analyseTime2Effect: Mixed effect time to event analysis

In StatCharrms: Statistical Analysis of Chemistry, Histopathology, and Reproduction Endpoints Including Repeated Measures and Multi-Generation Studies

Description

A wrapper function for the coxme function from the coxme package. Coxme is a mixed effects version of cox proportional models for comparison of time to event data taking into account censoring events.

Usage

analyseTime2Effect(Data, StatusVar, TimeVar, TreatmentVar, ReplicateVar)

Arguments

Data	A data set.
StatusVar	The name (as a string) of the status variable.
TimeVar	The name (as a string) of the time variable.
TreatmentVar	The name (as a string) of the treatment variable.
ReplicateVar	The name (as a string) of the replicate variable.

Value

Returns a list with the following values:

FitME	The results from coxme.
FitHP	The results from coxph. It is used in graphing.
FitS	The results from survfit. It is used in graphing.
EffectsTable	A dunnett table from oneWayDunnettTest.
MedianTable	A table showing the median time to effect along with the median's 95% confidence intervals. See quantile.survfit for more details.

Author(s)

Joe Swintek

References

Ripatti and J Palmgren, Estimation of multivariate frailty models using penalized partial likelihood, Biometrics 56:1016-1022, 2000.
T Therneau, P Grambsch and VS Pankratz, Penalized survival models and frailty, J Computational and Graphical Statistics 12:156-175, 2003.

See Also

coxme

Examples

	#Data 
		data(eventTimeData)
	#Run 
		analyseTime2Effect(Data=eventTimeData, StatusVar='Status', 
			TimeVar='Time', TreatmentVar='Trt', ReplicateVar='Rep')

StatCharrms documentation built on Nov. 14, 2020, 5:09 p.m.