Times to loss of equilibrium of 120 juvenile salmonids held at three constant temperatures, simulated from a known model so that what a fitted model estimates can be set against the values the data were made from. Twelve trials of ten fish, four at each temperature (23, 25 and 27 degrees C), were checked every hour for five days, so each failure is known to have happened between two checks. Fish that had not failed by the end of the fifth day are survivors. The coolest temperature is one a summer heat wave can reach, so that the assay informs predictions for the field (see stream_record).
Format
A tibble with 120 rows, one per fish, and 7 columns:
- id
Integer, the fish.
- trial
Character, the trial the fish was in (
"S01"to"S12").- path_id
Character, the temperature group (
"T23","T25","T27"), the key to its temperature trajectory.- temp
Numeric, the constant temperature of the trial, degrees C.
- mass
Numeric, body mass, g.
- event
Integer, 1 if the fish lost equilibrium, 0 if it survived to the end of the trial.
- t_upper
Numeric, the time of the check at which the fish was found to have failed, or of the last check for a survivor, minutes.
Details
The data are simulated, not measured. The values are plausible for a juvenile
rainbow trout acclimated to 14 degrees C, and stand for no particular study. The
model they come from is described under ramp_assay, which shares it, and is
stored with the data as attr(static_assay, "truth").
Examples
head(static_assay)
#> # A tibble: 6 × 7
#> id trial path_id temp mass event t_upper
#> <int> <chr> <chr> <dbl> <dbl> <int> <dbl>
#> 1 1 S01 T23 23 19.9 0 7200
#> 2 2 S01 T23 23 14.3 0 7200
#> 3 3 S01 T23 23 8 0 7200
#> 4 4 S01 T23 23 16.6 1 2040
#> 5 5 S01 T23 23 29.5 1 2400
#> 6 6 S01 T23 23 9 1 5820
# The temperature trajectory of each group, and the checks.
path <- data.frame(path_id = rep(c("T23", "T25", "T27"), each = 2),
time = rep(c(0, 7200), 3),
temp = rep(c(23, 25, 27), each = 2))
checks <- expand.grid(path_id = c("T23", "T25", "T27"),
time = seq(0, 7200, by = 60))
long <- build_hazard_data(static_assay, path, "interval",
covariates = c("mass", "trial"), checks = checks)
head(long)
#> # A tibble: 6 × 12
#> id mass trial path_id tau exposure Ta failed Tr log_tau tau_ref
#> <int> <dbl> <chr> <chr> <dbl> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
#> 1 1 19.9 S01 T23 30 60 23 0 25 3.40 360
#> 2 1 19.9 S01 T23 90 60 23 0 25 4.50 360
#> 3 1 19.9 S01 T23 150 60 23 0 25 5.01 360
#> 4 1 19.9 S01 T23 210 60 23 0 25 5.35 360
#> 5 1 19.9 S01 T23 270 60 23 0 25 5.60 360
#> 6 1 19.9 S01 T23 330 60 23 0 25 5.80 360
#> # ℹ 1 more variable: log_exposure <dbl>