Abstract
Previous research using latent growth curve models has been within the framework of random effects. Using longitudinal data on men’s BMI taken from the National Longitudinal Study of 1979, I show that traditional latent growth curve models estimated in a random-effects framework can be extended to a fixed-effects framework. I also show that latent growth curve models can be estimated when time-constant covariates are modeled on the inter-subject level. Finally, using data taken from the Early Years of Marriage Project, I demonstrate that latent growth curve models can be used for analyzing paired data. Specifically, the latent intercept and slope terms of husbands and wives can be allowed to co-vary.
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© 2014 Springer International Publishing Switzerland
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Teachman, J. (2014). Latent Growth Curve Models with Random and Fixed Effects. In: McHale, S., Amato, P., Booth, A. (eds) Emerging Methods in Family Research. National Symposium on Family Issues, vol 4. Springer, Cham. https://doi.org/10.1007/978-3-319-01562-0_1
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DOI: https://doi.org/10.1007/978-3-319-01562-0_1
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