Accession Number : ADA189070
Title : Detecting Serial Correlation in the Error Structure of a Cross-Lagged Panel Model.
Descriptive Note : Technical rept.,
Corporate Author : STANFORD UNIV CA DEPT OF STATISTICS
Personal Author(s) : Mayer, Lawrence S ; Carroll, Steven S
PDF Url : ADA189070
Report Date : 02 Feb 1988
Pagination or Media Count : 25
Abstract : Cross-lagged panel studies are statistical studies in which two or more variable are measured for a large number of subjects at each of several waves or points in time. The variables divide naturally into two sets and the primary purpose of analysis is to estimate and test the strength of the relationship between the sets. This paper contributes to these studies by developing and applying procedures for detecting the presence of serial correlation in the error structure of the regression models used in such studies. The regression approach was extended by incorporating the cross-effects as parameters in a multivariate regression model and develops procedures to estimate and test these parameters. Both the model with independent errors and the model with serially correlated errors were considered. This paper extends the applicability of this results by considering the problem of serially correlated error structure as opposed to the independent error structure.
Descriptors : *REGRESSION ANALYSIS, *TIME SERIES ANALYSIS, ERRORS, ESTIMATES, MATHEMATICAL MODELS, MULTIVARIATE ANALYSIS, STATISTICAL ANALYSIS, STRENGTH(GENERAL)
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE