gap (version 1.6)

pfc.sim: Probability of familial clustering of disease

Description

Probability of familial clustering of disease

Usage

pfc.sim(famdata, n.sim = 1e+06, n.loop = 1)

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.

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.

Author

Chang Yu, Dani Zelterman

Details

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

References

yu01gap

See Also

pfc

Examples

if (FALSE) {
# 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)
}