Colloquium

Department of Statistics

Statistics Colloquium/PhD Proposal
October 14 (Fri) 11 a.m.
Alavi Commons Room, 6625 Everett Tower

Subgroup Identification and Growth Curve Models for Longitudinal Data
Nichole Andrews
Department of Statistics
Western Michigan University

For this proposal, we will focus on growth curve analysis for longitudinal data. Growth curve analysis can be beneficial in longitudinal biomedical studies, as we can evaluate treatment effect over time. The generalized growth curve model using polynomial regression is proposed for longitudinal data. An optimal degree for the polynomial is obtained using the BIQIF, an adaptation of the Bayesian information criterion. Quadratic inference functions are used to estimate the parameters of the model, which takes into account the fact that repeated measurements from the same subject are more likely to be correlated. The equality of the growth curves is assessed using an asymptotically chi-squared test statistic. The proposed methodology is employed on data from a randomized controlled longitudinal study on depression. The effectiveness of the procedure is also confirmed with simulation studies.
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All statistics students are expected to attend.

Past colloquiums