inst/help/Bain Welch's T-Test.md

In koenderks/JASP-for-Bain: Bain Module for JASP

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bain Welch test

The bain (Bayesian informative hypotheses evaluation) Welch test allows you test the nul-hypothesis that two means are equal versus one-sided and two-sided alternative hypotheses. An important characteristic of the Bayesian Welch test is that it does NOT assume that the variance of the dependent variable is the same in both groups.

Specification of the bain Welch test

• Choose the dependent variable(s) from the variable list and move it/them to the Dependent Variable box.
• Choose the factor from the variable list and move it to the Grouping Variable box.
• When you execute the bain Welch test for the first time tick the additional statistics and both plots. When you return to the bain Welch test you will know what each of these three options renders and you can tick only the options you need.
• By default 95% credible intervals will be presented in the results. If desired the degree of belief (by default 95%) can be changed.

• You can choose from five testing situations:

• H0: m1 = m2 versus H1: m1, m2 (no constraints on both means)

• H0: m1 = m2 versus H1: m1 > m2
• H0: m1 = m2 versus H1: m1 < m2
• H1: m1 > m2 versus H2: m1 < m2

• H0: m1 = m2 versus H1: m1 > m2 versus H2: m1 < m2

• If under the Bayes Factors label you choose BF01, values of the Bayes factor larger than 1 express support in favor of H0. If you choose BF10, values of the Bayes factor larger than 1 express support in favor of H1 (or H2).

Results obtained after running the bain Welch test

• To be able to properly interpret the results of a the bain Welch test, you are required to read the TUTORIAL by Hoijtink, Mulder, van Lissa, and Gu (2018) that can be retrieved from the Psychological Methods website or from the bain website at https://informative-hypotheses.sites.uu.nl/software/bain/
• If you want to understand the technical background of bain you should read Gu, Mulder, and Hoijtink (2017) and Hoijtink, Gu, and Mulder (2018) that can be retrieved from the British Journal of Mathematical and Statistical Psychology website or from the bain website at https://informative-hypotheses.sites.uu.nl/software/bain/

• Four pieces of results for each dependent variable are obtained after running a Bayesian Welch test:

• The table in which the Bayes facor of H0 versus the alternative hypothese is presented. This table also contains the posterior model probability of each hypothesis.

• A desriptives table containing for each group the sample size, sample mean, sample standard deviation (sd), standard error (se) and 95% credible interval.
• A plot of the pmp's visually highlighting the support in the data for each hypothesis entertained.
• A plot of the sample means and their credible intervals.

References

• Gu, X., Mulder, J., and Hoijtink, H. (2018). Approximate adjusted fractional Bayes factors: A general method for testing informative hypotheses. British Journal of Mathematical and Statistical Psychology, 71, 229-261. DOI: 10.1111/bmsp.12110
• Hoijtink, H., Mulder, J., van Lissa, C., and Gu, X. (2018). A tutorial on testing hypotheses using the Bayes factor. Psychological Methods. DOI: 10.1037/met0000201
• Hoijtink, H., Gu, X., and Mulder, J. (2018). Bayesian evaluation of informative hypotheses for multiple populations. British Journal of Mathematical and Statistical Psychology. DOI: 10.1111/bmsp.12145

koenderks/JASP-for-Bain documentation built on May 29, 2019, 7:33 a.m.