Explores methods for choosing optimal weighting parameters (θ) in dual-frame survey sampling to minimize variance in population estimates.
Explains statistical methods for handling overlapping sampling frames in surveys, using a monster analogy for mobile and landline phone samples.
Explains the three main types of statistical weights (precision, frequency, sampling), their uses, and the software documentation challenges they create.
Explores challenges in applying weighted penalized least squares to linear mixed models for survey data, highlighting estimation issues.
Explores the statistical challenges of applying linear mixed models to complex survey data with multi-stage sampling, focusing on weighting issues.
Explores using pairwise composite likelihood to fit mixed models when survey sampling and model random-effect structures differ, using genetic analysis as an example.
