## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) options(rmarkdown.html_vignette.check_title = FALSE) ## ----setup-------------------------------------------------------------------- library(vigicaen) library(rlang) library(dplyr) ## ----interaction_dm----------------------------------------------------------- # ---- Tables ---- #### demo <- demo_ drug <- drug_ # ---- Dictionary step ---- #### d_drecno <- ex_$d_drecno a_llt <- ex_$a_llt # #### Data management #### #### # ---- Drugs ---- #### demo <- demo |> add_drug( d_code = d_drecno, drug_data = drug_ ) # ---- Adrs ---- #### demo <- demo |> add_adr( a_code = a_llt, adr_data = adr_ ) # ---- Sex ---- #### demo <- demo |> mutate( sex = case_when(Gender == "1" ~ 1, Gender == "2" ~ 2, TRUE ~ NA_real_) ) ## ----mod_inter---------------------------------------------------------------- mod3 <- glm(a_colitis ~ ipilimumab + sex, data = demo, family = "binomial") mod_or <- compute_or_mod( summary(mod3)$coefficients, estimate = Estimate, std_er = Std..Error ) |> select(rn, orl, ci, up_ci) mod_or ## ----echo=FALSE--------------------------------------------------------------- ror_ipi <- mod_or[rn == "ipilimumab", orl] ror_sex <- mod_or[rn == "sex", orl] ## ----------------------------------------------------------------------------- demo |> filter(nivolumab == 1) |> compute_dispro( y = "a_colitis", x = "ipilimumab" ) ## ----------------------------------------------------------------------------- mod4 <- glm(a_colitis ~ ipilimumab + sex + ipilimumab * sex, data = demo, family = "binomial") compute_or_mod( summary(mod4)$coefficients, estimate = Estimate, std_er = Std..Error ) ## ----compute_int-------------------------------------------------------------- demo |> compute_interaction( y = "a_colitis", x = "ipilimumab", z = "nivolumab" )