ASU Electronic Theses and Dissertations
- 1 English
- 1 Masters Thesis
- 1 Public
When analyzing longitudinal data it is essential to account both for the correlation inherent from the repeated measures of the responses as well as the correlation realized on account of the feedback created between the responses at a particular time and the predictors at other times. A generalized method of moments (GMM) for estimating the coefficients in longitudinal data is presented. The appropriate and valid estimating equations associated with the time-dependent covariates are identified, thus providing substantial gains in efficiency over generalized estimating equations (GEE) with the independent working correlation. Identifying the estimating equations for computation is of utmost importance. …
- Yin, Jianqiong, Wilson, Jeffrey Wilson, Reiser, Mark, et al.
- Created Date