Online Program

Modeling Time-Dependent Covariates in Longitudinal Data Analyses

Monday, November 2, 2015 : 10:50 a.m. - 11:10 a.m.

Trent Lalonde, PhD, Department of Applied Statistics and Research Methods, Univeristy of Northern Colorado, Greeley, CO
Often public health data contain variables of interest that change over the course of longitudinal data collection.  In this chapter a discussion is presented of analysis options for longitudinal data with time-dependent covariates.  Relevant definitions are presented and explained in the context of practical applications, such as different types of time-dependent covariates.  The consequences of ignoring the time-dependent nature of variables in models is discussed.  Modeling options for time-dependent covariate data are presented in two general classes: subject-specific models and population-averaged models.  Specific subject-specific models include random-intercept models and random-slopes models.  Decomposition of time-dependent covariates into ``within" and ``between" components within each subject-specific model is discussed.  Specific population-averaged models include the independent GEE model and various forms the GMM (Generalized Method of Moments) approach, including researcher-determined types of time-dependent covariates along with data-driven selection of moment conditions using the Extended Classification.  A practical data example is presented along with example programs for both SAS and R.

Learning Areas:

Biostatistics, economics
Communication and informatics
Public health or related public policy
Public health or related research

Learning Objectives:
Identify different modeling issues with public health data. Explain the modeling options for such data issues. Analyze public health data with missing values and / or longitudinal outcomes.

Keyword(s): Statistics, Biostatistics

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I regularly conduct consulting and research projects relating to longitudinal data analysis, specifically with time-dependent covariates. I have authored a book chapter on this topic.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.