Using Bayesian Piecewise Growth Curve Models to Handle Complex Nonlinear Trajectories

Bayesian analysis of longitudinal data using growth curve models

Using a Bayesian latent growth curve model to identify trajectories of positive affect and negative events following myocardial infarction.

Positive and negative affect data are often collected over time in psychiatric care settings, yet no generally accepted means are available to relate these data to useful diagnoses or treatments. Latent class analysis attempts data reduction by classifying subjects into one of K unobserved classes based on observed data. Latent class models have recently been extended to accommodate longitudina...

Examining the Earnings Trajectories of Community College Students Using a Piecewise Growth Curve Modeling Approach A CAPSEE Working Paper

Policymakers have become increasingly concerned with measuring—and holding colleges accountable for—students’ labor market outcomes. In this paper we introduce a piecewise growth curve approach to analyzing community college students’ labor market outcomes, and we discuss how this approach differs from Mincerian and fixed-effects approaches. Our results suggest that three assumptions underpinni...

Bayesian growth curve models with the generalized error distribution

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Bayesian Modeling of Dynamic Software Growth Curve Models

Models for characterizing the reliability of software have traditionally focused on using the observed number of failures or time between observed failures to estimate how defects will be uncovered over time. These models, which are called growth curve (GC) models, are most often used during the latter stages of development, as an aid in determining when the software is ready to be released or ...