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gap (version 1.1-20)

pfc: Probability of familial clustering of disease

Description

To calculate exact probability of familial clustering of disease

Usage

pfc(famdata,enum)

Arguments

famdata

collective information of sib size, number of affected sibs and their frequencies

enum

a switch taking value 1 if all possible tables are to be enumerated

Value

The returned value is a list containing (tailp,sump,nenum are only available if enum=1):

p

the probabitly of familial clustering

stat

the deviances, chi-squares based on binomial and hypergeometric distributions, the degrees of freedom should take into account the number of marginals used

tailp

the exact statistical significance

sump

sum of the probabilities used for error checking

nenum

the total number of tables enumerated

References

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

Yu C, Zelterman D (2002) Statistical inference for familial disease clusters. Biometrics 58:481-491

See Also

kin.morgan

Examples

Run this code
# NOT RUN {
# IPF among 203 siblings of 100 COPD patients from Liang KY, SL Zeger,
# Qaquish B. Multivariate regression analyses for categorical data
# (with discussion). J Roy Stat Soc B 1992, 54:3-40

# the degrees of freedom is 15
famtest<-c(
1, 0, 36,
1, 1, 12,
2, 0, 15,
2, 1,  7,
2, 2,  1,
3, 0,  5,
3, 1,  7,
3, 2,  3,
3, 3,  2,
4, 0,  3,
4, 1,  3,
4, 2,  1,
6, 0,  1,
6, 2,  1,
6, 3,  1,
6, 4,  1,
6, 6,  1)
test<-t(matrix(famtest,nrow=3))
famp<-pfc(test)
# }

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