154 lines
4.2 KiB
Plaintext
154 lines
4.2 KiB
Plaintext
---
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title: "Table One - enriched"
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author: "Andreas Gammelgaard Damsbo"
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date: "Knitted: `r format(Sys.time(), '%d %B, %Y')`"
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output: pdf_document
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---
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```{r setup, include=FALSE}
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knitr::opts_chunk$set(echo = TRUE, message = FALSE)
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```
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# Import
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```{r}
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dta<-read.csv("/Volumes/Data/depression/dep_dataset.csv")
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```
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## Formatting
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```{r}
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dta$diabetes<-factor(dta$diabetes)
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dta$pad<-factor(dta$pad)
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dta$civil<-factor(dta$civil)
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dta$hypertension<-factor(dta$hypertension)
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dta$afli<-factor(dta$afli)
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dta$smoke_ever<-factor(dta$smoke_ever)
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dta$ami<-factor(dta$ami)
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dta$tci<-factor(dta$tci)
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dta$thrombolysis<-factor(dta$thrombolysis)
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dta$thrombechtomy<-factor(dta$thrombechtomy)
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dta$rep_any<-factor(dta$rep_any)
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dta$pad<-factor(dta$pad)
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dta$nihss_0<-as.numeric(dta$nihss_0)
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dta$age<-as.numeric(dta$age)
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dta$rtreat<-factor(dta$rtreat)
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dta$sex<-factor(dta$sex)
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dta$pase_0<-as.numeric(dta$pase_0)
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dta$bmi<-as.numeric(dta$bmi)
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dta$mdi_6<-as.numeric(dta$mdi_6)
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dta$inc_time<-as.numeric(dta$inc_time)
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dta$bmi_isna<-is.na(dta$bmi)
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dta$nihss_0_isna<-is.na(dta$nihss_0)
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```
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# Defining patients to include for analysis
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```{r message=FALSE}
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library(dplyr)
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```
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Only including cases with complete pase_0 and MDI at 1 & 6 months
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```{r}
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dta<-dta[!is.na(dta$pase_0),]
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# &!is.na(dta$mdi_1)&!is.na(dta$mdi_6)
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```
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## Defining table one stratification
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```{r}
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dta$strat_table_one<-factor(case_when(dta$excluded_6%in%c("mi_6","ex_6")~"zExcluded",
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dta$pase_0_bin=="lower"~"xLower",
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dta$pase_0_bin=="higher"~"yHigher"))
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summary(dta$strat_table_one)
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```
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```{r}
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dta$in_ex<-plyr::mapvalues(dta$strat_table_one,
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from=c("xLower", "yHigher"),
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to=c("xIncluded","xIncluded"))
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# summary(dta$in_ex)
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```
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# Basic analyses
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```{r}
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show(mdn<-median(dta$pase_0))
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hist(dta$pase_0,100)
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hist(sqrt(dta$pase_0),100)
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```
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# Table One
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```{r}
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library(tableone)
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```
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```{r}
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tbl_norm<-c("rtreat","age","sex","bmi","bmi_isna","smoke_ever","civil","diabetes",
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"hypertension", "afli", "ami", "tci","pad","nihss_0","nihss_0_isna",
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"thrombolysis", "thrombechtomy","rep_any","inc_time")
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tbl_cat<-c("rtreat","sex","bmi_isna","diabetes", "hypertension", "smoke_ever","civil",
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"ami", "tci","nihss_0_isna", "thrombolysis",
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"thrombechtomy","rep_any")
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tbl_non<-c("age","nihss_0","inc_time")
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```
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```{r}
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tab1 <- CreateTableOne(vars = tbl_norm, data = dta,
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factorVars = tbl_cat,includeNA = TRUE)
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tbl1_1<-print(tab1, contDigits = 1, missing=T,showAllLevels=T ,
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nonnormal = tbl_non, smd = FALSE, quote = F, noSpaces = TRUE)
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```
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```{r}
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tab2 <- CreateTableOne(vars = tbl_norm, strata="pase_0_bin",
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data = dta, factorVars = tbl_cat,includeNA = T)
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tbl1_2<-print(tab2, contDigits = 1, missing=T,showAllLevels=T,
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nonnormal = tbl_non, smd = F,test = T, quote = F, noSpaces = TRUE)
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```
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```{r}
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tab3 <- CreateTableOne(vars = tbl_norm, strata="strat_table_one",
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data = dta, factorVars = tbl_cat,includeNA = T)
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tbl1_3<-print(tab3, contDigits = 1, missing=T,showAllLevels=T,
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nonnormal = tbl_non, smd = F,test = T, quote = F, noSpaces = TRUE)
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```
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```{r}
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tab4 <- CreateTableOne(vars = tbl_norm, strata="in_ex",
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data = dta, factorVars = tbl_cat,includeNA = T)
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tbl1_4<-print(tab4, contDigits = 1, missing=T,showAllLevels=T,
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nonnormal = tbl_non, smd = F,test = T, quote = F, noSpaces = TRUE)
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```
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```{r}
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table(is.na(dta$nihss_0),dta$strat_table_one)
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table(is.na(dta$bmi),dta$strat_table_one)
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```
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```{r}
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dta<-dta[dta$strat_table_one!="zExcluded",]
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dta$strat_table_one<-factor(dta$strat_table_one)
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tab5 <- CreateTableOne(vars = tbl_norm, strata="strat_table_one",
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data = dta, factorVars = tbl_cat,includeNA = T)
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tbl1_5<-print(tab5, contDigits = 1, missing=T,showAllLevels=T,
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nonnormal = tbl_non, smd = F,test = T, quote = F, noSpaces = TRUE)
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```
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```{r}
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tbl_list<-list(tbl1_1,tbl1_2,tbl1_3,tbl1_4,tbl1_5)
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for (i in 1:length(tbl_list)){
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nm<-paste0("tbl1_",i)
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write.csv(tbl_list[[i]],
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paste0("/Volumes/Data/depression/",nm,"_enr_",
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lubridate::today(),".csv"))
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}
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```
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