# doubleFGR: Double CIF Fine-Gray model with two causes In mets: Analysis of Multivariate Event Times

## Description

Estimation based on derived hazards and recursive estimating equations. fits two parametrizations 1)

F_1(t,X) = 1 - \exp( \exp( X^T β ) Λ_1(t))

and

F_2(t,X_2) = 1 - \exp( \exp( X_2^T β_2 ) Λ_2(t))

or restricted version 2)

F_1(t,X) = 1 - \exp( \exp( X^T β ) Λ_1(t))

and

F_2(t,X_2,X) = ( 1 - \exp( \exp( X_2^T β_2 ) Λ_2(t)) ) (1 - F_1(∞,X))

## Usage

 `1` ```doubleFGR(formula, data, offset = NULL, weights = NULL, X2 = NULL, ...) ```

## Arguments

 `formula` formula with 'Event' `data` data frame `offset` offsets for cox model `weights` weights for Cox score equations `X2` specifies the regression design for second CIF model `...` Additional arguments to lower level funtions

Thomas Scheike

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99``` ```res <- 0 data(bmt) bmt\$age2 <- bmt\$age newdata <- bmt[1:19,] if (interactive()) par(mfrow=c(5,3)) ## same X1 and X2 pr2 <- doubleFGR(Event(time,cause)~age+platelet,data=bmt,restrict=res) if (interactive()) { bplotdFG(pr2,cause=1) bplotdFG(pr2,cause=2,add=TRUE) } pp21 <- predictdFG(pr2,newdata=newdata) pp22 <- predictdFG(pr2,newdata=newdata,cause=2) if (interactive()) { plot(pp21) plot(pp22,add=TRUE,col=2) } pp21 <- predictdFG(pr2) pp22 <- predictdFG(pr2,cause=2) if (interactive()) { plot(pp21) plot(pp22,add=TRUE,col=2) } pr2 <- doubleFGR(Event(time,cause)~strata(platelet),data=bmt,restrict=res) if (interactive()) { bplotdFG(pr2,cause=1) bplotdFG(pr2,cause=2,add=TRUE) } pp21 <- predictdFG(pr2,newdata=newdata) pp22 <- predictdFG(pr2,,newdata=newdata,cause=2) if (interactive()) { plot(pp21) plot(pp22,add=TRUE,col=2) } pp21 <- predictdFG(pr2) pp22 <- predictdFG(pr2,cause=2) if (interactive()) { plot(pp21) plot(pp22,add=TRUE,col=2) } ## different X1 and X2 pr2 <- doubleFGR(Event(time,cause)~age+platelet+age2,data=bmt,X2=3,restrict=res) if (interactive()) { bplotdFG(pr2,cause=1) bplotdFG(pr2,cause=2,add=TRUE) } pp21 <- predictdFG(pr2,newdata=newdata) pp22 <- predictdFG(pr2,newdata=newdata,cause=2) if (interactive()) { plot(pp21) plot(pp22,add=TRUE,col=2) } pp21 <- predictdFG(pr2) pp22 <- predictdFG(pr2,cause=2) if (interactive()) { plot(pp21) plot(pp22,add=TRUE,col=2) } ### uden X1 pr2 <- doubleFGR(Event(time,cause)~age+platelet,data=bmt,X2=1:2,restrict=res) if (interactive()) { bplotdFG(pr2,cause=1) bplotdFG(pr2,cause=2,add=TRUE) } pp21 <- predictdFG(pr2,newdata=newdata) pp22 <- predictdFG(pr2,newdata=newdata,cause=2) if (interactive()) { plot(pp21) plot(pp22,add=TRUE,col=2) } pp21 <- predictdFG(pr2) p22 <- predictdFG(pr2,cause=2) if (interactive()) { plot(pp21) plot(pp22,add=TRUE,col=2) } ### without X2 pr2 <- doubleFGR(Event(time,cause)~age+platelet,data=bmt,X2=0,restrict=res) if (interactive()) { bplotdFG(pr2,cause=1) bplotdFG(pr2,cause=2,add=TRUE) } pp21 <- predictdFG(pr2,newdata=newdata) pp22 <- predictdFG(pr2,newdata=newdata,cause=2) if (interactive()) { plot(pp21) plot(pp22,add=TRUE,col=2) } pp21 <- predictdFG(pr2) pp22 <- predictdFG(pr2,cause=2) if (interactive()) { plot(pp21) plot(pp22,add=TRUE,col=2) } ```

mets documentation built on Oct. 23, 2020, 5:55 p.m.