A Unifying Framework for the Analysis of Continuous and Discontinuous Change

This thesis develops a new modeling framework, called generalized latent change modeling, as a unifying approach to investigate diverse patterns of change from a stage-sequential perspective. Whereas stage theories were originally proposed to describe discontinuous characteristics of human development, it is shown that stage-sequential change is not necessarily incompatible with continuous change. The family of generalized latent change models (GLCMs) integrates a number of well-known quantitative methods into a unified framework and offers a variety of new options. The new methodology accommodates both continuous and discontinuous change processes and can take into account a wide range of data types including continuous, binary, ordinal, categorical, frequency, ranking, and proportion data, as well as mixtures of response variables. As a result, this modeling approach offers a versatile and practical way of analyzing longitudinal data. Several empirical data analyses demonstrate that GLCMs yield easily interpretable results and provide important statistical tests for various hypotheses and competing theories about the behavioral change mechanism. The applications given include studies of attitude change toward substance use among adolescents and value change regarding the concept of a good citizen in the United States from the 1960s to the 1980s.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Psychology

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Kim, Jee-Seon

Contributors dc:contributor

• Bockenholt, Ulf
• Hubert, Lawrence J.

• Biology, Biostatistics

Language dc:language

eng

Identifier

(MiAaPQ)AAI3023092

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/82007