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This commit is contained in:
Andreas Gammelgaard Damsbo
parent
09719ea905
commit
23827402f8
@ -1,10 +1,6 @@
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Package: daDoctoR
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Title: Functions For Health Research
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<<<<<<< HEAD
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Version: 0.21.7
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=======
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Version: 0.21.5
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>>>>>>> d8ffa3dc7b67e43a846bbd58e055a141a010b304
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Version: 0.21.8
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Year: 2021
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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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@ -1,6 +1,6 @@
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#' REWRITE UNDERWAY
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#' Print regression results in table
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#'
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#' Print regression results according to STROBE
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#' New function ready for revision / rewrite
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#'
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#' Printable table of two dimensional regression analysis of group vs variable for outcome measure. By group. Includes p-value
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#' Group and variable has to be dichotomous factor.
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@ -16,14 +16,9 @@
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#' data('mtcars')
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#' mtcars$vs<-factor(mtcars$vs)
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#' mtcars$am<-factor(mtcars$am)
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#' strobe_diff_bygroup(meas="mpg",var="vs",group = "am",adj=c("disp","wt"),data=mtcars)
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#' print_diff_bygroup(meas="mpg",var="vs",group = "am",adj=c("disp","wt"),data=mtcars)
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<<<<<<< HEAD
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print_diff_bygroup<-function(meas,var,group,adj,data,dec=2){
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=======
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strobe_diff_bygroup<-function(meas,var,group,adj,data,dec=2){
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>>>>>>> d8ffa3dc7b67e43a846bbd58e055a141a010b304
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## meas: sdmt
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## var: rtreat
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## group: genotype
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@ -1,6 +1,6 @@
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#' REWRITE UNDERWAY
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#' Printable table of three dimensional regression analysis
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#'
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#' Print regression results according to STROBE
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#' New function ready for revision
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#'
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#' Printable table of three dimensional regression analysis of group vs var for meas. By var. Includes p-values.
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#' @param meas outcome meassure variable name in data-data.frame as a string. Can be numeric or factor. Result is calculated accordingly.
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@ -9,20 +9,15 @@
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#' @param adj variables to adjust for, as string.
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#' @param data dataframe of data.
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#' @param dec decimals for results, standard is set to 2. Mean and sd is dec-1.
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#' @keywords strobe
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#' @keywords table
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#' @export
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#' @examples
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#' data('mtcars')
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#' mtcars$vs<-factor(mtcars$vs)
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#' mtcars$am<-factor(mtcars$am)
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#' strobe_diff_byvar(meas="mpg",var="vs",group = "am",adj=c("disp","wt","hp"),data=mtcars)
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#' print_diff_byvar(meas="mpg",var="vs",group = "am",adj=c("disp","wt","hp"),data=mtcars)
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<<<<<<< HEAD
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print_diff_byvar<-function(meas,var,group,adj,data,dec=2){
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=======
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strobe_diff_byvar<-function(meas,var,group,adj,data,dec=2){
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>>>>>>> d8ffa3dc7b67e43a846bbd58e055a141a010b304
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## meas: sdmt
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## var: rtreat
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## group: genotype
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#' Print regression results according to STROBE
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#' Print regression results in table
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#'
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#' Printable table of logistic regression analysis according to STROBE.
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#' New function ready for revision
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#'
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#' Printable table of logistic regression analysis. Leaves out other variables from results.
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#' @param meas outcome meassure variable name in data-data.frame as a string. Can be numeric or factor. Result is calculated accordingly.
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#' @param var exposure variable to compare against (active vs placebo). As string.
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#' @param adj variables to adjust for, as string.
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@ -9,11 +11,7 @@
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#' @keywords logistic
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#' @export
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<<<<<<< HEAD
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print_log<-function(meas,var,adj,data,dec=2){
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=======
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strobe_log<-function(meas,var,adj,data,dec=2){
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>>>>>>> d8ffa3dc7b67e43a846bbd58e055a141a010b304
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## Ønskeliste:
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##
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## - Sum af alle, der indgår (Overall N)
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#' Print ordinal logistic regression results according to STROBE
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#' Print ordinal logistic regression results in table
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#'
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#' Printable table of ordinal logistic regression with bivariate and multivariate analyses.
