Poisson Regression in R

library(readr)

## Warning: package 'readr' was built under R version 3.4.1

bladder.dat <- read_csv("~/BiostatCourses/PublicHealthComputing/Lectures/Week10GLM/R/bladder.csv")

## Parsed with column specification:
## cols(
##   time = col_integer(),
##   x = col_integer(),
##   n = col_integer()
## )

head(bladder.dat)

## # A tibble: 6 x 3
##    time     x     n
##   <int> <int> <int>
## 1     2     0     1
## 2     3     0     1
## 3     6     0     1
## 4     8     0     1
## 5     9     0     1
## 6    10     0     1

bladder.mod1 <- glm(n ~ x + offset(log(time)),data=bladder.dat,family=poisson(link="log"))
summary(bladder.mod1)

## 
## Call:
## glm(formula = n ~ x + offset(log(time)), family = poisson(link = "log"), 
##     data = bladder.dat)
## 
## Deviance Residuals: 
##      Min        1Q    Median        3Q       Max  
## -1.35767  -0.71501   0.03659   0.66352   2.43000  
## 
## Coefficients:
##             Estimate Std. Error z value Pr(>|z|)    
## (Intercept)  -2.3394     0.1768 -13.234   <2e-16 ***
## x             0.2292     0.3062   0.749    0.454    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for poisson family taken to be 1)
## 
##     Null deviance: 25.964  on 30  degrees of freedom
## Residual deviance: 25.419  on 29  degrees of freedom
## AIC: 100.23
## 
## Number of Fisher Scoring iterations: 5