APriot: A computer program for Monte-Carlo simulations of cumulated error probabilities in ANOVA

When conducting a psychological experiment it often is tempting to intermediately inspect data and then to decide whether to add further participants or to end the study. But we all know that intermediately inspecting statistical data is "forbidden" since there is an accumulation of alpha.

Interstingly, in medical research intermediate inspections of the data of a running experiment are widely spread. This is comprehensible since ethical reasons often forbid a new drug to be tested for a longer time than necessary. The test procedure is called "group-sequential" testing and is based on the idea that a correction value  can be found for alpha such that the cumulated alpha error probability for multiple inspections does not exceed a predefined value, for example, .05.

In psychology sequential testing is widely unknown. One reason may be that the sequential tests known from medical research  focus on statistical tests based on the normal distribution. This is suitable for testing the effectiveness of a new drug. There is one group of participants receiving the new drug and a control group. Within classical statistics a t-test would be conducted. With a number of participants not too small the t-distribution approximates the normal distribution.

In psychological research the analysis of variance is very common since it allows for testing more complex experimental designs with multiple variables and interactions between those variables. APriot can conduct Monte-Carlo simulations of the ANOVA and simulate the effects of intermediately inspecting data. APriot can simulate all effects of the ANOVA including repeated measures and interactions of any order.

It has been tried to make APriot as easy to use as possible. There is no need for the user to enter complex simulation parameters like matrices of means, standard deviations or correlations of residuals. Instead, the user enters the data of an earlier study and APriot computes all parameters needed for conducting a simulation.

I hope that APriot will help you to detect effects in a more economical way without the shortcoming of an inflated alpha error probability.

Screenshots (click to enlarge)

System requirements

APriot is compatible with Windows 7 - 10. There are 32 and 64 bits versions.

Download and install

By downloading APriot you agree to these terms of use:

  1. APriot is free for everyone. Commercial distribution is strictly prohibited.
  2. APriot  is distributed from this website. If you wish to distribute APriot in some other way, then you need to seek permission from the author. Please undefinedsend me an e-mail in which you specify how and for what purpose you intend to distribute APriot.
  3. You may use screenshots of APriot without asking for permission.
  4. Considerable effort has been put into program development and evaluation, but there is no warranty whatsoever.

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APriot is distributed with a user manual in which all steps necessary to conduct a simulation are explained. You can select the manual within APriot by choosing '? -> APriot user manual'.

Alternatively, you can undefineddownload the manual here.

Please note

If you use APriot for your research I would appreciate your including the following reference to APriot in the papers in which you publish your results:

Lang, A.-G. (2014). APriot: A computer program for Monte-Carlo simulations of cumulated error probabilities in ANOVA. In Heinrich-Heine-Universität - Institut für experimentelle Psychologie. Retrieved June 21, 2016, from www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/apriot.html.

(Please replace the date retrieved with the date you retrieved this web site.)

Bug reports

If you find a problem with APriot please send a bug report to Albert-Georg Lang.

Verantwortlich für den Inhalt: E-Mail sendenAlbert-Georg Lang