Probability of familial clustering of disease
To calculate probability of familial clustering of disease using Monte Carlo simulation
pfc.sim(famdata,n.sim=1000000,n.loop=1)
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 |
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 |
Yu C and D Zelterman (2001) Exact inference for family disease clusters. Commun Stat – Theory Meth 30:2293-2305
Adapted from runi.for from Change Yu, 5/6/4
Chang Yu, Dani Zelterman
## 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)
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