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Xijuan Zhang; Hao Wu – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A full structural equation model (SEM) typically consists of both a measurement model (describing relationships between latent variables and observed scale items) and a structural model (describing relationships among latent variables). However, often researchers are primarily interested in testing hypotheses related to the structural model while…
Descriptors: Structural Equation Models, Goodness of Fit, Robustness (Statistics), Factor Structure
Anders Holm; Anders Hjorth-Trolle; Robert Andersen – Sociological Methods & Research, 2025
Lagged dependent variables (LDVs) are often used as predictors in ordinary least squares (OLS) models in the social sciences. Although several estimators are commonly employed, little is known about their relative merits in the presence of classical measurement error and different longitudinal processes. We assess the performance of four commonly…
Descriptors: Elementary Education, Scores, Error of Measurement, Predictor Variables
Olivera-Aguilar, Margarita; Millsap, Roger E. – Multivariate Behavioral Research, 2013
A common finding in studies of differential prediction across groups is that although regression slopes are the same or similar across groups, group differences exist in regression intercepts. Building on earlier work by Birnbaum (1979), Millsap (1998) presented an invariant factor model that would explain such intercept differences as arising due…
Descriptors: Statistical Analysis, Measurement, Prediction, Regression (Statistics)
Roncancio, Angelica M.; Ward, Kristy K.; Sanchez, Ingrid A.; Cano, Miguel A.; Byrd, Theresa L.; Vernon, Sally W.; Fernandez-Esquer, Maria Eugenia; Fernandez, Maria E. – Health Education & Behavior, 2015
To reduce the high incidence of cervical cancer among Latinas in the United States it is important to understand factors that predict screening behavior. The aim of this study was to test the utility of theory of planned behavior in predicting cervical cancer screening among a group of Latinas. A sample of Latinas (N = 614) completed a baseline…
Descriptors: Cancer, Screening Tests, Incidence, Hispanic Americans
Rhemtulla, Mijke; Brosseau-Liard, Patricia E.; Savalei, Victoria – Psychological Methods, 2012
A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…
Descriptors: Factor Analysis, Computation, Simulation, Sample Size
Carr, Amanda G.; Caskie, Grace I. L. – Journal of College Student Development, 2010
This study examined (a) whether a developmental model or a model in which all subscales' measurement errors are correlated best explains the relationships among White racial identity (WRI) statuses, and (b) social problem-solving (SPS) skills as a predictor of WRI. Path analysis was conducted with a sample of 255 White undergraduate students from…
Descriptors: Undergraduate Students, Error of Measurement, Private Colleges, Racial Identification
Rios-Uribe, Carlos Andres – ProQuest LLC, 2009
Measurements of social constructs that evaluate natural hazard preparedness are important to decrease natural hazard vulnerability. Preparedness reduces natural hazard impacts and human vulnerability. Investment in education and education research contribute to human sustainable development and natural hazard preparedness. Faced with other needs,…
Descriptors: Learning Theories, Structural Equation Models, Validity, Physical Geography
Edirisooriya, Gunapala – 1995
Stepwise regression is not an adequate technique to provide the best set of variables with which to predict the dependent variable. By using the stepwise regression method, one who attempts to select the best set of predictors of a given dependent variable will face more problems than he or she attempted to resolve. This is illustrated with an…
Descriptors: Employees, Error of Measurement, Goodness of Fit, Predictor Variables
Interpreting the Results of Weighted Least-Squares Regression: Caveats for the Statistical Consumer.
Willett, John B.; Singer, Judith D. – 1987
In research, data sets often occur in which the variance of the distribution of the dependent variable at given levels of the predictors is a function of the values of the predictors. In this situation, the use of weighted least-squares (WLS) or techniques is required. Weights suitable for use in a WLS regression analysis must be estimated. A…
Descriptors: Error of Measurement, Estimation (Mathematics), Goodness of Fit, Least Squares Statistics
O'Brien, Francis J., Jr. – 1987
This paper is part of a series of applied statistics monographs intended to provide supplementary reading for applied statistics students. In the present paper, derivations of the unbiased standard error of estimate for both the raw score and standard score linear models are presented. The derivations for raw score linear models are presented in…
Descriptors: Error of Measurement, Estimation (Mathematics), Goodness of Fit, Higher Education
Hendrickson, Leslie; Jones, Barnie – 1982
The logic of using a gain score approach versus longitudinal causal models is studied in this secondary analysis of a complex data base. The gain score model used by the Federal Reserve Bank and the School District of Philadelphia in their "What Works in Reading?" study is successively refined using the LISREL structural equation…
Descriptors: Achievement Gains, Achievement Tests, Data Analysis, Elementary Education
Werts, Charles E.; Linn, Robert L. – 1975
Forming a sequence covering the various aspects of the simplex model, four articles are presented here under the following titles: "A Simplex Model for Analyzing Academic Growth", "Analyzing Ratings With Correlated Intrajudge Measurement Errors", "The Correlation of States With Gain", and "The Reliability of…
Descriptors: Academic Achievement, Achievement Gains, Analysis of Covariance, College Students