data from 1000 to 250 hPa of 20 stations during the period 1983-87 , the inter-sasonal and inter-annual variations of vertically intearated mean and eddy sensible and latent heat fluxes over India were examined. Vertically intearated meridional, sensible and latent fluxes (both mean and eddy fluxes) were generally southwards over the country except over northeastern parts. Large seasonal variation of mean sensible heat and latent heat flux values occur in association with the seasonal shifts of Hadley circulation. Maximum sensible heat fluxes were observed during pre-monsoon season over northern parts of India. Maximum latent heat fluxes were observed over central parts of India during monsoon season. Eddy fluxes were two order smaller than fluxes due to mean flow during all seasons. Maximum eddy fluxes occur in winter and are accomplished by large scale transient eddies. The eddy fluxes were practically negligible equatorwards of 15°N. Seasonal variations of fluxes over low latitudes were, however, different from the zonal pattern of annual cycle obtained by Oort (1971).  There were significant differences in meridional mean and eddy flux values between 1983 (a good monsoon year) and 1987 (a bad monsoon year). During 1983 (1987) the sensible heat flux values due to transient eddies were equatorwards (polewards) during the premonsoon as well as monsoon seasons. Similarly during monsoon season of 1983 larger northward mean sensible and latent heat fluxes were observed. In addition there were significant differences in vertical structure of zonal sensible and latent heat fluxes between 1983 and 1987 also.

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Robitzsch, Alexander. "About the Equivalence of the Latent D-Scoring Model and the Two-Parameter Logistic Item Response Model." Mathematics 9, no. 13 (2021): 1465. http://dx.doi.org/10.3390/math9131465.

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This article shows that the recently proposed latent D-scoring model of Dimitrov is statistically equivalent to the two-parameter logistic item response model. An analytical derivation and a numerical illustration are employed for demonstrating this finding. Hence, estimation techniques for the two-parameter logistic model can be used for estimating the latent D-scoring model. In an empirical example using PISA data, differences of country ranks are investigated when using different metrics for the latent trait. In the example, the choice of the latent trait metric matters for the ranking of countries. Finally, it is argued that an item response model with bounded latent trait values like the latent D-scoring model might have advantages for reporting results in terms of interpretation.

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Ahmed, Taufique, and Luca Longo. "Interpreting Disentangled Representations of Person-Specific Convolutional Variational Autoencoders of Spatially Preserving EEG Topographic Maps via Clustering and Visual Plausibility." Information 14, no. 9 (2023): 489. http://dx.doi.org/10.3390/info14090489.

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Dimensionality reduction and producing simple representations of electroencephalography (EEG) signals are challenging problems. Variational autoencoders (VAEs) have been employed for EEG data creation, augmentation, and automatic feature extraction. In most of the studies, VAE latent space interpretation is used to detect only the out-of-order distribution latent variable for anomaly detection. However, the interpretation and visualisation of all latent space components disclose information about how the model arrives at its conclusion. The main contribution of this study is interpreting the disentangled representation of VAE by activating only one latent component at a time, whereas the values for the remaining components are set to zero because it is the mean of the distribution. The results show that CNN-VAE works well, as indicated by matrices such as SSIM, MSE, MAE, and MAPE, along with SNR and correlation coefficient values throughout the architecture’s input and output. Furthermore, visual plausibility and clustering demonstrate that each component contributes differently to capturing the generative factors in topographic maps. Our proposed pipeline adds to the body of knowledge by delivering a CNN-VAE-based latent space interpretation model. This helps us learn the model’s decision and the importance of each component of latent space responsible for activating parts of the brain.

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Mislevy, Robert J., and Kathleen M. Sheehan. "Information Matrices in Latent-Variable Models." Journal of Educational Statistics 14, no. 4 (1989): 335–50. http://dx.doi.org/10.3102/10769986014004335.

