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getDF<-function(seerSet,srs=NULL) {
age=trt=race=surv=year=py=popsa=cancer1=nO=O=E=ageE=ageEci=ageO=int=sig2O=ageOci=ageG=NULL
if (is.null(seerSet$L)) stop("seerSet L field is empty. Please run tsd on your seerSet object!") else {
nms=names(seerSet$L)
indx=seerSet$active
cat("Current active series:",indx,"\n",sep="")
print(seerSet$series)
if (is.null(srs)) {indx=seerSet$active #grab most recent
cat(paste0("Using (active) series ",indx,", i.e. ", nms[indx],".\n"))
# cat(paste0("Using active time series in L. Index:",indx,"\n"))
}
if (length(srs)>1) {
cat("... collapsing brks vector to a single string.\n")
srs=paste0("b",paste(srs,collapse="_"))
}
if (is.character(srs)){ indx=srs #grab ith most recent
cat(paste0("Using series ",which(indx==nms),", i.e. ", indx,".\n"))
}
if (is.numeric(srs)){ indx=srs #grab ith most recent
cat("Using series ",indx,", i.e. ", nms[indx],".\n",sep="")
}
L=seerSet$L[[indx]]
}
secondS=seerSet$secondS
firstS=L$firstS
# options(stringsAsFactors=FALSE)
f=data.frame(cancer1=firstS)
fs=merge(f,data.frame(cancer2=secondS))%>%arrange(cancer1)
funfs=function(x,by){
y=left_join(fs,x,by=by)
y[is.na(y[,"n"]),"n"]=0
y
}
funOE=function(x,by,out="O"){
x=melt(x)
names(x)=c("cancer1","cancer2",out)
left_join(fs,x,by=by)
}
trts=L$trtS
ao=NULL
pya=NULL
o=NULL
e=NULL
options(warn=-1)
for (i in trts){
yrGrp=names(L[[i]])
for (j in yrGrp) {
ageGrp=names(L[[i]][[j]])
for (k in ageGrp) {
pya=rbind(pya,cbind(ldply(lapply(L[[i]][[j]][[k]]$PYA,funfs,by=c("cancer1"))),trt=i,yearG=j,ageG=k))
ao=rbind(ao,cbind(ldply(lapply(L[[i]][[j]][[k]]$AgeO,funfs,by=c("cancer1","cancer2"))),trt=i))
o=rbind(o,cbind(ldply(lapply(L[[i]][[j]][[k]]$O,funOE,by=c("cancer1","cancer2"),out="O")),trt=i))
e=rbind(e,cbind(ldply(lapply(L[[i]][[j]][[k]]$E,funOE,by=c("cancer1","cancer2"),out="E")),trt=i))
}
}
}
options(warn=0)
names(ao)[4:5]=c("ageO","sig2O")
names(pya)[1]=c("int")
d=cbind(pya%>%select(int:ageG),ao%>%select(ageO:sig2O))
d=cbind(d,O=o$O,E=e$E)
d$int=factor(d$int,levels=unique(d$int))
d=d%>%mutate(RR=O/E,
rrL=qchisq(.025,2*O)/(2*E),
rrU=qchisq(.975,2*O+2)/(2*E))
sem=sqrt(d$sig2/d$n)
options(warn=-1) # expect warnings on t df of 0 and -1
ci95=qt(0.975,d$n-1)*sem
d$aeL=d$age-ci95
d$aeU=d$age+ci95
sem=sqrt(d$sig2O/d$O)
ci95=qt(0.975,d$O-1)*sem
options(warn=0) # turn off expect warnings on t df of 0 and -1
d$aoL=d$ageO-ci95
d$aoU=d$ageO+ci95
i=sapply(d,is.numeric)
d[i]=round(d[i],3)
d=tbl_df(d)
# print(glimpse(d))
d
}
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