standardizeRisks: Estimate standardized mortality risks

Description Usage Arguments Value References Examples

Description

Estimate standardized mortality risks

Usage

1
2
3
standardizeRisks(patientCovariates, center, Y, method = c("indirect",
  "direct"), Firth = TRUE, alpha = 0.05, missing = c("completeCase",
  "dummyCategory"), trace = FALSE)

Arguments

patientCovariates

data frame of patient-specific covariates

center

center code (n values for n patients)

Y

binary outcome

method

method of standardization; one of 'indirect' (default) or 'direct'

Firth

logical apply Firth correction? default value TRUE

alpha

statistical significance level; default value is 0.05

missing

how to handle missing categorical data? one of 'completeCase' (default) or 'dummyCategory'; when 'dummyCategory' is chosen a separate category is added to model a missing value effect

trace

logical print summary of fitted model? default value FALSE

Value

object of class 'standardizedRisks'; data frame with columns centerName, centerSize, standardizedRisk, varStandardizedRisk, lowerCI, upperCI and observedRisk

References

Varewyck M., Goetghebeur E., Eriksson M. and Vansteelandt S. (2014), On shrinkage and model extrapolation in the evaluation of clinical center performance, Biostatistics, 15(4), p. 651–664

Examples

1
2
3
4
set.seed(130513)
simulatedData <- simulateData()
standardizedRisks <- with(simulatedData, standardizeRisks(patientCovariates = L, center = center, Y = Y))
head(standardizedRisks)

StatGent/RiskStandard documentation built on May 9, 2019, 1:57 p.m.