2014-11-13-HW10-Liangquan-Zhou.Rmd

---
title: "ADA HW10"
author: "Liangquan Zhou lz2377"
date: "November 13, 2014"
output: pdf_document
---

Consider the Mayo Clinic Lung Cancer Data in R package survival: data(lung) or data(cancer): including the variables

$\ \ \ $  inst: Institution code
 
$\ \ \ $   time: Survival time in 
 
$\ \ \ $   status: censoring status 1=censored, 2=dead
 
 $\ \ \ $  age: Age in years
 
 $\ \ \ $  sex: Male=1 Female=2, etc.
 
```{r, warning=FALSE, message=FALSE}
library(survival)
dat = lung
```
 
## 1. Estimate and plot the survival curves for time BY sex using the following methods:

### Kaplan-Meier
```{r, warning=FALSE, message=FALSE}
fit1 <- survfit(Surv(time, status) ~ sex, data=dat)
plot(fit1, lty=2:3, main = "Kaplan-Meier Estimates for Lung Cancer Data")
legend("bottomleft", c("male", "female"), lty = c(2,3))
```

### Fleming-Harrington
```{r, warning=FALSE, message=FALSE}
fit2 <- survfit(Surv(time, status) ~ sex, type = "fh2", data=dat)
plot(fit2, lty=2:3,  main = "Fleming-Harrington Estimates for Lung Cancer Data")
legend("bottomleft", c("male", "female"), lty = c(2,3))
```

## 2. For each case in 1, estimate the median survival time, using the estimated survival curves.

```{r, warning=FALSE,message=FALSE}
print(fit1)
print(fit2)
```
We can see that the the median survival time for male and female using `Kplan-Meier` Estimates are 270 and 426;

The median survival time for male and female using `Fleming-Harrington` Estimates are also 270 and 426;