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Updated counting and added flag

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agdamsbo 2018-10-12 11:26:20 +02:00
parent 52f60b448b
commit fa76288a0a
3 changed files with 55 additions and 27 deletions
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2
DESCRIPTION
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@ -1,7 +1,7 @@
Package: daDoctoR
Type: Package
Title: FUNCTIONS FOR HEALTH RESEARCH
Version: 0.1.0.9008
Version: 0.1.0.9009
Author@R: c(person("Andreas", "Gammelgaard Damsbo", email = "agdamsbo@pm.me", role = c("cre", "aut")))
Maintainer: Andreas Gammelgaard Damsbo <agdamsbo@pm.me>
Description: I am a Danish medical doctor involved in neuropsychiatric research.

76
R/strobe_pred.R
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@ -5,12 +5,13 @@
#' @param adj variables to adjust for, as string.
#' @param data dataframe of data.
#' @param dec decimals for results, standard is set to 2. Mean and sd is dec-1.
#' @param n.by.adj flag to indicate wether to count number of patients in adjusted model or overall.
#' @keywords logistic
#' @export
#' @examples
#' strobe_pred()
strobe_pred<-function(meas,adj,data,dec=2){
strobe_pred<-function(meas,adj,data,dec=2,n.by.adj=FALSE){
## Ønskeliste:
##
## - Sum af alle, der indgår (Overall N)
@ -58,7 +59,7 @@ strobe_pred<-function(meas,adj,data,dec=2){
dat<-data.frame(m=m,ads)
ma <- glm(m ~ .,family = binomial(), data = dat)
miss<-length(ma$na.action)
actable <- coef(summary(ma))
pa <- actable[,4]
@ -74,32 +75,54 @@ strobe_pred<-function(meas,adj,data,dec=2){
aup<-aci[,2]
aor_ci<-paste0(aco," (",alo," to ",aup,")")
dat2<-dat[,-1]
# names(dat2)<-c(var,names(ads))
nq<-c()
for (i in 1:ncol(dat2)){
if (is.factor(dat2[,i])){
vec<-dat2[,i]
ns<-names(dat2)[i]
for (r in 1:length(levels(vec))){
vr<-levels(vec)[r]
dr<-vec[vec==vr&!is.na(vec)]
n<-as.numeric(length(dr))
nall<-as.numeric(nrow(dat[!is.na(dat2[,c(ns)]),]))
nl<-paste0(ns,levels(vec)[r])
pro<-round(n/nall*100,0)
rt<-paste0(n," (",pro,"%)")
if (n.by.adj==TRUE){
dat2<-ma$model[,-1]
for (i in 1:ncol(dat2)){
if (is.factor(dat2[,i])){
vec<-dat2[,i]
ns<-names(dat2)[i]
for (r in 1:length(levels(vec))){
vr<-levels(vec)[r]
n<-as.numeric(length(vec[vec==vr&!is.na(vec)]))
nall<-as.numeric(length(dat2[,c(ns)]))
nl<-paste0(ns,levels(vec)[r])
pro<-round(n/nall*100,0)
rt<-paste0(n," (",pro,"%)")
nq<-rbind(nq,cbind(nl,rt))
}}
if (!is.factor(dat2[,i])){
num<-dat2[,i]
nl<-names(dat2)[i]
rt<-as.numeric(length(dat2[,c(nl)]))
nq<-rbind(nq,cbind(nl,rt))
}
}
if (!is.factor(dat2[,i])){
num<-dat2[,i]
nl<-names(dat2)[i]
rt<-as.numeric(nrow(dat[!is.na(dat2[,c(nl)]),]))
nq<-rbind(nq,cbind(nl,rt))
}
}
}}}
else {
dat2<-dat[,-1]
for (i in 1:ncol(dat2)){
if (is.factor(dat2[,i])){
vec<-dat2[,i]
ns<-names(dat2)[i]
for (r in 1:length(levels(vec))){
vr<-levels(vec)[r]
n<-as.numeric(length(vec[vec==vr&!is.na(vec)]))
nall<-as.numeric(length(dat[,c(ns)]))
nl<-paste0(ns,levels(vec)[r])
pro<-round(n/nall*100,0)
rt<-paste0(n," (",pro,"%)")
nq<-rbind(nq,cbind(nl,rt))
}}
if (!is.factor(dat2[,i])){
num<-dat2[,i]
nl<-names(dat2)[i]
rt<-as.numeric(length(dat[,c(nl)]))
nq<-rbind(nq,cbind(nl,rt))
}}}
rnames<-c()
@ -132,5 +155,8 @@ strobe_pred<-function(meas,adj,data,dec=2){
names(ref)<-c("Variable","N","Crude OR (95 % CI)","Mutually adjusted OR (95 % CI)")
return(ref)
ls<-list(tbl=ref,miss)
names(ls)<-c("Printable table","Deleted due to missingness")
return(ls)
}

4
man/strobe_pred.Rd
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@ -4,7 +4,7 @@
\alias{strobe_pred}
\title{Logistic regression of predictors according to STROBE}
\usage{
strobe_pred(meas, adj, data, dec = 2)
strobe_pred(meas, adj, data, dec = 2, n.by.adj = FALSE)
}
\arguments{
\item{meas}{binary outcome meassure variable, column name in data.frame as a string. Can be numeric or factor. Result is calculated accordingly.}
@ -14,6 +14,8 @@ strobe_pred(meas, adj, data, dec = 2)
\item{data}{dataframe of data.}
\item{dec}{decimals for results, standard is set to 2. Mean and sd is dec-1.}
\item{n.by.adj}{flag to indicate wether to count number of patients in adjusted model or overall.}
}
\description{
Printable table of logistic regression analysis according to STROBE.