powerSim(m)
#> Power for predictor 'cyl', (95% confidence interval):
#> 0.00% ( 0.00, 0.37)
#>
#> Test: t-test
#>
#> Based on 1000 simulations, (0 warnings, 1000 errors)
#> alpha = 0.05, nrow = 28
#>
#> Time elapsed: 0 h 0 m 1 s
#>
#> nb: result might be an observed power calculation
powerCurve’s does not:
(pc <- powerCurve(m))
#> Power for predictor 'cyl', (95% confidence interval),
#> by largest value of cyl:
#> 8: 0.00% ( 0.00, 0.37) - 28 rows
#>
#> Time elapsed: 0 h 0 m 1 s
# nor
summary(pc)
#> nrow nlevels successes trials mean lower upper
#> 1 28 3 0 1000 0 0 0.003682084
powerCurve
output does not indicate errors, which makes debugging scripts usingsimr
difficult - 100% errors are displayed as 0.00 power.(Make some missing data to recreate the same error in #204 )
While
powerSim
’s printing indicates errors:powerCurve
’s does not: