forsearch_cph {forsearch}

Create Statistics Of Forward Search in a Cox Proportional Hazard Database

Description

Prepares summary statistics at each stage of forward search for subsequent plotting.

Usage

forsearch_cph(alldata, formula.rhs, initial.sample=1000, 
        n.obs.per.level=1, skip.step1=NULL, ties = "efron", proportion=TRUE, 
        unblinded=TRUE, begin.diagnose= 100, verbose=TRUE)

Arguments

alldata

Data frame containing variables 'Observation', 'event.time', 'status', and independent variables, in that order

formula.rhs

Character vector of names of independent variables in model

initial.sample

Number of observations in Step 1 of forward search

n.obs.per.level

Number of observations per level of (possibly crossed) factor levels to include in Step 1

skip.step1

NULL or a vector of integers for observations to be included in Step 1

ties

Method for handling ties in event time; = "efron", "breslow", or "exact"; see survival::coxph

proportion

TRUE causes evaluation of proportionality of Cox regression

unblinded

TRUE causes printing of presumed analysis structure

begin.diagnose

Numeric. Indicates where in code to begin printing diagnostics. 0 prints all; 100 prints none

verbose

TRUE causes function identifier display before and after run

Value

LIST

Rows in stage

Observation numbers of rows included at each stage

Number of model parameters

Number of fixed coefficients in Cox model

Fixed parameter estimates

Vector of parameter estimates at each stage

Wald Test

Vector of Wald tests at each stage

LogLikelihood

Vector of null and overall coefficients log likelihoods at each stage

Likelihood ratio test

Vector of LRTs at each stage

Leverage

Matrix of leverage of each observation at each stage

Call

Call to this function

Author(s)

William R. Fairweather

References

Atkinson, A and M Riani. Robust Diagnostic Regression Analysis, Springer, New York, 2000.

Examples

## Not run: 
{# Forsearch for Cox Proportional Survival, including Step 1
veteran <- survival::veteran
veteran <- veteran[order(veteran$celltype),]
veteranx <- veteran[,c(3,4,1,2)]
veteranx$trt <- as.factor(veteranx$trt)
dimv <- dim(veteran)[1]
Observation <- 1:dimv
veteranx <- data.frame(Observation,veteranx)
names(veteranx)[2] <- "event.time"
form.1 <- "trt + celltype"  
forskip <- NULL
# forskip <- c(12,  23,  38,  71,  91, 104, 116, 130,  31,  73,  62,  76)
cphtest1a.out <- forsearch_cph(alldata=veteranx, formula.rhs=form.1, 
       n.obs.per.level=2, skip.step1=forskip, ties="efron", unblinded=TRUE, 
       initial.sample=467, begin.diagnose = 100, verbose = TRUE)
}
{# Same, but skipping Step 1.
forskip <- c(12,  23,  38,  71,  91, 104, 116, 130,  31,  73,  62,  76)
cphtest1b.out <- forsearch_cph(alldata=veteranx, formula.rhs=form.1, 
      n.obs.per.level=2, skip.step1=forskip, ties="efron", unblinded=TRUE, 
      initial.sample=467, begin.diagnose = 100, verbose = TRUE) 
}

## End(Not run)