estimate sample sizes
lfq_power_t_test_quantiles_V2(
quantile_sd,
delta = c(0.59, 1, 2),
power = 0.8,
sig.level = 0.05,
min.n = 1.5
)
output of `summarize_stats_quantiles`
effect size you are interested in
of test
smallest n to determine
P-Value
bb1 <- prolfqua::sim_lfq_data_peptide_config()
#> creating sampleName from fileName column
#> Warning: no nr_children column specified in the data, adding column nr_children and setting to 1.
#> completing cases
config <- bb1$config
data2 <- bb1$data
stats_res <- summarize_stats(data2, config)
#> [1] "group_"
#> completing cases
xx <- summarize_stats_quantiles(stats_res, config, probs = c(0.5,0.8))
bbb <- lfq_power_t_test_quantiles_V2(xx$long)
bbb <- dplyr::bind_rows(bbb)
summary <- bbb |>
dplyr::select( -N_exact, -quantiles, -sdtrimmed ) |>
tidyr::spread(delta, N, sep = "=")