Analysis of kin-cohort data

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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

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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.

Author(s)

Victor Moreno, Nilanjan Chatterjee, Bhramar Mukherjee.

Maintainer: Victor Moreno <v.moreno@iconcologia.net>

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.

See Also

kc.marginal, kc.moments

Examples

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## 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)