#' A output table for multivariable logistic analysis
#'
#'JB.logreg_o_multi output the table with OR (95\% Confidence Interval),P value
#'@param outx polr output object
#'@return A dataframe of output including Variable names, ORs (95\% Confidence Intervals), P values
#'@examples
#'E2.aGVHD_tmp <- polr(as.factor(aGVHD) ~ mutation + age_ge60 + diseasestat_m2,, data = D, Hess=TRUE)
#'JB.logreg_o_multi(E2.aGVHD_tmp)
#'@export
#'@name JB.logreg_o_multi
#'
#'
JB.logreg_o_multi <- function(outx){
OR <- J.digit(exp(coef(outx)), 2)
CL <- exp(confint(outx))
LCL <- J.digit(CL[ ,1], 2)
UCL <- J.digit(CL[ ,2], 2)
OR95CI <- paste(OR,'(',LCL,',',UCL,')')
ctable <- coef(summary(outx)) ## store table
.P <- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE) * 2 ## calculate and store p values
P <- JS.p(.P[1:length(UCL)])
out <- cbind(OR95CI, P)
colnames(out) <- c('Odds Ratio (95% CI)', 'P')
return(out)
}
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