# Printing a findn Object Displays details about a sample size estimation from a `findn` object. ```r ## S3 method for class 'findn' print( x, details = c("low", "high"), max_n = NULL, digits = 3, invisible = FALSE, ... ) ``` ## Arguments - `x`: Object of class `findn`. - `details`: Either `"low"` (default) or `"high"`. See also 'Details'. - `max_n`: If `details = "high"` the predicted power values and confidence intervals are shown for all sample sizes from 1 to `max_n` if `max_n` is non-`NULL`. See also 'Details'. - `digits`: Number of decimal places to be shown. - `invisible`: Whether the results should be printed or only assigned. - `...`: Further arguments. ## Returns `findn` returns an object of class `findn` which contains the following elements: - **sample_size**: the sample size estimate - **fit**: the model coefficients and covariance matrix from the last Bayesian probit regression model - **all_evals**: all evaluated sample sizes - **targ**: the target power - **level**: the significance level for the confidence intervals used for the stopping criteria - **exit.mes**: a message about wheter the stopping criterion was reached with the number of simulations given by `max_evals` By default, a list containing the point estimate for the sample size, the minimum sufficient sample size (i.e. the smallest sample size for which the lower limit of the confidence interval for the estimated power is larger than the target power) and a message whether the stopping criterion was reached is printed. ## Details When `details = "low"`, only the point estimate (i.e., the smallest sample for which the predicted power exceeds the target power), the "minimum sufficient sample size" (i.e., the smallest sample size for which the lower limit of the `level` interval for the predicted power exceeds the target power) and an exit message. The exit message shows whether the chosen stopping rule was satisfied. If `details = "high"` then the default behaviour (i.e. when `max_n = NULL`) is to display all sample sizes, their predicted power values and the alpha whether their power exceeds the target power, and the three largest sample sizes that are smaller than the smallest sample size that is rated uncertain and the three smallest sample sizes which are greater than the smallest sample size that is rated uncertain. If `details = "high"` and `max_n` is non-`NULL`, then the sample sizes, their predicted power values and the confidence intervals for the predicted power values from 1 to `max_n` are displayed. ## Examples ```r # Function that simulates the outcomes of a two-sample t-test ttest <- function(mu1 = 0, mu2 = 1, sd, n, k) { sample1 <- matrix(rnorm(n = ceiling(n) * k, mean = mu1, sd = sd), ncol = k) mean1 <- apply(sample1, 2, mean) sd1_hat <- apply(sample1, 2, sd) sample2 <- matrix(rnorm(n = ceiling(n) * k, mean = mu2, sd = sd), ncol = k) mean2 <- apply(sample2, 2, mean) sd2_hat <- apply(sample2, 2, sd) sd_hat <- sqrt((sd1_hat^2 + sd2_hat^2) / 2) teststatistic <- (mean1 - mean2) / (sd_hat * sqrt(2 / n)) crit <- qt(1 - 0.025, 2*n - 2) return(mean(teststatistic < -crit)) } # Create a findn object res_ttest <- findn(fun = ttest, targ = 0.8, k = 25, start = 100, init_evals = 100, r = 4, stop = "evals", max_evals = 2000, level = 0.05, var_a = 0.05, var_b = 1, alpha = 0.025, alternative = "one.sided", sd = 2, verbose = FALSE) # print with default settings print(res_ttest, details = "low", digits = 3) ```

print.findn function