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The Fisher, or expected, information matrix for the parameters in a latent-variable model is bounded from above by the information that would be obtained if the values of the latent variables could also be observed. The difference between this upper bound and the information in the observed data is the “missing information.” This paper explicates the structure of the expected information matrix and related information matrices, and characterizes the degree to which missing information can be recovered by exploiting collateral variables for respondents. The results are illustrated in the context of item response theory models, and practical implications are discussed.

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Lee, Soyoung, Jiyoung Lim, and Jina Ryoo. "The impact of unmarried people’s values and perceptions on marriage and fertility intentions: Focusing on latent classes of gender role attitudes and subjective economic uncertainty." Center for Social Welfare Research Yonsei University 82 (September 30, 2024): 43–79. http://dx.doi.org/10.17997/swry.82.1.2.

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South Korea's long-standing low fertility rate has been widely acknowledged as a significant issue. The purpose of this study is to conduct a more refined analysis of values and perceptions, which have been recently pointed out as causes of low fertility, by identifying the latent types of gender role values among unmarried individuals and exploring the relationship between these gender role value latent groups and perceived uncertainties in relation to intentions to marry and have children. We conducted a latent class analysis and logistic regression on data from 5,003 unmarried people from the 2021 National Family and Fertility Survey. The latent class analysis categorized unmarried individuals into three groups based on their gender role attitudes: egalitarian value group (71.8%), traditional value group (19.8%), and transitional value group (8.4%). Using the egalitarian value group as the reference group, a multinomial logistic regression is conducted to examine the factors influencing the classification of the remaining two groups. The results indicate that gender, age, educational level, employment type, and equivalized total income were significant. Logistic regression analysis showed that the egalitarian value group had lower intentions to marry and have children compared to the traditional value group. Additionally, individuals with more positive future prospects, i.e., lower uncertainty about the future, had higher marriage and fertility intentions. Based on these findings, the study suggests promoting a culture of gender equality in both public and private spheres and increasing housing and income stability to reduce uncertainty.

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Lin, K. M., J. Y. Juang, Y. W. Shiu, and L. F. W. Chang. "Estimating the Bowen Ratio for Application in Air Quality Models by Integrating a Simplified Analytical Expression with Measurement Data." Journal of Applied Meteorology and Climatology 55, no. 4 (2016): 1041–48. http://dx.doi.org/10.1175/jamc-d-15-0080.1.

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AbstractIn air quality models, daytime sensible and latent heat fluxes are important factors that influence atmospheric stability. These heat fluxes originate from heat that is generated from solar radiation and is then released from the earth’s surface. Different climates and surface conditions may lead to varying heat flux distributions. Because latent heat flux is influenced by both solar radiation and plant evapotranspiration, it is often difficult to estimate. The objective of this study was to apply thermodynamic concepts to determine an equation that could be used to estimate the Bowen ratio in the absence of latent and sensible heat fluxes. This study showed that, using two meteorological parameters (i.e., absolute temperature and relative humidity), the Bowen ratio for the climate in Taiwan could be obtained and then used to estimate sensible and latent heat fluxes in a series of equations. Furthermore, the approach’s applicability was determined by testing the sensitivities of parameters used in the Bowen ratio equation. A comparison of results determined through the Priestly–Taylor and Penman–Monteith methods with meteorological data for Yilan and Chiayi counties, Taiwan, for the 2006 summer and winter is performed. The results of this study showed that, among the simulated latent heat fluxes in the two study areas, the values estimated using the Penman–Monteith method were the largest, followed by those estimated using the Priestly–Taylor method. Values estimated using the Bowen ratio method were the smallest. Predictions generated by the proposed Bowen ratio equation correlated with those generated by the other models; however, the values estimated with the Priestly–Taylor method were closest to the simulated values.

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Adams, Shahieda, Rodney Ehrlich, Roslynn Baatjies, Nandini Dendukuri, Zhuoyu Wang, and Keertan Dheda. "Evaluating Latent Tuberculosis Infection Test Performance Using Latent Class Analysis in a TB and HIV Endemic Setting." International Journal of Environmental Research and Public Health 16, no. 16 (2019): 2912. http://dx.doi.org/10.3390/ijerph16162912.

