#' Generate Odds Ratios CI Pval table from GLM
#'
#' @param fit model fit by brm function
#' @return Tibble with 5 columns: Name (char), OR, 2.5%, 97.%, p-val (doubles)
#' @examples
#' x = runif(100,0,10)
#' y = sample(c(0,1), size = 100, replace = T)
#' z = runif(100,0,10)
#' df = tibble(
#' x = x,
#' y = y,
#' z = z
#' )
#' glmfit = glm(y ~ x + z, data = df, family = bernoulli(link = "logit"))
#' glm_ORs(glmfit)
glm_ORs = function(fit){
CI = suppressMessages(confint(fit))[-1,]
summ = coef(summary(fit))[-1,c(1,4)]
if(nrow(coef(summary(fit)))==2){
Tib = tibble(
Name = rownames(coef(summary(fit)))[-1],
OR = exp(summ[1]),
Lower = exp(CI[1]),
Upper = exp(CI[2]),
p = summ[2]
)
Tib
}else{
Tib = tibble(
Name = rownames(summ),
OR = exp(summ[,1]),
Lower = exp(CI[,1]),
Upper = exp(CI[,2]),
p = summ[,2]
)
Tib
}
}
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