A technical discussion comparing two classes of multiparameter tests in survey statistics, focusing on the Rao-Scott tests and intrinsically-weighted tests for regression models.
A technical explanation of the Two-Stage Least Squares (2SLS) method for causal inference in regression, covering its derivation and variance estimation.
Explains the concept of 'symbolically nested' statistical models, their computational advantages, and their importance in survey analysis.
Introducing svyVGAM, a new R package for fitting complex survey regression models using the VGAM framework with design-based inference.
The author discusses a potential bug or design quirk in the 'leaps' R package related to how forward/backward selection interacts with its exhaustive search preprocessing.
A statistical analysis comparing large and small model estimators, focusing on efficiency and misspecification testing in regression contexts.
Explains the statistical concept of 'double robust' estimation, where using two models for outcome and exposure improves reliability.
