Gompertz Aging analysis in R

Question

I have survival data from an experiment in flies which examines rates of aging in various genotypes. The data is available to me in several layouts so the choice of which is

Answer 1

This should get you started...

Firstly, for the flexsurvreg function to work, you need to specify your input data as a Surv object (from package:survival). This means one row per observation.

The first thing is to re-create the 'raw' data from the summary tables you provide. (I know rbind is not efficient, but you can always switch to data.table for large sets).

### get rows with >1 death
df3 <- df2[df2$Deaths>1, 2:3]
### expand to give one row per death per time
df3 <- sapply(df3, FUN=function(x) rep(df3[, 2], df3[, 1]))
### each death is 1 (occurs once)
df3[, 1] <- 1
### add this to the rows with <=1 death
df3 <- rbind(df3, df2[!df2$Deaths>1, 2:3])
### convert to Surv object
library(survival)
s1 <- with(df3, Surv(Day, Deaths))
### get parameters for Gompertz distribution
library(flexsurv) 
f1 <- flexsurvreg(s1 ~ 1, dist="gompertz")

giving

> f1$res
              est         L95%        U95%
shape 0.165351912 0.1281016481 0.202602176
rate  0.001767956 0.0006902161 0.004528537

Note that this is an intercept-only model as all your genotypes are A. You can loop this over multiple survival objects once you have re-created the per-observation data as above.

From the flexsurv docs:

Gompertz distribution with shape parameter a and rate parameter b has hazard function

H(x: a, b) = b.e^{ax}

So it appears your alpha is b, the rate, and beta is a, the shape.