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gap (version 1.1-1)

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):
  • pthe probabitly of familial clustering
  • statthe deviances, chi-squares based on binomial and hypergeometric distributions, the degrees of freedom should take into account the number of marginals used
  • tailpthe exact statistical significance
  • sumpsum of the probabilities used for error checking
  • nenumthe total number of tables enumerated

References

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

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

See Also

kin.morgan

Examples

Run this code
# IPF among 203 siblings of 100 COPD patients from Liang KY, SL Zeger, B Qaquish (1992)
# Multivariate regression analyses for categorical data (with discussion). J Roy Stat Soc
# B 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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