Arithmetic Operations

This tutorial introduces MRStdLCRT, an R package for model-robust standardization in 2×2 crossover (CRXO) trials. We focus on two population-level estimands: i-ATE (individual-average treatment effect) and c-ATE (cluster-average treatment effect), and show how to obtain both unadjusted and adjusted estimates using LMM (lmer), GLMM (glmer), and GEE (gee). Uncertainty is quantified via delete-1 cluster jackknife standard errors, including for the difference (i-ATE - c-ATE)

Prova 16-09-25 Ariana da Silva

aula 1609

Atividade avaliativa 2

Atividade 2, realizada em sala no dia 16/09/2025

Atividade Avaliativa 2

PROVA 16/09

ggplot(data = economics, mapping = aes(x= pop,y= psavert , color = uempmed ))+ geom_point()+ theme_light()+ xlab("Population")+ ylab("Save_money") + ggtitle("Negative_linear correlation")