# ab-methods: Methods for ab objects In abtest: Bayesian A/B Testing

## Description

Methods defined for objects returned from the `ab_test` function.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```## S3 method for class 'ab' summary(object, digits = 3, raw = FALSE, ...) ## S3 method for class 'summary.ab' print(x, ...) ## S3 method for class 'ab' print(x, ...) ## S3 method for class 'ab' plot(x, ...) ```

## Arguments

 `object, x` object of class `ab` as returned from `ab_test`. `digits` number of digits to print for the summary. `raw` if `TRUE`, the raw posterior samples are used to estimate the mean, sd, and quantiles for the summary of the posterior. If `FALSE`, parametric fits to the marginal posteriors are used to obtain the mean, sd, and quantiles. Specifically, a normal distribution is fitted for ```psi (logor)``` and `beta`; a log-normal distribution is fitted for `or` and `rrisk`; beta distributions are fitted for `p1` and `p2`; a scaled beta distribution is fitted for `arisk`. These distributional fits are also used in `plot_posterior`. `...` further arguments, currently ignored.

## Value

The `print` methods prints the Bayes factors, prior probabilities of the hypotheses, and posterior probabilities of the hypotheses (and returns nothing).

The `plot` method visualizes the prior probabilities of the hypotheses and posterior probabilities of the hypotheses (the next plots is obtained by hitting Return) using the `prob_wheel` function.

The `summary` methods returns the `ab` object that is guaranteed to contain posterior samples (i.e., it adds posterior samples if they were not included already). Additionally, it adds to the object a posterior summary matrix (i.e., `ab\$post\$post_summary`) for the posterior under H1 and the arguments `digits` (used for printing) and `raw` (added to `ab\$input`).

abtest documentation built on Nov. 22, 2021, 9:07 a.m.