165 lines
4.7 KiB
Plaintext
165 lines
4.7 KiB
Plaintext
|
---
|
||
|
title: "Patient flowchart and chi^2 tests"
|
||
|
author: "Andreas Gammelgaard Damsbo"
|
||
|
date: "Knitted: `r format(Sys.time(), '%d %B, %Y')`"
|
||
|
output: pdf_document
|
||
|
---
|
||
|
|
||
|
```{r setup, include=FALSE}
|
||
|
knitr::opts_chunk$set(echo = TRUE, message = FALSE)
|
||
|
```
|
||
|
|
||
|
# Import
|
||
|
```{r}
|
||
|
dta_all<-read.csv("/Volumes/Data/depression/dep_dataset.csv")
|
||
|
```
|
||
|
|
||
|
# Defining patients to include for analysis
|
||
|
Only including cases with complete pase_0 and MDI at 1 & 6 months
|
||
|
```{r}
|
||
|
dta<-dta_all[!is.na(dta_all$pase_0),]
|
||
|
# &!is.na(dta$mdi_1)&!is.na(dta$mdi_6)
|
||
|
```
|
||
|
|
||
|
# Backup
|
||
|
```{r}
|
||
|
dta_b<-dta
|
||
|
```
|
||
|
|
||
|
|
||
|
# Sammentællinger
|
||
|
```{r}
|
||
|
summary(cbind(is.na(dta_all[,c("pase_0","mdi_1","mdi_1_enr","mdi_6_newobs","mdi_6_newobs_enr")]),
|
||
|
both_missing=is.na(dta$mdi_1)&is.na(dta$mdi_6_newobs),
|
||
|
either_missing=is.na(dta$mdi_1)|is.na(dta$mdi_6_newobs)))
|
||
|
```
|
||
|
|
||
|
|
||
|
```{r}
|
||
|
suppressWarnings(summary(cbind(all_particip=dta_all$mors_180=="yes",
|
||
|
all_pase0=dta$mors_180=="yes",
|
||
|
all_mdi_1=!is.na(dta$mdi_1)&dta$mors_180=="yes"))) # Antal der dør
|
||
|
|
||
|
table(dta$pase_0_bin,factor(dta$mors_180)) # Antal der dør, stratificeret efter PASE gruppe
|
||
|
```
|
||
|
|
||
|
```{r}
|
||
|
# summary(factor(dta$mors_v1))
|
||
|
# summary(factor(dta$mors_v16)) # OBS medregnet er 2 dødsfald, der ikke har MDI 1.
|
||
|
```
|
||
|
|
||
|
# Flow
|
||
|
|
||
|
## 1 month
|
||
|
|
||
|
Shows counts of all patients withs missing MDI 1 scores.
|
||
|
```{r message=FALSE}
|
||
|
source("/Volumes/Data/depression/function_flow.R") # Home made flow function
|
||
|
show(flow_prog(df=dta[dta$excluded_1%in%c("ex_1","mi_1","ca_1"),],
|
||
|
sngl=c("mors_v1","drop1"),
|
||
|
sngl_keep=c("no","yes"),
|
||
|
mltp=c("open_treat","wants_out","side_effect","side_effect2")))
|
||
|
# v1<-dta$rnumb[dta$excluded_1%in%c("ex_1","mi_1")]
|
||
|
```
|
||
|
|
||
|
Same overview, but vectorised
|
||
|
```{r}
|
||
|
summary(factor(dta$excluded_1))
|
||
|
|
||
|
# dt_1 are organic data, en_1 are enriched, ex_1 are excluded, mi_1 were missing,
|
||
|
# ca_1 were missing at 1 month, but held data at 6 months, and thus carried along.
|
||
|
```
|
||
|
|
||
|
|
||
|
|
||
|
## 6 months
|
||
|
|
||
|
Shows counts of all patients withs missing MDI 6 scores.
