Nothing
## incidence ratio test as defined by Kerber 1995
data(minnbreast)
mbsub <- minnbreast[minnbreast$famid %in% 4:19, ]
PedDf <- mbsub[, c("famid", "id", "fatherid", "motherid", "sex")]
colnames(PedDf) <- FamAgg:::.PEDCN
PedDf$sex <- FamAgg:::sanitizeSex(PedDf$sex)
## generate the FAData.
fad <- FAData(pedigree=PedDf)
## specify the trait.
tcancer <- mbsub$cancer
names(tcancer) <- mbsub$id
## the time at risk...
tar <- mbsub$endage
test_incidence_ratio <- function(){
fr <- FamAgg:::.FR(ped=pedigree(fad), kin=kinship(fad), trait=tcancer,
timeAtRisk=tar)
## the same but per family
frFam <- FamAgg:::.FR(ped=pedigree(fad), kin=kinship(fad), trait=tcancer,
timeAtRisk=tar, perFamilyTest=TRUE)
fr3 <- familialIncidenceRate(fad, trait=tcancer, timeAtRisk=tar)
checkEquals(fr[[1]], fr3)
## The argument rm.singletons has been removed, so no need for the test below.
## Using the method: check if rm.singletons has an effect.
## fr <- familialIncidenceRate(fad, trait=tcancer, timeAtRisk=tar, rm.singletons=FALSE)
## fr2 <- familialIncidenceRate(fad, trait=tcancer, timeAtRisk=tar, rm.singletons=TRUE)
## checkEquals(sum(fr, na.rm=TRUE)==sum(fr2, na.rm=TRUE), TRUE)
## Note: we're getting the same results here as we are summing kinship coefs. singletons have
## a kinship of 0 with any other, thus they don't add to the value anyway.
## So, it's not the same if we run this within family or for the whole pedigree...
## frVals <- unlist(fr, use.names=FALSE)
## frFamVals <- unlist(frFam, use.names=FALSE)
## checkEquals(frVals[!is.na(frVals)], frFamVals[!is.na(frFamVals)])
## checkEquals(unlist(fr, use.names=FALSE), unlist(frFam, use.names=FALSE))
## fr[[1]][1:10]
## frFam[["4"]]
}
test_estimate_time_at_risk <- function(){
sdates <- c("2012-04-17", "2014-05-29", "1999-12-31", "2002-10-10")
edates <- c("2015-09-15", "2015-09-15", "2005-09-15", "2015-09-15")
idates <- c(NA, NA, "2007-07-13", "2013-12-23")
ddates <- c(NA, NA, NA, "2014-03-14")
checkException(estimateTimeAtRisk(sdates))
ests <- estimateTimeAtRisk(startDate=sdates, endDate=edates)
ests2 <- estimateTimeAtRisk(startDate=sdates, endDate=edates,
incidenceDate=idates)
ests3 <- estimateTimeAtRisk(startDate=sdates, endDate=edates,
incidenceDate=idates, deathDate=ddates)
}
test_fr_simulation <- function(){
doPlot <- FALSE
fr <- FamAgg:::.FR(ped=pedigree(fad), kin=kinship(fad), trait=tcancer,
timeAtRisk=tar)
fr <- fr[[1]]
fr2 <- familialIncidenceRate(fad, trait=tcancer,
timeAtRisk=tar)
checkEquals(fr, fr2[names(fr)])
## Use the familialIncidenceRateTest
set.seed(18011977)
Test <- FamAgg:::.FRSimulation(ped=pedigree(fad), kin=kinship(fad), trait=tcancer,
timeAtRisk=tar, prune=TRUE, nsim=1000)
set.seed(18011977)
frRes <- familialIncidenceRateTest(fad, trait=tcancer,
timeAtRisk=tar, nsim=1000)
checkEquals(frRes@sim$fir, fr2)
## Do the simulation using dummy strata.
set.seed(18011977)
frStrat <- familialIncidenceRateTest(fad, trait=tcancer,
timeAtRisk=tar, nsim=1000,
strata=rep(1, length(fad$id)))
checkEquals(frRes@sim$fir, frStrat@sim$fir)
checkEquals(frRes@sim$pvalue, frStrat@sim$pvalue)
## Repeat using the low mem version.
set.seed(18011977)
frLM <- familialIncidenceRateTest(fad, trait=tcancer,
timeAtRisk=tar, nsim=1000,
lowMem=TRUE)
checkEquals(frRes@sim$fir, frLM@sim$fir)
checkEquals(frRes@sim$pvalue, frLM@sim$pvalue)
##
## plotting...
if(doPlot){
res <- result(frRes)
plotPed(frRes, id="4")
plotPed(frRes, family=19)
plotPed(frRes, id=res[1, "id"])
## plotRes.
plotRes(frRes, id="4")
plotRes(frRes, id=res[1, "id"])
}
## Testing the $ accessors.
checkEquals(frRes$fir, frRes@sim$fir)
checkEquals(frRes$tar, FamAgg:::timeAtRisk(frRes))
## Testing with and without rm.singletons.
fr <- familialIncidenceRateTest(fad, trait=tcancer, nsim=400,
timeAtRisk=tar, rm.singletons=TRUE)
fr2 <- familialIncidenceRateTest(fad, trait=tcancer, nsim=400,
timeAtRisk=tar, rm.singletons=FALSE)
checkEquals(fr$fir, fr2$fir)
}
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