An S4 class to represent the results of a sequential t-test.

Slots

likelihood_ratio_log: the logarithmic test statistic.
decision: the test decision: "accept H1", "accept H0", or "continue sampling".
A_boundary_log: the lower logarithmic boundary of the test.
B_boundary_log: the upper logarithmic boundary of the test.
d: a number indicating the specified effect size (Cohen's d).
mu: a number indicating the true value of the mean (or difference in means if you are performing a two sample test).
alpha: the type I error. A number between 0 and 1.
power: 1 - beta (beta is the type II error probability). A number between 0 and 1.
likelihood_ratio: the likelihood ratio of the test without logarithm.
likelihood_1: the likelihood of the alternative Hypothesis (H1).
likelihood_0: the likelihood of the null Hypothesis (H0).
likelihood_1_log: the logarithmic likelihood of the alternative Hypothesis (H1).
likelihood_0_log: the logarithmic likelihood of the null Hypothesis (H0).
non_centrality_parameter: parameter to calculate the likelihoods
t_value: the t-value of the t-statistic.
p_value: the p-value of the t-test.
df: degrees of freedom.
mean_estimate: the estimated mean or difference in means depending on whether it was a one-sample test or a two-sample test.
alternative: a character string specifying the alternative hypothesis: "two.sided" (default), "greater" or "less".
one_sample: "true" if it is a one-sample test, "false" if it is a two-sample test.
ttest_method: a character string indicating what type of t-test was performed.
data_name: a character string giving the name(s) of the data.
verbose: a logical value whether you want a verbose output or not.