## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width = 7, fig.height = 4 ) ## ----setup, message=FALSE----------------------------------------------------- library(anovapowersim) ## ----load-precomputed-results, include=FALSE---------------------------------- vignette_results_path <- system.file( "extdata", "anovapowersim-vignette-results.rds", package = "anovapowersim" ) if (!nzchar(vignette_results_path)) { vignette_results_path <- file.path( "..", "inst", "extdata", "anovapowersim-vignette-results.rds" ) } vignette_results <- readRDS(vignette_results_path) ## ----adaptive-code, eval=FALSE------------------------------------------------ # power_n( # between = c(cond = 2), # cond has 2 levels # within = c(stim = 4), # stim has 4 levels # term = "cond:stim", # target_pes = 0.14, # alpha = 0.05, # power = 0.90, # n_sims = 1000, # use 5000+ for a more precise estimate # seed = 123 # for reproducibility # ) ## ----adaptive-output, echo=FALSE---------------------------------------------- vignette_results$adaptive ## ----complex, eval=FALSE------------------------------------------------------ # power_n( # between = c(cond = 2, age = 3), # cond has 2 levels, age has 3 levels # within = c(stim = 4), # stim has 4 levels # term = "cond:stim:age", # target_pes = 0.14, # alpha = 0.05, # power = 0.90, # n_sims = 1000, # use 5000+ for a more precise estimate # seed = 123 # for reproducibility # ) ## ----curve-fixed-code, eval=FALSE--------------------------------------------- # pc <- power_curve( # between = c(cond = 2), # within = c(stim = 2), # term = "cond:stim", # target_pes = 0.14, # n_range = c(16, 20, 23, 28), # n per between-subject cell # n_sims = 1000, # seed = 123 # ) # pc ## ----curve-fixed-output, echo=FALSE------------------------------------------- pc <- vignette_results$curve pc ## ----plot-fixed, echo=FALSE--------------------------------------------------- plot_power_curve( pc, power_lines = c(.80, .90) # adds horizontal lines at 80% and 90% power ) ## ----parallel, eval=FALSE----------------------------------------------------- # power_curve( # between = c(cond = 2), # within = c(stim = 2), # term = "cond:stim", # target_pes = 0.14, # n_range = c(16, 20, 23, 28), # n_sims = 5000, # parallel = TRUE, # cores = 4, # seed = 123 # ) ## ----gpower-adaptive-code, eval=FALSE----------------------------------------- # power_n( # between = c(cond = 2), # within = c(stim = 4), # term = "cond:stim", # target_pes = 0.14, # alpha = 0.05, # power = 0.90, # n_sims = 1000, # seed = 123, # gpower = TRUE # ) ## ----gpower-adaptive-output, echo=FALSE--------------------------------------- vignette_results$gpower_adaptive