gap (version 1.1-16)

pfc.sim: Probability of familial clustering of disease

Description

To calculate probability of familial clustering of disease using Monte Carlo simulation

Usage

pfc.sim(famdata,n.sim=1000000,n.loop=1)

Arguments

famdata

collective information of sib size, number of affected sibs and their frequencies

n.sim

number of simulations in a single Monte Carlo run

n.loop

total number of Monte Carlo runs

Value

The returned value is a list containing:

n.sim

a copy of the number of simulations in a single Monte Carlo run

n.loop

the total number of Monte Carlo runs

p

the observed p value

tailpl

accumulated probabilities at the lower tails

tailpu

simulated p values

References

Yu C and D Zelterman (2001) Exact inference for family disease clusters. Commun Stat -- Theory Meth 30:2293-2305

See Also

pfc

Examples

## Not run: 
# # Li FP, Fraumeni JF Jr, Mulvihill JJ, Blattner WA, Dreyfus MG, Tucker MA,
# # Miller RW. A cancer family syndrome in twenty-four kindreds.
# # Cancer Res 1988, 48(18):5358-62. 
# 
# # family_size  #_of_affected frequency
# 
# famtest<-c(
# 1, 0, 2,
# 1, 1, 0,
# 2, 0, 1,
# 2, 1, 4,
# 2, 2, 3,
# 3, 0, 0,
# 3, 1, 2,
# 3, 2, 1,
# 3, 3, 1,
# 4, 0, 0,
# 4, 1, 2,
# 5, 0, 0,
# 5, 1, 1,
# 6, 0, 0,
# 6, 1, 1,
# 7, 0, 0,
# 7, 1, 1,
# 8, 0, 0,
# 8, 1, 1,
# 8, 2, 1,
# 8, 3, 1,
# 9, 3, 1)
# 
# test<-matrix(famtest,byrow=T,ncol=3)
# 
# famp<-pfc.sim(test)
# ## End(Not run)