Pst: Computation of P(s,t)

Description Usage Arguments Details Value Note Author(s) References See Also Examples

Description

This function calculates the transition probability matrix between any two values s and t and then prints it. The function also calculates and prints the cov(P(s,t)) matrix if the user specifies. Values are returned invisibly.

Usage

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Pst(object, s=0, t="last", deci=4, covar=FALSE)

Arguments

object

An msSurv object.

s

The lower time. Default is 0.

t

The highter time. Default is "last" which is the highest (or "last") event time.

deci

Numeric argument specifying number of decimal places for estimates. Default is 4.

covar

Logical argument to determine if var(P(s,t)) is computed. Default is FALSE.

Details

Computation of P(s,t) and var(P(s,t)) for multistate models are described in Andersen et al. (1993).

Value

Returned invisibly:

Pst

The transition probability matrix between two times s and t.

cov.Pst

Covariance matrix for the transition probability matrix between two times s and t (if covar==TRUE).

Note

If s = 0 and all subjects begin in the initial state at time 0, then the top row of P(0,t) yields the state occupation probabilities at time t. Data are assumed to follow a Markovian model.

Author(s)

Nicole Ferguson <nicole.ferguson@kennesaw.edu>, Guy Brock <guy.brock@louisville.edu>, Somnath Datta <somnath.datta@louisville.edu>

References

Nicole Ferguson, Somnath Datta, Guy Brock (2012). msSurv: An R Package for Nonparametric Estimation of Multistate Models. Journal of Statistical Software, 50(14), 1-24. URL http://www.jstatsoft.org/v50/i14/.

Andersen, P.K., Borgan, O., Gill, R.D. and Keiding, N. (1993). Statistical models based on counting processes. Springer Series in Statistics. New York, NY: Springer.

See Also

msSurv

Examples

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## Row elements of data 
p1 <- c(1,0,0.21,1,3)
p2 <- c(2,0,0.799,1,2)
p22 <- c(2,0.799,1.577,2,3)
p3 <- c(3,0,0.199,1,0)

## Combining data into a matrix
ex1 <- rbind(p1,p2,p22,p3)
colnames(ex1) <- c("id", "start", "stop", "start.stage", "end.stage")
ex1 <- data.frame(id=ex1[,1], start=ex1[,2], stop=ex1[,3],
                  start.stage=ex1[,4], end.stage=ex1[,5])


## Inputting nodes & edges of the tree structure
Nodes <- c("1","2","3") # states in MSM
Edges <- list("1"=list(edges=c("2","3")),"2"=list(edges=c("3")),
           "3"=list(edges=NULL)) ## allowed transitions between states
                                 ## edges=NULL implies terminal node

## Specifying tree
treeobj <- new("graphNEL", nodes=Nodes, edgeL=Edges,
                edgemode="directed")

## Running msSurv
ans1 <- msSurv(ex1,treeobj)
Pst(ans1, s=0.25, t=2.5)

msSurv documentation built on May 1, 2019, 7:31 p.m.