Calcutta Statistical Association Bulletin, Volume 75, Issue 1, Page 36-37, May 2023.

Calcutta Statistical Association Bulletin, Volume 75, Issue 1, Page 48-59, May 2023.
Stratified sampling has been commonly used in many large-scale surveys. The two inter-related problems of determining strata boundaries where strata have to be developed using some variable(s) whose values can be accessed while designing the survey and of allocating the total sample size among the strata have been studied during a long period, initially without involving mathematical programming and subsequently using concurrent developments in constrained optimization methods and algorithms. The present article provides a critique of some of these studies, especially those dealing with multiple stratification variables and multiple parameters to be estimated.AMS Subject Classification: 62D05

Calcutta Statistical Association Bulletin, Volume 75, Issue 1, Page 8-27, May 2023.
How to construct the pseudo-weights in voluntary samples is an important practical problem in survey sampling. The problem is quite challenging when the sampling mechanism for the voluntary sample is allowed to be non-ignorable. Under the assumption that the sample participation model is correctly specified, we can compute a consistent estimator of the model parameter and construct the propensity score estimator of the population mean. We propose using the empirical likelihood method to construct the final weights for voluntary samples by incorporating the bias calibration constraints and the benchmarking constraints. Linearization variance estimation of the proposed method is developed. A toy example is also presented to illustrate the idea and the computational details. A limited simulation study is also performed to evaluate the performance of the proposed methods.AMS subject classification: 62D10, 63D05

Calcutta Statistical Association Bulletin, Volume 75, Issue 1, Page 43-47, May 2023.