In surveys requiring cost efficiency, such as medical research, measuring the variable of interest (e.g., disease status) is expensive and/or time-consuming; however, we often have access to easily obtainable characteristics about sampling units. These are not typically employed in data collection process. Judgment post-stratification (JPS) enables us supplement random samples from population w...

OBJECTIVE To assess the validity of the estimates obtained through telephone survey and to measure the impact of the post-stratification weighting factor to adjust estimates. METHODS The same questionnaire was completed by two independent samples of the population living in the municipality of Belo Horizonte city (Barreiro and West regions). One sample (n=440) completed the questionnaire of V...

Traditional methods for sampling weight adjustment involve weighting class adjustment for nonresponse bias reduction, followed by post-stratification (raking-ratio or regression) adjustment for coverage bias reduction, and then trimming (or winsorization) of extreme weights for variance reduction followed by final post-stratification to meet desired control totals and for further variance reduc...

Principal stratification has recently become a popular tool to address certain causal inference questions, particularly in dealing with post-randomization factors in randomized trials. Here, we analyze the conceptual basis for this framework and invite response to clarify the value of principal stratification in estimating causal effects of interest.

Abstract In this study, the difficulty of estimating population mean in situation post-stratification is discussed. The case presented for ratio-type exponential estimators finite mean. Mean-squared error proposed estimator obtained up to first degree approximation. instance post-stratification, was compared with existing estimators. An empirical study by using some real data and further, simul...