Literature DB >> 1936099

Structural modeling of mixed longitudinal and cross-sectional data.

J J McArdle1, F Hamagami, M F Elias, M A Robbins.   

Abstract

In this paper we describe some mathematical and statistical models for dealing with changes over age. We concentrate specifically on the use of a structural equation modeling (SEM) approach (using computer programs like LISREL) to deal with issues of: (1) group differences in regression parameters, (2) differences in longitudinal and cross-sectional results, (3) differences due to longitudinal attrition, and (4) mixtures of these problems. To illustrate these ideas we use data from a previous study of hypertension and intellectual abilities (from Schultz, Elias, Robbins, Streeten, and Blakeman, 1986).

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Year:  1991        PMID: 1936099     DOI: 10.1080/03610739108253884

Source DB:  PubMed          Journal:  Exp Aging Res        ISSN: 0361-073X            Impact factor:   1.645


  3 in total

1.  The ABC's of LGM: An Introductory Guide to Latent Variable Growth Curve Modeling.

Authors:  Terry E Duncan; Susan C Duncan
Journal:  Soc Personal Psychol Compass       Date:  2009-12-01

2.  Testing Models for the Contributions of Genes and Environment to Developmental Change in Adolescent Depression.

Authors:  Nathan A Gillespie; Lindon J Eaves; Hermine Maes; Judy L Silberg
Journal:  Behav Genet       Date:  2015-04-18       Impact factor: 2.805

3.  Cohorts based on decade of death: no evidence for secular trends favoring later cohorts in cognitive aging and terminal decline in the AHEAD study.

Authors:  Gizem Hülür; Frank J Infurna; Nilam Ram; Denis Gerstorf
Journal:  Psychol Aging       Date:  2012-10-08
  3 in total

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