Compute theoretical sample sizes from factor level standard deviations — lfq_power_t_test_proteins • prolfqua

Compute theoretical sample sizes from factor level standard deviations

lfq_power_t_test_proteins(
  stats_res,
  delta = c(0.59, 1, 2),
  power = 0.8,
  sig.level = 0.05,
  min.n = 1.5
)

Arguments

stats_res: data.frame `summarize_stats` output
delta: effect size you are interested in
power: of test
min.n: smallest n to determine
sigma.level: P-Value

See also

Other stats: INTERNAL_FUNCTIONS_BY_FAMILY, lfq_power_t_test_quantiles(), lfq_power_t_test_quantiles_V2(), 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 fileName column
#> Warning: no nr_children column specified in the data, adding column nr_children and setting to 1.
#> completing cases

ldata <- LFQData$new(bb1$data, bb1$config)
stats_res <- summarize_stats(ldata$data, ldata$config)
#> [1] "group_"
#> completing cases
bb <- lfq_power_t_test_proteins(stats_res)