kin.cohort: Analysis of kin-cohort data

Description

This function estimates cumulative risk at given ages for carriers and noncarriers of a mutation based on the probands genotypes. It can use the Marginal Maximum Likelihood estimation method (Chatterjee and Wacholder, 2001) or the method of moments (Wacholder et al, 2001). Bootstrap confidence intervals can be requested.

Usage

kin.cohort(..., method = c("marginal", "mml", "chatterjee",  "moments",  "km",  "watcholder"))

Arguments

...

see kc.marginal and kc.moments for details

method

choose estimation method: Marginal Maximum Likelihood (selected by "marginal", "mml", "chatterjee") or method of moments (selected by "moments", "km", "watcholder")

Details

This function is a wrapper that will call kc.marginal or kc.moments depending on the argument method.

References

Wacholder S, Hartge P, Struewing JP, Pee D, McAdams M, Lawrence B, Tucker MA. The kin-cohort study for estimating penetrance. American Journal of Epidemiology. 1998; 148: 623-9.

Chatterjee N and Wacholder S. A Marginal Likelihood Approach for Estimating Penetrance from Kin-Cohort Designs. Biometrics. 2001; 57: 245-52.

Examples

Run this code

## Not run: 
# data(kin.data)
# attach(kin.data)
# 
# res.k<-   kin.cohort(age, cancer, gen1, rel, knots=c(30,40,50,60,70,80), f=0.02, 
#                      method="km")
# res.k          
# plot(res.k)
# plot(res.k,what="crr")
# 
# set.seed(1)
# res.k.b<- kin.cohort(age, cancer, gen1, rel, knots=c(30,40,50,60,70,80), f=0.02, 
#                      set=family, method="km", B=10)
# res.k.b
# plot(res.k.b)
# plot(res.k.b,what="crr")
# 
# res.m<-   kin.cohort(age, cancer, gen1, rel, knots=c(30,40,50,60,70,80), f=0.02, 
#                     method="mml")
# res.m
# plot(res.m)
# plot(res.m, what="hr")
# 
# res.m2<-  kin.cohort(age, cancer, data.frame(gen1,gen2), rel, 
#                      knots=c(30,40,50,60,70,80), f=c(0.02,0.01), method="mml")
# res.m2
# plot(res.m2)
# plot(res.m2, what="hr")
# 
# set.seed(1)
# res.m.b<- kin.cohort(age, cancer, gen1, rel, knots=c(30,40,50,60,70,80), f=0.02, 
#                      set=family, method="mml", B=10)
# res.m.b
# plot(res.m.b)
# plot(res.m.b, what="hr")
# ## End(Not run)