NPplot: Graphic Comparison of Parametric Survival Models to...

In VZoche-Golob/AFTtools: Tools for the Data Preparation, Fitting and Diagnostics of Accelerated Failure Times Models

Description

Plots of the predicted survival of model and of corresponding non-parametric models.

Usage

NPplot(model, data)

Arguments

model	An object of class survreg.
data	The data used to fit model.

Details

predict_survreg is used internally to calculate the predicted survival for model. As non-parametric references, the Kaplan-Meier (for right censored data) and the Turnbull (for interval censored data) models are used by calling survfit. Frailties and interactions are ignored for the non-parametric predictions.

Value

One plot per predictor level (if more than one, par(mfrow = c(2, 2)) is used.)

Note

Currently only right- and interval-censored data have been tested.

References

M. Fay, P. Shaw, „Exact and Asymptotic Weighted Logrank Tests for Interval Censored Data: The interval R Package“, Journal of Statistical Software, Bd. 36, Nr. 2, S. 1-34, 2010.

K. Goethals, B. Ampe, D. Berkvens, H. Laevens, P. Janssen, und L. Duchateau, „Modeling interval-censored, clustered cow udder quarter infection times through the shared gamma frailty model“, JABES, Bd. 14, Nr. 1, S. 1–14, März 2009.

W. R. Swindell, „ACCELERATED FAILURE TIME MODELS PROVIDE A USEFUL STATISTICAL FRAMEWORK FOR AGING RESEARCH“, Exp Gerontol, Bd. 44, Nr. 3, S. 190–200, März 2009.

Examples

intS2 <- with(MIC, create_int2Surv(concentration, inhibition))
psm1 <- survival::survreg(as.formula("intS2 ~ region +
 frailty(herd, sparse = FALSE)"), data = cbind(intS2, MIC))
NPplot(psm1, cbind(intS2, MIC))

psm2 <- survival::survreg(as.formula("Surv(concentration, inhibition) ~ region +
 frailty(herd, sparse = FALSE)"), data = MIC)
NPplot(psm2, MIC)

rm(psm1, psm2, intS2)

VZoche-Golob/AFTtools documentation built on May 9, 2019, 9:42 p.m.