fit_pwexp | R Documentation |

Computes survival function, density function, -2*log-likelihood based on input dataset and intervals for piecewise constant failure rates. Initial version assumes observations are right censored or events only.

```
fit_pwexp(
srv = Surv(time = Ex1delayedEffect$month, event = Ex1delayedEffect$evntd),
intervals = array(3, 3)
)
```

`srv` |
input survival object (see |

`intervals` |
Vector containing positive values indicating interval lengths where the exponential rates are assumed. Note that a final infinite interval is added if any events occur after the final interval specified. |

A matrix with rows containing interval length, estimated rate, -2*log-likelihood for each interval.

```
# use default arguments for delayed effect example dataset (Ex1delayedEffect)
library(survival)
# example 1
rateall <- fit_pwexp()
rateall
# example 2
# Estimate by treatment effect
rate1 <- with(subset(Ex1delayedEffect, trt == 1), fit_pwexp(Surv(month, evntd)))
rate0 <- with(subset(Ex1delayedEffect, trt == 0), fit_pwexp(Surv(month, evntd)))
rate1
rate0
rate1$rate/rate0$rate
# chi-square test for (any) treatment effect (8 - 4 parameters = 4 df)
pchisq(sum(rateall$m2ll) - sum(rate1$m2ll + rate0$m2ll),
df = 4,
lower.tail = FALSE)
# compare with logrank
survdiff(formula = Surv(month, evntd) ~ trt, data = Ex1delayedEffect)
# example 3
# simple model with 3 rates same for each for 3 months,
# different for each treatment after months
rate1a <- with(subset(Ex1delayedEffect, trt == 1), fit_pwexp(Surv(month, evntd), 3))
rate0a <- with(subset(Ex1delayedEffect, trt == 0), fit_pwexp(Surv(month, evntd), 3))
rate1a$rate/rate0a$rate
m2ll0 <- rateall$m2ll[1] + rate1a$m2ll[2] + rate0a$m2ll[2]
m2ll1 <- sum(rate0$m2ll) + sum(rate1$m2ll)
# as a measure of strength, chi-square examines improvement in likelihood
pchisq(m2ll0-m2ll1, df = 5, lower.tail=FALSE)
```

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