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#' Table according to STROBE. Uses polr() funtion of the MASS-package.
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#' Uses polr() funtion of the MASS-package. Prints table.
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#' Formula analysed is the most simple m~v1+v2+vn. The is no significance test. Results are point estimates with 95 percent CI.
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#' @param meas outcome meassure variable name or response in data-data.frame as a string. Should be factor, preferably ordered.
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#' @param vars variables to compare against. As vector of columnnames.
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#' @keywords olr
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#' @export
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<<<<<<< HEAD
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print_olr<-function(meas,vars,data,dec=2,n.by.adj=FALSE){
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=======
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strobe_olr<-function(meas,vars,data,dec=2,n.by.adj=FALSE){
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>>>>>>> d8ffa3dc7b67e43a846bbd58e055a141a010b304
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## For calculation of p-value from t-value see rep_olr()
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require(MASS)
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#' Regression model of predictors according to STROBE, bi- and multivariable.
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#' Regression model of predictors according to STROBE, bi- and multivariable. Printable result.
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#'
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#' Printable table of regression model according to STROBE for linear or binary outcome-variables.
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#' Includes both bivariate and multivariate in the same table.
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#' @keywords logistic
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#' @export
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<<<<<<< HEAD
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print_pred<-function(meas,adj,data,dec=2,n.by.adj=FALSE,p.val=FALSE){
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=======
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strobe_pred<-function(meas,adj,data,dec=2,n.by.adj=FALSE,p.val=FALSE){
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>>>>>>> d8ffa3dc7b67e43a846bbd58e055a141a010b304
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## Wish list:
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## - SPEED, maybe flags to include/exclude time consuming tasks
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@ -2,7 +2,7 @@
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% Please edit documentation in R/print_diff_bygroup.R
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\name{print_diff_bygroup}
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\alias{print_diff_bygroup}
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\title{REWRITE UNDERWAY}
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\title{Print regression results in table}
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\usage{
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print_diff_bygroup(meas, var, group, adj, data, dec = 2)
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}
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\item{dec}{decimals for results, standard is set to 2. Mean and sd is dec-1. pval has 3 decimals.}
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}
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\description{
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Print regression results according to STROBE
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New function ready for revision / rewrite
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}
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\details{
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Printable table of two dimensional regression analysis of group vs variable for outcome measure. By group. Includes p-value
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data('mtcars')
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mtcars$vs<-factor(mtcars$vs)
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mtcars$am<-factor(mtcars$am)
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strobe_diff_bygroup(meas="mpg",var="vs",group = "am",adj=c("disp","wt"),data=mtcars)
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print_diff_bygroup(meas="mpg",var="vs",group = "am",adj=c("disp","wt"),data=mtcars)
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}
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\keyword{strobe}
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% Please edit documentation in R/print_diff_byvar.R
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\name{print_diff_byvar}
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\alias{print_diff_byvar}
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\title{REWRITE UNDERWAY}
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\title{Printable table of three dimensional regression analysis}
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\usage{
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print_diff_byvar(meas, var, group, adj, data, dec = 2)
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}
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\item{dec}{decimals for results, standard is set to 2. Mean and sd is dec-1.}
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}
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\description{
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Print regression results according to STROBE
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New function ready for revision
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}
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\details{
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Printable table of three dimensional regression analysis of group vs var for meas. By var. Includes p-values.
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data('mtcars')
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mtcars$vs<-factor(mtcars$vs)
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mtcars$am<-factor(mtcars$am)
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strobe_diff_byvar(meas="mpg",var="vs",group = "am",adj=c("disp","wt","hp"),data=mtcars)
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print_diff_byvar(meas="mpg",var="vs",group = "am",adj=c("disp","wt","hp"),data=mtcars)
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}
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\keyword{strobe}
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\keyword{table}
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% Please edit documentation in R/print_log.R
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\name{print_log}
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\alias{print_log}
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\title{Print regression results according to STROBE}
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\title{Print regression results in table}
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\usage{
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print_log(meas, var, adj, data, dec = 2)
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}
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@ -18,6 +18,9 @@ print_log(meas, var, adj, data, dec = 2)
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\item{dec}{decimals for results, standard is set to 2. Mean and sd is dec-1.}
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}
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\description{
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Printable table of logistic regression analysis according to STROBE.
