lfq_power_t_test_quantiles: Compute theoretical sample sizes from factor level standard...

In wolski/prolfqua: Proteomics Label Free Quantification

Compute theoretical sample sizes from factor level standard deviations

Description

Compute theoretical sample sizes from factor level standard deviations

Usage

lfq_power_t_test_quantiles(
  pdata,
  config,
  delta = 1,
  power = 0.8,
  sig.level = 0.05,
  probs = seq(0.5, 0.9, by = 0.1)
)

Arguments

pdata	data.frame
config	AnalysisConfiguration
delta	effect size you are interested in
power	of test
sigma.level	P-Value

See Also

Other stats: INTERNAL_FUNCTIONS_BY_FAMILY, lfq_power_t_test_proteins(), 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()
config <- bb1$config
data2 <- bb1$data

res <- lfq_power_t_test_quantiles(data2, config)
res$summary
stats_res <- summarize_stats(data2, config)
res <- lfq_power_t_test_quantiles(data2, config, delta = 2)
res <- lfq_power_t_test_quantiles(data2, config, delta = c(0.5,1,2))

wolski/prolfqua documentation built on Dec. 4, 2024, 11:18 p.m.