DESCRIPTION OF COURSES
AS 664 INFERENTIAL ASPECTS OF SURVEY SAMPLING AND ANALYSIS OF SURVEY DATA (2L+1P) III
This is an advanced course dealing with inferential aspect of survey sampling. It aims at describing some advanced level topics for students who wish to pursue research in inferential sampling and analysis of survey data.
Unified theory of sampling from finite populations. UMV - non-existence theorem and existence theorem under restricted conditions. Concept of sufficiency and likelihood in survey sampling. Admissibility and hyper-admissibility.
Inference under super population models - concept of designs and model unbiasedness, prediction approach. Regression analysis and categorical data analysis with data from complex surveys. Domain estimation. Small area estimation. Calibrated estimators. Model assisted approach in survey sampling.
Estimation of parameters using sampling design based estimation procedures, unified theory of sampling, likelihood function under survey sampling, super population based approach of estimation, domain estimation, small area estimation. Categorical data analysis in the context of sample survey data. Exercises on robust estimation, regression analysis from sample survey data.