Nothing
interarm_postprocessres <- function(data_df, fit_res){
m2resloglik <- -2*fit_res$mgls$logLik
s_mgls <- summary(fit_res$mgls)
aic <- s_mgls$AIC
var_res <- fit_res$mgls$sigma^2
sigmas <- stats::coef(fit_res$mgls$modelStruct$varStruct, uncons = FALSE, allCoef = TRUE) * fit_res$mgls$sigma
vars <- t(cbind(sigmas^2))
colnames(vars) <- levels(data_df$stim)
rownames(vars) <- c("Variance")
# model output ----
res_lik <- t(c("AIC" = aic, "-2 Res. logLikelihood" = m2resloglik))
res_2plot <- fit_res$res_tab[grep("Effect of arm", rownames(fit_res$res_tab)), ]
rnames<-rownames(res_2plot)
metainfo_2plot <- do.call(rbind, strsplit(gsub(" reference", "", gsub(" stimulation", "",
sapply(strsplit(rownames(res_2plot), "Effect of arm "), "[", 2))),
" on response in "))
res_2plot <- cbind.data.frame("Arm" = metainfo_2plot[, 1],
"Stimulation" = metainfo_2plot[, 2],
"pvalue" = res_2plot[, "p-value"])
rownames(res_2plot)<-rnames
pval_2plot <- make_nice_pvals(res_2plot, data_df, auxvar = "arm")
return(list(
"vars" = vars,
"pval_2plot" = pval_2plot,
"res_lik" = res_lik,
"res_2plot" = res_2plot,
"pval_2plot" = pval_2plot
))
}
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