Description Usage Arguments Details Value Note References Examples
Plots of the predicted survival of model
and of corresponding non-parametric
models.
1 |
model |
An object of class |
data |
The data used to fit |
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.
One plot per predictor level (if more than one,
par(mfrow = c(2, 2))
is used.)
Currently only right- and interval-censored data have been tested.
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.
1 2 3 4 5 6 7 8 9 10 | 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)
|
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