NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Tong, Xin; Zhang, Zhiyong – Multivariate Behavioral Research, 2012
Growth curve models with different types of distributions of random effects and of intraindividual measurement errors for robust analysis are compared. After demonstrating the influence of distribution specification on parameter estimation, 3 methods for diagnosing the distributions for both random effects and intraindividual measurement errors…
Descriptors: Models, Robustness (Statistics), Statistical Analysis, Error of Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
Lin, Johnny; Bentler, Peter M. – Multivariate Behavioral Research, 2012
Goodness-of-fit testing in factor analysis is based on the assumption that the test statistic is asymptotically chi-square, but this property may not hold in small samples even when the factors and errors are normally distributed in the population. Robust methods such as Browne's (1984) asymptotically distribution-free method and Satorra Bentler's…
Descriptors: Factor Analysis, Statistical Analysis, Scaling, Sample Size
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Barchard, Kimberly A.; Hakstian, A. Ralph – Multivariate Behavioral Research, 1997
Two studies, both using Type 12 sampling, are presented in which the effects of violating the assumption of essential parallelism in setting confidence intervals are studied. Results indicate that as long as data manifest properties of essential parallelism, the two methods studied maintain precise Type I error control. (SLD)
Descriptors: Error of Measurement, Robustness (Statistics), Sampling, Statistical Analysis