pfc.sim {gap}R Documentation

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 a copy of the total number of Monte Carlo runs
p the observed p value
tailpl probabilities at the lower tails
tailpu probabilities at the upper tails

References

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

Note

Adapted from runi.for from Change Yu, 5/6/4

Author(s)

Chang Yu, Dani Zelterman

See Also

pfc

Examples

## Not run: 

# Li, Fraumeni, Mulvihill, et al., 1988
# 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)

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