io28-mockstudy_analysis_chisq.Rmd

---
title: "Chisq and basic graphs from mockstudy"
author: "Peter Higgins"
date: "4/25/2019"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(arsenal)
library(survival)
library(survminer)
library(patchwork)
library(tidyverse)
library(janitor)
library(gt)
data("mockstudy")
```

### Take a look at the data



```{r glimpse}
glimpse(mockstudy)
```
### Set up a chisquared table
with text interpretation with inline r code.

```{r table, warning=FALSE}
mockstudy %>% 
  tabyl(arm, fu.stat) ->
outcome_table
names(outcome_table) <- c("Study Arm", "Lived", "Died")
outcome_table %>% 
  gt()
```


```{r chisq, messages=FALSE}
mockstudy %>% 
  tabyl(arm, fu.stat) %>% 
  column_to_rownames('arm') %>% 
  chisq.test() ->
results

results$statistic
results$parameter
```

### Study Results

This is a statement of study results. <br>

In the evaluation of followup status by study arm, the null hypothesis of independence was rejected, with a chi-squared statistic of `r round(results$statistic,2)`, with `r results$parameter` degrees of freedom, and a p value of `r results$p.value`, using the `r results$method` method.

```{r}



```

### Start with a barplot
for percent survival
tag it as panel A for a multipanel plot

```{r survival_barplot}
mockstudy %>% 
  group_by(arm) %>% 
  summarize(surv = length(which(fu.stat==1)),
         died = length(which(fu.stat==2)),
         pct_surv = surv*100/(died+surv)) %>% 
  select(arm, surv, died, pct_surv) %>% 
  ggplot() +
  aes(x=arm, y = pct_surv, fill=arm,
      label= round(pct_surv,1)) +
  geom_bar(stat= 'identity') +
  labs(y= "Percent Survived \n To End of Followup", x= "Study Arm", tag ="A") +
  theme_classic2(base_size = 15) +
  theme(legend.position = 'none') +
  geom_text(size=5, vjust=-0.3) +
  scale_fill_manual(values = c("black", "green", "blue")) +
  ylim(0,18) ->
p1
```

### Now add a boxplot, make it multipanel
tagged as panel B

```{r survivaltime_boxplot}
mockstudy %>% 
  group_by(arm) %>% 
ggplot() +
  aes(x=arm, y = fu.time, fill=arm) +
  geom_violin(alpha =0.3) +
  geom_jitter(width =0.25, alpha=0.15) +
  labs(y= "Survival Time in \nDays (Censored)", x= "Study Arm", tag = "B") +
  theme_classic2(base_size = 15) +
  theme(legend.position = 'none') +
  scale_fill_manual(values = c("black", "green", "blue")) ->
p2

p1 + p2   + plot_layout(ncol=2, heights = c(4,4))
```



### Now add a survival curve
For some reason, patchwork does not work with this survival curve

```{r survival_curves}
survfit(formula = Surv(fu.time, fu.stat) ~ arm, data= mockstudy) ->
fit

ggsurvplot(fit,
           pval = TRUE, conf.int = TRUE,
           risk.table = TRUE,
           risk.table.col = "strata",
           linetype = "strata",
           surv.median.line = "hv",
           ggtheme = theme_bw(),
           palette = c("black", "blue", "gray80")) 


```