Survival times, in days, of 50 female black ducks captured and fitted with radios (Collett, 2023, Appendix B.3).
Format
A data frame with 50 rows and 6 variables:
- duck
Duck number (1-50).
- time
Survival time in days.
- status
Event indicator: 1 = dead, 0 = alive or missing.
- age
Age group: 0 = hatch-year bird, 1 = bird aged at least one year.
- weight
Body weight in g.
- length
Wing length in mm.
Source
Collett, D. (2023) Modelling Survival Data in Medical Research, 4th ed. Chapman & Hall/CRC, Appendix B.3 (Table B.3). Data from Hand et al. (1994); the study was conducted by the US Fish and Wildlife Service.
Details
Fifty female ducks from two locations in New Jersey were captured between 8 November and 14 December 1983 and their status was recorded daily until the study ended on 15 February 1984; there are 18 deaths. The data are included in Hand et al. (1994).
The appendix suggests a proportional hazards model for age, weight and length, a test of whether the coefficients of weight and length differ between age groups, and an assessment of whether non-linear functions of weight and length are needed.
Aliases
This data set is not used in a numbered example, so it has no dX.Y alias.
See dataset_by_exercise for the complete index.
Examples
# Collett (2023), Appendix B.3 (no numbered example) ------------------
# Chapter 17 style: proportional hazards model for age, weight and length
survival::coxph(
survival::Surv(time, status) ~ age + weight + length,
data = ducks
)
#> Call:
#> survival::coxph(formula = survival::Surv(time, status) ~ age +
#> weight + length, data = ducks)
#>
#> coef exp(coef) se(coef) z p
#> age 0.463263 1.589251 0.578130 0.801 0.423
#> weight -0.004197 0.995812 0.002892 -1.451 0.147
#> length 0.012487 1.012566 0.040875 0.306 0.760
#>
#> Likelihood ratio test=2.2 on 3 df, p=0.5324
#> n= 50, number of events= 18
# Modern tools --------------------------------------------------------
if (requireNamespace("broom", quietly = TRUE)) {
broom::tidy(
survival::coxph(survival::Surv(time, status) ~ age + weight + length, data = ducks),
exponentiate = TRUE, conf.int = TRUE
)
}
#> # A tibble: 3 × 7
#> term estimate std.error statistic p.value conf.low conf.high
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 age 1.59 0.578 0.801 0.423 0.512 4.94
#> 2 weight 0.996 0.00289 -1.45 0.147 0.990 1.00
#> 3 length 1.01 0.0409 0.306 0.760 0.935 1.10