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New function ready for revision
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}
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\details{
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Printable table of logistic regression analysis. Leaves out other variables from results.
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}
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\keyword{logistic}
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% Please edit documentation in R/print_olr.R
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\name{print_olr}
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\alias{print_olr}
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\title{Print ordinal logistic regression results according to STROBE}
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\title{Print ordinal logistic regression results in table}
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\usage{
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print_olr(meas, vars, data, dec = 2, n.by.adj = FALSE)
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}
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@ -19,7 +19,7 @@ print_olr(meas, vars, data, dec = 2, n.by.adj = FALSE)
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}
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\description{
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Printable table of ordinal logistic regression with bivariate and multivariate analyses.
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Table according to STROBE. Uses polr() funtion of the MASS-package.
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Uses polr() funtion of the MASS-package. Prints table.
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Formula analysed is the most simple m~v1+v2+vn. The is no significance test. Results are point estimates with 95 percent CI.
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}
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\keyword{olr}
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@ -2,7 +2,7 @@
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% Please edit documentation in R/print_pred.R
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\name{print_pred}
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\alias{print_pred}
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\title{Regression model of predictors according to STROBE, bi- and multivariable.}
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\title{Regression model of predictors according to STROBE, bi- and multivariable. Printable result.}
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\usage{
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print_pred(meas, adj, data, dec = 2, n.by.adj = FALSE, p.val = FALSE)
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}
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@ -1,11 +1,9 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/print_diff_bygroup.R, R/strobe_diff_bygroup.R
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% Please edit documentation in R/strobe_diff_bygroup.R
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\name{strobe_diff_bygroup}
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\alias{strobe_diff_bygroup}
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\title{REWRITE UNDERWAY - replaced by 'print_diff_bygroup'}
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\usage{
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strobe_diff_bygroup(meas, var, group, adj, data, dec = 2)
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strobe_diff_bygroup(meas, var, group, adj, data, dec = 2)
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}
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\arguments{
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\item{dec}{decimals for results, standard is set to 2. Mean and sd is dec-1. pval has 3 decimals.}
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}
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\description{
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Print regression results according to STROBE
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Print regression results according to STROBE
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}
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\details{
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Printable table of two dimensional regression analysis of group vs variable for outcome measure. By group. Includes p-value
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Group and variable has to be dichotomous factor.
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Printable table of two dimensional regression analysis of group vs variable for outcome measure. By group. Includes p-value
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Group and variable has to be dichotomous factor.
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}
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@ -38,9 +31,5 @@ Group and variable has to be dichotomous factor.
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mtcars$vs<-factor(mtcars$vs)
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mtcars$am<-factor(mtcars$am)
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strobe_diff_bygroup(meas="mpg",var="vs",group = "am",adj=c("disp","wt"),data=mtcars)
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data('mtcars')
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mtcars$vs<-factor(mtcars$vs)
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mtcars$am<-factor(mtcars$am)
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strobe_diff_bygroup(meas="mpg",var="vs",group = "am",adj=c("disp","wt"),data=mtcars)
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}
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\keyword{strobe}
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@ -1,11 +1,9 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/print_diff_byvar.R, R/strobe_diff_byvar.R
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% Please edit documentation in R/strobe_diff_byvar.R
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\name{strobe_diff_byvar}
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\alias{strobe_diff_byvar}
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\title{REWRITE UNDERWAY - replaced by 'print_diff_byvar'}
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\usage{
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strobe_diff_byvar(meas, var, group, adj, data, dec = 2)
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strobe_diff_byvar(meas, var, group, adj, data, dec = 2)
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}
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\arguments{
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\item{dec}{decimals for results, standard is set to 2. Mean and sd is dec-1.}
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}
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\description{
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Print regression results according to STROBE
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Print regression results according to STROBE
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}
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\details{
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Printable table of three dimensional regression analysis of group vs var for meas. By var. Includes p-values.
