andreas/daDoctoR
1
0
Fork 0
mirror of https://github.com/agdamsbo/daDoctoR.git synced 2024-11-24 12:41:54 +01:00
Code Issues Projects Releases Wiki Activity

u

Browse Source
This commit is contained in:
agdamsbo 2019-11-13 10:05:53 +01:00
parent 3573b74a1b
commit dc2d8985c1
3 changed files with 16 additions and 9 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
DESCRIPTION
View File

@ -1,7 +1,7 @@
Package: daDoctoR Package: daDoctoR
Type: Package Type: Package
Title: FUNCTIONS FOR HEALTH RESEARCH Title: FUNCTIONS FOR HEALTH RESEARCH
Version: 0.1.0.9025 Version: 0.1.0.9026
Author: c(person("Andreas", "Gammelgaard Damsbo", email = "agdamsbo@pm.me", role = c("cre", "aut"))) Author: c(person("Andreas", "Gammelgaard Damsbo", email = "agdamsbo@pm.me", role = c("cre", "aut")))
Maintainer: Andreas Gammelgaard Damsbo <agdamsbo@pm.me> Maintainer: Andreas Gammelgaard Damsbo <agdamsbo@pm.me>
Description: I am a Danish medical doctor involved in neuropsychiatric research. Description: I am a Danish medical doctor involved in neuropsychiatric research.

21
R/strobe_pred.R
View File

@ -6,7 +6,7 @@
#' @param data dataframe of data. #' @param data dataframe of data.
#' @param dec decimals for results, standard is set to 2. Mean and sd is dec-1. #' @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 for outcome meassure not NA. #' @param n.by.adj flag to indicate wether to count number of patients in adjusted model or overall for outcome meassure not NA.
#' @param p.val flag to include p-values in linear regression for now, set to FALSE as standard. #' @param p.val flag to include p-values in table, set to FALSE as standard.
#' @keywords logistic #' @keywords logistic
#' @export #' @export
@ -140,10 +140,10 @@ strobe_pred<-function(meas,adj,data,dec=2,n.by.adj=FALSE,p.val=FALSE){
for (i in 1:ncol(dat2)){ for (i in 1:ncol(dat2)){
if (is.factor(dat2[,i])){ if (is.factor(dat2[,i])){
rnames<-c(rnames,names(dat2)[i],paste0(names(dat2)[i],levels(dat2[,i]))) rnames<-c(rnames,names(dat2)[i],levels(dat2[,i]))
} }
if (!is.factor(dat2[,i])){ if (!is.factor(dat2[,i])){
rnames<-c(rnames,paste0(names(dat2)[i],".all"),names(dat2)[i]) rnames<-c(rnames,names(dat2[i]),"Per unit increase")
} }
} }
res<-cbind(aor_ci,apv) res<-cbind(aor_ci,apv)
@ -163,9 +163,16 @@ strobe_pred<-function(meas,adj,data,dec=2,n.by.adj=FALSE,p.val=FALSE){
suppressWarnings(re<-left_join(df,dfcr,by="names")) suppressWarnings(re<-left_join(df,dfcr,by="names"))
ref<-data.frame(re[,1],re[,2],re[,5],re[,3]) if (p.val==TRUE){
ref<-data.frame(re[,1],re[,2],re[,5],re[,6],re[,3],re[,4])
names(ref)<-c("Variable",paste0("N=",n.meas),"Crude OR (95 % CI)","Mutually adjusted OR (95 % CI)") names(ref)<-c("Variable",paste0("N=",n.meas),"Crude OR (95 % CI)","p-value","Mutually adjusted OR (95 % CI)","A p-value")
}
else{
ref<-data.frame(re[,1],re[,2],re[,5],re[,3])
names(ref)<-c("Variable",paste0("N=",n.meas),"Crude OR (95 % CI)","Mutually adjusted OR (95 % CI)")
}
ls<-list(tbl=ref,miss,n.meas,nrow(d)) ls<-list(tbl=ref,miss,n.meas,nrow(d))
names(ls)<-c("Printable table","Deleted due to missingness in adjusted analysis","Number of outcome observations","Length of dataframe") names(ls)<-c("Printable table","Deleted due to missingness in adjusted analysis","Number of outcome observations","Length of dataframe")
@ -297,10 +304,10 @@ strobe_pred<-function(meas,adj,data,dec=2,n.by.adj=FALSE,p.val=FALSE){
for (i in 1:ncol(dat2)){ for (i in 1:ncol(dat2)){
if (is.factor(dat2[,i])){ if (is.factor(dat2[,i])){
rnames<-c(rnames,names(dat2)[i],paste0(names(dat2)[i],levels(dat2[,i]))) rnames<-c(rnames,names(dat2)[i],levels(dat2[,i]))
} }
if (!is.factor(dat2[,i])){ if (!is.factor(dat2[,i])){
rnames<-c(rnames,paste0(names(dat2)[i],".all"),names(dat2)[i]) rnames<-c(rnames,names(dat2[i]),"Per unit increase")
} }
} }
res<-cbind(amean_ci,apv) res<-cbind(amean_ci,apv)

2
man/strobe_pred.Rd
View File

@ -18,7 +18,7 @@ strobe_pred(meas, adj, data, dec = 2, n.by.adj = FALSE,
\item{n.by.adj}{flag to indicate wether to count number of patients in adjusted model or overall for outcome meassure not NA.} \item{n.by.adj}{flag to indicate wether to count number of patients in adjusted model or overall for outcome meassure not NA.}
\item{p.val}{flag to include p-values in linear regression for now, set to FALSE as standard.} \item{p.val}{flag to include p-values in table, set to FALSE as standard.}
} }
\description{ \description{
Printable table of regression model according to STROBE. Includes borth bivariate and multivariate in the same table. Output is a list, with the first item being the main "output" as a dataframe. Automatically uses logistic regression model for dichotomous outcome variable and linear regression model for continous outcome variable. Linear regression will give estimated adjusted true mean in list. Printable table of regression model according to STROBE. Includes borth bivariate and multivariate in the same table. Output is a list, with the first item being the main "output" as a dataframe. Automatically uses logistic regression model for dichotomous outcome variable and linear regression model for continous outcome variable. Linear regression will give estimated adjusted true mean in list.