| pfc.sim {gap} | R Documentation |
Probability of familial clustering of disease
Description
Probability of familial clustering of disease
Usage
pfc.sim(famdata, n.sim = 1e+06, 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. |
Details
To calculate probability of familial clustering of disease using Monte Carlo simulation.
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.
Note
Adapted from runi.for from Change Yu, 5/6/4
Author(s)
Chang Yu, Dani Zelterman
References
Yu C, Zelterman D (2001). “Exact inference for family disease clusters.” Communications in Statistics - Theory and Methods, 30(11), 2293-2305. ISSN 0361-0926, doi:10.1081/STA-100107686.
See Also
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)