Remission times (in months) for 128 bladder cancer patients. This is a complete (uncensored) sample widely used in lifetime distribution literature to demonstrate decreasing or right-skewed hazard rates.
Format
A data frame with 128 rows and 2 columns:
- time
Remission time in months
- status
Event indicator (1 = event occurred)
Source
Lee, E. T., & Wang, J. W. (2003). Statistical Methods for Survival Data Analysis (3rd ed.). Wiley.
Examples
data(remission)
# \donttest{
fit <- fit_betadanish(survival::Surv(time, status) ~ 1, data = remission)
#> Warning: The times look recorded on a grid of 0.01. The point-density likelihood treats them as exact, which understates the standard errors. Consider grouped = TRUE.
#> Warning: The fitted correlation between a-hat and c-hat is -0.987, so effectively only the product c*a is identified. Individual estimates of a and c should not be interpreted.
#> Warning: 2 starting point(s) reached a degenerate ridge and were discarded. The reported fit is the best admissible optimum. If this is most of the grid, the four-parameter model is a poor choice for these data.
summary(fit)
#>
#> Call:
#> fit_betadanish(formula = survival::Surv(time, status) ~ 1, data = remission)
#>
#> Beta-Danish Distribution Fit
#> Model: Full 4-Parameter Model
#>
#> Estimate Std. Error Lower 95% Upper 95% z value Pr(>|z|)
#> a 0.686571 0.787152 -0.856248 2.229389 0.8722 0.38309
#> b 4.078176 1.481508 1.174420 6.981932 2.7527 0.00591 **
#> c 2.196539 2.552985 -2.807311 7.200389 0.8604 0.38958
#> k 0.082975 0.076454 -0.066875 0.232824 1.0853 0.27779
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> ---
#> Log-Likelihood: -409.9137
#> AIC: 827.8274 | BIC: 839.2356
# }