|
||
|
```{r}
|
||
|
show(flow_prog(df=dta[is.na(dta$mdi_6_newobs_enr)&dta$excluded_6%in%c("ex_6"),], #
|
||
|
sngl=c("mors_v16","drop16"),
|
||
|
sngl_keep=c("no","yes"),
|
||
|
mltp=c("open_treat","wants_out","side_effect","side_effect2")))
|
||
|
# v2<-dta$rnumb[is.na(dta$mdi_6_newobs_enr)&dta$excluded_1%in%c("ca_1","dt_1")]
|
||
|
```
|
||
|
|
||
|
```{r}
|
||
|
summary(factor(dta$excluded_6))
|
||
|
|
||
|
# dt_6 are organic data, en_6 are enriched, ex_6 are excluded, mi_6 were excluded at 1 month.
|
||
|
# At 6 month 118 are excluded due to any cause
|
||
|
# Due to later inclusion of ca_1 patients, the sum of patients excluded at 6 months is 71+62-16=117
|
||
|
```
|
||
|
|
||
|
This flow counts all patients dying or dropping out early after 1 month. Some have a recorded MDI at dropout. This is just to give a perspective on data.
|
||
|
```{r}
|
||
|
show(flow_prog(df=dta, #
|
||
|
sngl=c("mors_v16","drop16"),
|
||
|
sngl_keep=c("no","yes"),
|
||
|
mltp=c("open_treat","wants_out","side_effect","side_effect2")))
|
||
|
# v2<-dta$rnumb[is.na(dta$mdi_6_newobs_enr)&dta$excluded_1%in%c("ca_1","dt_1")]
|
||
|
```
|
||
|
|
||
|
```{r}
|
||
|
summary(as.numeric(dta$inc_time[dta$drop16=="yes"]))
|
||
|
```
|
||
|
|
||
|
|
||
|
# Chi^2 tests
|
||
|
|
||
|
```{r}
|
||
|
source("/Volumes/Data/depression/function_chi_test_sum.R")
|
||
|
ex_lst<-list()
|
||
|
ex_var<-c("mdi_1_enr","rtreat","pase_0_bin")
|
||
|
for (i in 2:3){
|
||
|
ex_lst <- append(ex_lst,chi_test_sum(a=is.na(dta[,ex_var[1]]),
|
||
|
b=dta[,ex_var[i]],
|
||
|
aname=ex_var[1],
|
||
|
bname=ex_var[i]))
|
||
|
}
|
||
|
```
|
||
|
|
||
|
```{r}
|
||
|
# ex_var<-c("open_treat","rtreat","pase_0_bin")
|
||
|
# for (i in 2:3){
|
||
|
# ex_lst <- append(ex_lst,
|
||
|
# chi_test_sum(a=dta[,ex_var[1]],
|
||
|
# b=dta[,ex_var[i]],
|
||
|
# aname=ex_var[1],
|
||
|
# bname=ex_var[i]))
|
||
|
# }
|
||
|
|
||
|
## Taget ud grundet for lave tal
|
||
|
```
|
||
|
|
||
|
```{r}
|
||
|
ex_var<-c("mdi_1_enr","rtreat","pase_0_bin")
|
||
|
for (i in 2:3){
|
||
|
ex_lst <- append(ex_lst,
|
||
|
chi_test_sum(a=is.na(dta$mdi_6_newobs_enr)&!is.na(dta$mdi_1_enr),
|
||
|
b=dta[,ex_var[i]],
|
||
|
aname="Excluded at 6 months",
|
||
|
bname=ex_var[i]))
|
||
|
}
|
||
|
for (i in 2:3){
|
||
|
ex_lst <- append(ex_lst,
|
||
|
chi_test_sum(a=is.na(dta$mdi_6_newobs_enr),
|
||
|
b=dta[,ex_var[i]],
|
||
|
aname="Total unavailable at 6 months",
|
||
|
bname=ex_var[i]))
|
||
|
}
|
||
|
```
|
||
|
|
||
|
|
||
|
```{r}
|
||
|
# ex_var<-c("open_treat","rtreat","pase_0_bin")
|
||
|
# for (i in 2:3){
|
||
|
# ex_lst <- append(ex_lst,
|
||
|
# chi_test_sum(a=dta[,ex_var[1]],
|
||
|
# b=dta[,ex_var[i]],
|
||
|
# aname=ex_var[1],
|
||
|
# bname=ex_var[i]))
|
||
|
# }
|
||
|
show(ex_lst)
|
||
|
```
|