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synced 2024-11-21 19:30:22 +01:00
fix n.by.adj flag function for print_pred
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5728450087
commit
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@ -1,6 +1,6 @@
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Package: daDoctoR
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Package: daDoctoR
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Title: Functions For Health Research
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Title: Functions For Health Research
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Version: 0.21.13
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Version: 0.21.14
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Year: 2021
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Year: 2021
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Author: Andreas Gammelgaard Damsbo <agdamsbo@pm.me>
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Author: Andreas Gammelgaard Damsbo <agdamsbo@pm.me>
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Maintainer: Andreas Gammelgaard Damsbo <agdamsbo@pm.me>
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Maintainer: Andreas Gammelgaard Damsbo <agdamsbo@pm.me>
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@ -88,10 +88,11 @@ print_pred<-function(meas,adj,data,dec=2,n.by.adj=FALSE,p.val=FALSE){
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nq<-c()
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nq<-c()
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nall<-length(!is.na(dat[,1]))
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nall<-length(!is.na(dat[,1]))
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nalt<-c()
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if (n.by.adj==TRUE){
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if (n.by.adj==TRUE){
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dat2<-ma$model
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dat2<-ma$model
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# nalt<-nrow(dat2)
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nalt<-nrow(dat2)
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for (i in 2:ncol(dat2)) {
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for (i in 2:ncol(dat2)) {
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if (is.factor(dat2[, i])) {
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if (is.factor(dat2[, i])) {
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vec <- dat2[, i]
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vec <- dat2[, i]
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@ -120,6 +121,7 @@ print_pred<-function(meas,adj,data,dec=2,n.by.adj=FALSE,p.val=FALSE){
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else {
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else {
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dat2<-dat[!is.na(dat[,1]),]
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dat2<-dat[!is.na(dat[,1]),]
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nalt<-nall
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for (i in 2:ncol(dat2)) {
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for (i in 2:ncol(dat2)) {
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if (is.factor(dat2[, i])) {
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if (is.factor(dat2[, i])) {
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vec <- dat2[, i]
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vec <- dat2[, i]
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@ -184,12 +186,12 @@ print_pred<-function(meas,adj,data,dec=2,n.by.adj=FALSE,p.val=FALSE){
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if (p.val==TRUE){
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if (p.val==TRUE){
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ref<-data.frame(c(NA,rona),re[,"N"],re[,"N.out"],re[,"or_ci"],re[,"pv"],re[,"aor_ci"],re[,"apv"])
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ref<-data.frame(c(NA,rona),re[,"N"],re[,"N.out"],re[,"or_ci"],re[,"pv"],re[,"aor_ci"],re[,"apv"])
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names(ref)<-c("Variable",paste0("N=",nall),paste0("N, ",meas," is ",levels(m)[2]),"Crude OR (95 % CI)","p-value","Mutually adjusted OR (95 % CI)","A p-value")
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names(ref)<-c("Variable",paste0("N=",nalt),paste0("N, ",meas," is ",levels(m)[2]),"Crude OR (95 % CI)","p-value","Mutually adjusted OR (95 % CI)","A p-value")
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}
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}
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else{
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else{
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ref<-data.frame(c(NA,rona),re[,"N"],re[,"N.out"],re[,"or_ci"],re[,"aor_ci"])
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ref<-data.frame(c(NA,rona),re[,"N"],re[,"N.out"],re[,"or_ci"],re[,"aor_ci"])
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names(ref)<-c("Variable",paste0("N=",nall),paste0("N, ",meas," is ",levels(m)[2]),"Crude OR (95 % CI)","Mutually adjusted OR (95 % CI)")
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names(ref)<-c("Variable",paste0("N=",nalt),paste0("N, ",meas," is ",levels(m)[2]),"Crude OR (95 % CI)","Mutually adjusted OR (95 % CI)")
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}
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}
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ls<-list(tbl=ref,miss,nall,nrow(d))
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ls<-list(tbl=ref,miss,nall,nrow(d))
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@ -259,10 +261,11 @@ print_pred<-function(meas,adj,data,dec=2,n.by.adj=FALSE,p.val=FALSE){
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nq<-c()
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nq<-c()
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nall<-length(!is.na(dat[,1]))
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nall<-length(!is.na(dat[,1]))
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nalt<-c()
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if (n.by.adj==TRUE){
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if (n.by.adj==TRUE){
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dat2<-ma$model[,-1]
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dat2<-ma$model[,-1]
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# nalt<-nrow(dat2)
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nalt<-nrow(dat2)
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for (i in 1:ncol(dat2)){
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for (i in 1:ncol(dat2)){
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if (is.factor(dat2[,i])){
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if (is.factor(dat2[,i])){
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vec<-dat2[,i]
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vec<-dat2[,i]
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@ -283,6 +286,7 @@ print_pred<-function(meas,adj,data,dec=2,n.by.adj=FALSE,p.val=FALSE){
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else {
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else {
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dat2<-dat[!is.na(dat[,1]),][,-1]
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dat2<-dat[!is.na(dat[,1]),][,-1]
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nalt<-nall
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for (i in 1:ncol(dat2)) {
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for (i in 1:ncol(dat2)) {
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if (is.factor(dat2[, i])) {
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if (is.factor(dat2[, i])) {
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vec <- dat2[, i]
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vec <- dat2[, i]
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@ -342,12 +346,12 @@ print_pred<-function(meas,adj,data,dec=2,n.by.adj=FALSE,p.val=FALSE){
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if (p.val==TRUE){
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if (p.val==TRUE){
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ref<-data.frame(c(NA,rona),re[,2],re[,5],re[,6],re[,3],re[,4])
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ref<-data.frame(c(NA,rona),re[,2],re[,5],re[,6],re[,3],re[,4])
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names(ref)<-c("Variable",paste0("N=",nall),"Difference (95 % CI)","p-value","Mutually adjusted difference (95 % CI)","A p-value")
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names(ref)<-c("Variable",paste0("N=",nalt),"Difference (95 % CI)","p-value","Mutually adjusted difference (95 % CI)","A p-value")
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}
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}
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else{
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else{
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ref<-data.frame(c(NA,rona),re[,2],re[,5],re[,3])
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ref<-data.frame(c(NA,rona),re[,2],re[,5],re[,3])
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names(ref)<-c("Variable",paste0("N=",nall),"Difference (95 % CI)","Mutually adjusted difference (95 % CI)")
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names(ref)<-c("Variable",paste0("N=",nalt),"Difference (95 % CI)","Mutually adjusted difference (95 % CI)")
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}
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}
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ls<-list(tbl=ref,miss,nall,nrow(d),mean_est)
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ls<-list(tbl=ref,miss,nall,nrow(d),mean_est)
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@ -357,3 +361,4 @@ print_pred<-function(meas,adj,data,dec=2,n.by.adj=FALSE,p.val=FALSE){
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return(ls)
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return(ls)
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}
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}
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