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Cham, Heining; West, Stephen G.; Ma, Yue; Aiken, Leona S. – Multivariate Behavioral Research, 2012
A Monte Carlo simulation was conducted to investigate the robustness of 4 latent variable interaction modeling approaches (Constrained Product Indicator [CPI], Generalized Appended Product Indicator [GAPI], Unconstrained Product Indicator [UPI], and Latent Moderated Structural Equations [LMS]) under high degrees of nonnormality of the observed…
Descriptors: Monte Carlo Methods, Computation, Robustness (Statistics), Structural Equation Models
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Kelava, Augustin; Nagengast, Benjamin – Multivariate Behavioral Research, 2012
Structural equation models with interaction and quadratic effects have become a standard tool for testing nonlinear hypotheses in the social sciences. Most of the current approaches assume normally distributed latent predictor variables. In this article, we present a Bayesian model for the estimation of latent nonlinear effects when the latent…
Descriptors: Bayesian Statistics, Computation, Structural Equation Models, Predictor Variables
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Thoemmes, Felix J.; West, Stephen G. – Multivariate Behavioral Research, 2011
In this article we propose several modeling choices to extend propensity score analysis to clustered data. We describe different possible model specifications for estimation of the propensity score: single-level model, fixed effects model, and two random effects models. We also consider both conditioning within clusters and conditioning across…
Descriptors: Probability, Scores, Statistical Analysis, Models
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Shrout, Patrick E. – Multivariate Behavioral Research, 2011
Maxwell, Cole, and Mitchell (2011) extended the work of Maxwell and Cole (2007), which raised important questions about whether mediation analyses based on cross-sectional data can shed light on longitudinal mediation process. The latest article considers longitudinal processes that can only be partially explained by an intervening variable, and…
Descriptors: Causal Models, Psychopathology, Peer Mediation, Longitudinal Studies
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Deboeck, Pascal R. – Multivariate Behavioral Research, 2010
The fitting of dynamical systems to psychological data offers the promise of addressing new and innovative questions about how people change over time. One method of fitting dynamical systems is to estimate the derivatives of a time series and then examine the relationships between derivatives using a differential equation model. One common…
Descriptors: Computation, Calculus, Statistical Analysis, Statistical Bias
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Kammeyer-Mueller, John; Steel, Piers D. G.; Rubenstein, Alex – Multivariate Behavioral Research, 2010
Common source bias has been the focus of much attention. To minimize the problem, researchers have sometimes been advised to take measurements of predictors from one observer and measurements of outcomes from another observer or to use separate occasions of measurement. We propose that these efforts to eliminate biases due to common source…
Descriptors: Statistical Bias, Predictor Variables, Measurement, Data Collection
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Reichardt, Charles S. – Multivariate Behavioral Research, 2011
Maxwell, Cole, and Mitchell (2011) demonstrated that simple structural equation models, when used with cross-sectional data, generally produce biased estimates of meditated effects. I extend those results by showing how simple structural equation models can produce biased estimates of meditated effects when used even with longitudinal data. Even…
Descriptors: Structural Equation Models, Statistical Data, Longitudinal Studies, Error of Measurement
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Curran, Patrick J.; Bollen, Kenneth A.; Paxton, Pamela; Kirby, James; Chen, Feinian – Multivariate Behavioral Research, 2002
Examined several hypotheses about the suitability of the noncentral chi square in applied research using Monte Carlo simulation experiments with seven sample sizes and three distinct model types, each with five specifications. Results show that, in general, for models with small to moderate misspecification, the noncentral chi-square is well…
Descriptors: Chi Square, Models, Monte Carlo Methods, Sample Size
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Carvajal, Scott C.; Baumler, Elizabeth; Harrist, Ronald B.; Parcel, Guy S. – Multivariate Behavioral Research, 2001
Describes the use of multilevel models (MLMs) for studies in which individuals are randomized by groups to treatment condition. Uses data from the Safer Choices study, an evaluation of a theory-based multi-component program to prevent sexually transmitted diseases and pregnancy, to illustrate the application of MLMs for both continuous and…
Descriptors: Groups, Intervention, Models, Pregnancy
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Deegan, John, Jr. – Multivariate Behavioral Research, 1976
Focuses on developing a systematic characterization of the error forms resulting from model misspecification in single equation models for least squares regression analyses. (Author/DEP)
Descriptors: Hypothesis Testing, Least Squares Statistics, Mathematical Models, Multiple Regression Analysis
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Strauss, Shiela M.; Rindskopf, David M.; Falkin, Gregory P. – Multivariate Behavioral Research, 2001
Used empirical data about HIV risk behaviors from 330 female participants in a drug treatment program to explore the implications and consequences of using various statistical models to describe the association of one ordinal and one dichotomous variable in which data are incomplete for the dichotomous variable. Examined the statistical fit and…
Descriptors: Acquired Immune Deficiency Syndrome, Females, Goodness of Fit, Mathematical Models
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Buja, Andreas; Eyuboglu, Nermin – Multivariate Behavioral Research, 1992
Use of parallel analysis (PA), a selection rule for the number-of-factors problem, is investigated from the viewpoint of permutation assessment through a Monte Carlo simulation. Results reveal advantages and limitations of PA. Tables of sample eigenvalues are included. (SLD)
Descriptors: Computer Simulation, Correlation, Factor Structure, Mathematical Models
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Graham, John W.; Collins, Nancy L. – Multivariate Behavioral Research, 1991
Common approaches to examining the relationship between multitrait-multimethod (MTMM) data and variables outside the MTMM data are compared: averaging various means of each trait and estimating LISREL computer program models, and estimating only relationships between MTMM traits and the outside variables. Problems of correlational bias are…
Descriptors: Comparative Analysis, Computer Simulation, Correlation, Equations (Mathematics)
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Farley, John U.; Reddy, Srinivas K. – Multivariate Behavioral Research, 1987
In an experiment manipulating artificial data in a factorial design, model misspecification and varying levels of error in measurement and in model structure are shown to have significant effects on LISREL parameter estimates in a modified peer influence model. (Author/LMO)
Descriptors: Analysis of Variance, Computer Simulation, Error of Measurement, Estimation (Mathematics)