## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
library(ggpower)

## ----de-----------------------------------------------------------------------
power_compute("ttest_biomarker", "post_hoc", d = 0.6, n1 = 40, n2 = 40,
              alpha = 0.05, tails = "two")

## ----de-apriori---------------------------------------------------------------
power_compute("ttest_biomarker", "a_priori", d = 0.5, alpha = 0.05,
              power = 0.8, allocation_ratio = 1)

## ----roc-one------------------------------------------------------------------
power_compute(
  "roc_auc_one",
  analysis = "a_priori",
  auc = 0.75,
  auc0 = 0.5,
  n_pos = 50,
  n_neg = 50,
  alpha = 0.05,
  power = 0.8,
  tails = "two"
)

## ----roc-two------------------------------------------------------------------
power_compute(
  "roc_auc_two",
  analysis = "post_hoc",
  auc1 = 0.78,
  auc2 = 0.62,
  n1 = 80,
  n2 = 80,
  alpha = 0.05,
  tails = "two"
)

## ----diag---------------------------------------------------------------------
power_compute("diagnostic_acc", "post_hoc", sensitivity = 0.85, specificity = 0.85,
              n_pos = 50, n_neg = 50, alpha = 0.05)

## ----diag-apriori-------------------------------------------------------------
power_compute("diagnostic_acc", "a_priori", sensitivity = 0.9, specificity = 0.9,
              alpha = 0.05, power = 0.8, allocation_ratio = 1)

## ----surv---------------------------------------------------------------------
power_compute("survival_logrank", "post_hoc", hazard_ratio = 0.65,
              total_n = 200, event_rate = 0.5, alpha = 0.05)

## ----cox----------------------------------------------------------------------
power_compute("cox_regression", "post_hoc", hazard_ratio = 0.65,
              events = 100, alpha = 0.05)

## ----cox-apriori--------------------------------------------------------------
power_compute("cox_regression", "a_priori", hazard_ratio = 0.7,
              alpha = 0.05, power = 0.8)

## ----fdr----------------------------------------------------------------------
power_compute("discovery_fdr", "post_hoc", effect_d = 0.5, m_tests = 1000,
              pi0 = 0.9, fdr_level = 0.05, n = 40, alpha = 0.05)