A guide to comparing survey sample demographics with national population data using R, covering both classical and Bayesian statistical methods.
A technical introduction to Structural Equation Modeling (SEM) in R, explaining its concepts, graphical models, and applications in research.
Explores methods for choosing optimal weighting parameters (θ) in dual-frame survey sampling to minimize variance in population estimates.
Explains a fourth type of statistical weight for dual-frame surveys, addressing overlap to avoid double-counting in population estimates.
Explains the importance of factors in R for data analysis, covering when and how to convert strings to factors to avoid errors.
A technical guide on using R, brms, and marginaleffects packages to perform conjoint analysis for statistical research.
A data scientist details the complex process of tracing the original source and context of a medical dataset used in statistical software packages.
Analyzing statistical tests for independence in survey contingency tables with zero cells, comparing methods like Rao-Scott and Wald tests in R.
A technical tutorial on implementing quadratic trend tests using the R survey package, including code examples and statistical analysis.
Announces version 3.37 of the R 'survey' package, detailing new features for statistical analysis with complex survey data.
Introducing the 'rimu' R package for manipulating and analyzing multiple-response data, with examples using ethnicity survey data.
A technical guide on handling 'plausible values' in survey data analysis using R, including code for the survey package.
Introducing an R package for complex survey analysis using SQL databases via dplyr/dbplyr, with a focus on hexagonal binning algorithms.
Explores Bayesian vs. Frequentist approaches to the multiple comparisons problem in statistical inference and data analysis.
Explores the complexities and efficiency trade-offs between weighted and unweighted logistic regression in case-control study designs.