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Printable table of three dimensional regression analysis of group vs var for meas. By var. Includes p-values.
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}
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\examples{
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@ -36,9 +30,5 @@ Printable table of three dimensional regression analysis of group vs var for mea
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mtcars$vs<-factor(mtcars$vs)
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mtcars$am<-factor(mtcars$am)
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strobe_diff_byvar(meas="mpg",var="vs",group = "am",adj=c("disp","wt","hp"),data=mtcars)
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data('mtcars')
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mtcars$vs<-factor(mtcars$vs)
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mtcars$am<-factor(mtcars$am)
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strobe_diff_byvar(meas="mpg",var="vs",group = "am",adj=c("disp","wt","hp"),data=mtcars)
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}
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\keyword{strobe}
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@ -1,11 +1,9 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/print_log.R, R/strobe_log.R
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% Please edit documentation in R/strobe_log.R
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\name{strobe_log}
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\alias{strobe_log}
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\title{OBSOLETE - use 'print_log'}
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\usage{
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strobe_log(meas, var, adj, data, dec = 2)
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strobe_log(meas, var, adj, data, dec = 2)
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}
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\arguments{
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\item{dec}{decimals for results, standard is set to 2. Mean and sd is dec-1.}
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}
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\description{
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Print regression results according to STROBE
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}
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\details{
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Printable table of logistic regression analysis according to STROBE.
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Print regression results according to STROBE
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}
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\details{
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@ -1,11 +1,9 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/print_olr.R, R/strobe_olr.R
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% Please edit documentation in R/strobe_olr.R
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\name{strobe_olr}
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\alias{strobe_olr}
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\title{OBSOLETE - use 'print_olr'}
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\usage{
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strobe_olr(meas, vars, data, dec = 2, n.by.adj = FALSE)
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strobe_olr(meas, vars, data, dec = 2, n.by.adj = FALSE)
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}
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\arguments{
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\item{n.by.adj}{flag to indicate wether to count number of patients in adjusted model or overall for outcome meassure not NA.}
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}
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\description{
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Print ordinal logistic regression results according to STROBE
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}
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\details{
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Printable table of ordinal logistic regression with bivariate and multivariate analyses.
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Table according to STROBE. Uses polr() funtion of the MASS-package.
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Formula analysed is the most simple m~v1+v2+vn. The is no significance test. Results are point estimates with 95 percent CI.
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Print ordinal logistic regression results according to STROBE
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}
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\details{
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@ -1,11 +1,9 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/print_pred.R, R/strobe_pred.R
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% Please edit documentation in R/strobe_pred.R
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\name{strobe_pred}
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\alias{strobe_pred}
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\title{OBSOLETE - use 'print_pred'}
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\usage{
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strobe_pred(meas, adj, data, dec = 2, n.by.adj = FALSE, p.val = FALSE)
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strobe_pred(meas, adj, data, dec = 2, n.by.adj = FALSE, p.val = FALSE)
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}
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\arguments{
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@ -22,15 +20,6 @@ strobe_pred(meas, adj, data, dec = 2, n.by.adj = FALSE, p.val = FALSE)
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\item{p.val}{flag to include p-values in table, set to FALSE as standard.}
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}
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\description{
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Regression model of predictors according to STROBE, bi- and multivariable.
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}
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\details{
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Printable table of regression model according to STROBE for linear or binary outcome-variables.
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Includes both bivariate and multivariate in the same table.
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Output is a list, with the first item being the main "output" as a dataframe.
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Automatically uses logistic regression model for dichotomous outcome variable and linear regression model for continuous outcome variable. Linear regression will give estimated adjusted true mean in list.
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For logistic regression gives count of outcome variable pr variable level.
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Regression model of predictors according to STROBE, bi- and multivariable.
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}
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\details{
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