Longitudinal Models for Ordinal Data With Many Zeros and Varying Numbers of Response Categories

Citation

McTernan, Melissa & Blozis, Shelley A. (2014). Longitudinal Models for Ordinal Data With Many Zeros and Varying Numbers of Response Categories. Structural Equation Modeling: A Multidisciplinary Journal. vol. 22 (2) pp. 216-226

Abstract

Ordinal response scales are often used to survey behaviors, including data collected in longitudinal studies. Advanced analytic methods are now widely available for longitudinal data. This study evaluates the performance of 4 methods as applied to ordinal measures that differ by the number of response categories and that include many zeros. The methods considered are hierarchical linear models (HLMs), growth mixture mixed models (GMMMs), latent class growth analysis (LCGA), and 2-part latent growth models (2PLGMs). The methods are evaluated by applying each to empirical response data in which the number of response categories is varied. The methods are applied to each outcome variable, first treating the outcome as continuous and then as ordinal, to compare the performance of the methods given both a different number of response categories and treatment of the variables as continuous versus ordinal. We conclude that although the 2PLGM might be preferred, no method might be ideal.

URL

http://dx.doi.org/10.1080/10705511.2014.935915

Reference Type

Journal Article

Journal Title

Structural Equation Modeling: A Multidisciplinary Journal

Author(s)

McTernan, Melissa
Blozis, Shelley A.

Year Published

2014

Volume Number

22

Issue Number

2

Pages

216-226

Edition

Nov 6 2014

ISSN/ISBN

1070-5511

DOI

10.1080/10705511.2014.935915

Reference ID

5303