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Background: Given the lack of a gold standard for latent tuberculosis infection (LTBI) and paucity of performance data from endemic settings, we compared test performance of the tuberculin skin test (TST) and two interferon-gamma-release assays (IGRAs) among health-care workers (HCWs) using latent class analysis. The study was conducted in Cape Town, South Africa, a tuberculosis and human immunodeficiency virus (HIV) endemic setting Methods: 505 HCWs were screened for LTBI using TST, QuantiFERON-gold-in-tube (QFT-GIT) and T-SPOT.TB. A latent class model utilizing prior information on test characteristics was used to estimate test performance. Results: LTBI prevalence (95% credible interval) was 81% (71–88%). TST (10 mm cut-point) had highest sensitivity (93% (90–96%)) but lowest specificity (57%, (43–71%)). QFT-GIT sensitivity was 80% (74–91%) and specificity 96% (94–98%), and for TSPOT.TB, 74% (67–84%) and 96% (89–99%) respectively. Positive predictive values were high for IGRAs (90%) and TST (99%). All tests displayed low negative predictive values (range 47–66%). A composite rule using both TST and QFT-GIT greatly improved negative predictive value to 90% (range 80–97%). Conclusion: In an endemic setting a positive TST or IGRA was highly predictive of LTBI, while a combination of TST and IGRA had high rule-out value. These data inform the utility of LTBI-related immunodiagnostic tests in TB and HIV endemic settings.

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Johnson, Branden B., and Nathan F. Dieckmann. "Lay Americans’ views of why scientists disagree with each other." Public Understanding of Science 27, no. 7 (2017): 824–35. http://dx.doi.org/10.1177/0963662517738408.

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A survey experiment assessed response to five explanations of scientific disputes: problem complexity, self-interest, values, competence, and process choices (e.g. theories and methods). A US lay sample ( n = 453) did not distinguish interests from values, nor competence from process, as explanations of disputes. Process/competence was rated most likely and interests/values least; all, on average, were deemed likely to explain scientific disputes. Latent class analysis revealed distinct subgroups varying in their explanation preferences, with a more complex latent class structure for participants who had heard of scientific disputes in the past. Scientific positivism and judgments of science’s credibility were the strongest predictors of latent class membership, controlling for scientific reasoning, political ideology, confidence in choice, scenario, education, gender, age, and ethnicity. The lack of distinction observed overall between different explanations, as well as within classes, raises challenges for further research on explanations of scientific disputes people find credible and why.

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Na, Tae-Kyun, and Saem Han. "Classifying Job Value Profiles and Employment Outcomes Among Culinary Arts Graduates." Societies 15, no. 3 (2025): 66. https://doi.org/10.3390/soc15030066.

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The job values of college graduates are rapidly changing, but a mismatch between industry expectations and young chefs’ values has emerged. To capture the heterogeneity in job values that traditional variable-centered approaches may overlook, this study employed Latent Profile Analysis, a person-centered method, to classify the job value profiles of culinary arts graduates and examine their impact on major–job match and subjective well-being. A total of 386 culinary arts graduates, extracted from the Graduates Occupational Mobility Survey, were classified into six latent profiles. First, the most prevalent profile (Profile 4) emphasized environmental and developmental values, and was associated with a higher proportion of women and a greater likelihood of unemployment. Second, graduates who valued job attributes across all dimensions (Profile 1) were more likely to secure employment in or outside their field than those in Profiles 2, 3, and 5 were. Third, negative emotions increased the likelihood of belonging to Profiles 2, 3, and 5 compared to Profile 1. Finally, higher life satisfaction reduced the probability of belonging to Profiles 4, 5, or 6 compared to Profile 1. These findings emphasize the importance of aligning HR policies with graduates’ job values. Such alignment can enhance employment within graduates’ academic disciplines and improve their subjective well-being.

