gap (version 1.2.2)

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)
# }