Materi Perkuliahan Pertemuan 2

This analysis revisits the classical barley leaf blotch dataset to assess variance specification in binomial generalized linear models. Evidence from residual diagnostics and dispersion estimates suggests that the standard binomial assumption does not adequately capture the variability in the data. Using a quasi-likelihood framework, the binomial, quasi-binomial, and a quasi-custom variance model are compared. Model evaluation is based on QAIC, dispersion, and deviance statistics. Results indicate that the quasi-custom specification better reflects the empirical heterogeneity present in the dataset, leading to more stable standard errors and more reliable statistical inference for overdispersed proportion data.

This report demonstrates the application of propensity score matching to construct age- and sex-balanced comparison groups between Familial and Sporadic individuals using observational data. A 1:1 nearest-neighbour matching approach without replacement was implemented to reduce baseline differences and improve comparability prior to downstream analyses. The workflow is fully reproducible in R and illustrates best practices for covariate balance assessment using standardized mean differences.