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Lewbel, Arthur. "Semiparametric Estimation of Location and Other Discrete Choice Moments." Econometric Theory 13, no. 1 (1997): 32–51. http://dx.doi.org/10.1017/s0266466600005636.

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Latent variable discrete choice model estimation and interpretation depend on the density function of the latent variable's unobserved random component. This paper provides a simple semiparametric estimator of the moments of this density. The results can be used as starting values for parametric estimators, to estimate the appropriate location and scaling for semiparametric estimators, for specification testing including tests of latent error skewness and kurtosis, and to estimate coefficients of discrete explanatory variables in the model.

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Kopecky, Robin, Lenka Příplatová, Silvia Boschetti, Konrad Talmont-Kaminski, and Jaroslav Flegr. "Le Petit Machiavellian Prince: Effects of Latent Toxoplasmosis on Political Beliefs and Values." Evolutionary Psychology 20, no. 3 (2022): 147470492211126. http://dx.doi.org/10.1177/14747049221112657.

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Humans infected by Toxoplasma gondii express no specific symptoms but manifest higher incidence of many diseases, disorders and differences in personality and behavior. The aim of this study was to compare the political beliefs and values of Toxoplasma-infected and Toxoplasma-free participants. We measured beliefs and values of 2315 responders via an online survey (477 Toxoplasma-infected) using the Political Beliefs and Values Inventory (PI34). This study showed Toxoplasma-infected and Toxoplasma-free participants of our cross-sectional study differed in three of four factors of PI34, scoring higher in Tribalism and lower in Cultural liberalism and Anti-Authoritarianism. We found sex differences in political beliefs associated with Toxoplasma infection. Infected women scored higher in tribalism and lower in cultural liberalism, compared with the Toxoplasma-free control group, while infected men scored higher in economic equity. These results fit with sexual differences in behavior and attitude observed after toxoplasmosis infection. Controlling for the effect of worse physical health and mental health had little impact, suggesting that impaired health did not cause these changes. Rather than adaptation to prevalence of parasites, as suggested by parasite-stress theory, the differences might be side-effects of long-term mild inflammatory reaction. However, to get clear picture of the mild inflammation effects, more research focused on different infectious diseases is needed.

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Lin, Zhengning. "Assessing the impact of extreme values in clinical studies−a latent variable approach." Biometrics & Biostatistics International Journal 8, no. 3 (2019): 85–91. http://dx.doi.org/10.15406/bbij.2019.08.00276.

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Schmidt, Mikkel N., Daniel Seddig, Eldad Davidov, et al. "Latent profile analysis of human values: What is the optimal number of clusters?" Methodology 17, no. 2 (2021): 127–48. http://dx.doi.org/10.5964/meth.5479.

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Latent Profile Analysis (LPA) is a method to extract homogeneous clusters characterized by a common response profile. Previous works employing LPA to human value segmentation tend to select a small number of moderately homogeneous clusters based on model selection criteria such as Akaike information criterion, Bayesian information criterion and Entropy. The question is whether a small number of clusters is all that can be gleaned from the data. While some studies have carefully compared different statistical model selection criteria, there is currently no established criteria to assess if an increased number of clusters generates meaningful theoretical insights. This article examines the content and meaningfulness of the clusters extracted using two algorithms: Variational Bayesian LPA and Maximum Likelihood LPA. For both methods, our results point towards eight as the optimal number of clusters for characterizing distinctive Schwartz value typologies that generate meaningful insights and predict several external variables.

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Buch, Alfred. "New Method for Verifying Latent Heat of Fusion Handbook Values for Pure Metals." Materials Testing 49, no. 11-12 (2007): 600–602. http://dx.doi.org/10.3139/120.100849.

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WALLMO, KRISTY, and STEVE EDWARDS. "Estimating Non-market Values of Marine Protected Areas: A Latent Class Modeling Approach." Marine Resource Economics 23, no. 3 (2008): 301–23. http://dx.doi.org/10.1086/mre.23.3.42629620.

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Journal articles on the topic 'Latent values'

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