estimate sample sizes

estimate sample sizes

Usage

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
)

Arguments

quantile_sd

output of `summarize_stats_quantiles`

delta

effect size you are interested in

power

of test

sig.level

P-Value

min.n

smallest n to determine

See also

Other stats: INTERNAL_FUNCTIONS_BY_FAMILY, lfq_power_t_test_proteins(), lfq_power_t_test_quantiles(), plot_stat_density(), plot_stat_density_median(), plot_stat_violin(), plot_stat_violin_median(), plot_stdv_vs_mean(), pooled_V2(), summarize_stats()

Examples

bb1 <- prolfqua::sim_lfq_data_peptide_config()
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
lfq <- LFQData$new(bb1$data, bb1$config)
stats_res <- summarize_stats(lfq)
xx <- summarize_stats_quantiles(stats_res, lfq$relevant_factor_keys(), 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::pivot_wider(names_from = delta, values_from = N)