Weighting Large Datasets with Complex Sampling Designs: Choosing the Appropriate Variance Estimation Method

Weighting Large Datasets with Complex Sampling Designs: Choosing the Appropriate Variance Estimation Method

Choosing profile double-sampling designs for survival estimation with application to PEPFAR evaluation

Most studies that follow subjects over time are challenged by having some subjects who dropout. Double-sampling is a design that selects, and devotes resources to intensively pursue and find a subset of these dropouts; then uses data obtained from these to adjust naïve estimates, which are potentially biased by the dropout. Existing methods to estimate survival from double-sampling assume a ran...

Estimation of Variance of Normal Distribution using Ranked Set Sampling

Introduction     In some biological, environmental or ecological studies, there are situations in which obtaining exact measurements of sample units are much harder than ranking them in a set of small size without referring to their precise values. In these situations, ranked set sampling (RSS), proposed by McIntyre (1952), can be regarded as an alternative to the usual simple random sampling ...

Choosing an appropriate method of data collection.

Introduction Conducting real-world research, in particular for the novice researcher, is not easy (Casey 2004). Choices have to be made concerning each stage of the process, all of which are governed by the research question and/or aims of the study. In making these choices researchers resort to textbooks as well as research studies. Both sources are helpful, however, the latter may sometimes b...

Improved Variance Estimation for Fully Synthetic Datasets

Fully synthetic datasets, i.e. datasets that only contain simulated values, arguably provide a very high level of data protection. Since all values are simulated reidentification is almost impossible. This makes the approach especially attractive for the release of very sensitive data such as medical records. However, the established variance estimate for fully synthetic datasets has two major ...