2017 Theses Doctoral

# Efficient Estimation of the Expectation of a Latent Variable in the Presence of Subject-Specific Ancillaries

Latent variables are often included in a model in order to capture the diversity among subjects in a population. Sometimes the distribution of these latent variables are of principle interest. In studies where sequences of observations are taken from subjects, ancillary variables, such as the number of observations provided by each subject, usually also vary between subjects. The goal here is to understand efficient estimation of the expectation of the latent variable in the presence of these subject-specific ancillaries.

Unbiased estimation and efficient estimation of the expectation of the latent parameter depend on the dependence structure of these three subject-specific components: latent variable, sequence of observations, and ancillary. This dissertation considers estimation under two dependence configurations. In Chapter 3, efficiency is studied under the model in which no assumptions are made about the joint distribution of the latent variable and the subject-specific ancillary. Chapter 4 treats the setting where the ancillary variable and the latent variable are independent.

## Subjects

## Files

- Mittel_columbia_0054D_14284.pdf application/pdf 398 KB Download File

## More About This Work

- Academic Units
- Statistics
- Thesis Advisors
- Rabinowitz, Daniel
- Degree
- Ph.D., Columbia University
- Published Here
- October 20, 2017