Howdy, Stranger!

It looks like you're new here. If you want to get involved, click one of these buttons!

Supported by

p value for Conover's test

Hi everyone,

I would like to know when using Conover's test as the post hoc comparison for Friedman's test, which p-value I should use? The output table has 3 different p values, namely, p, pbonf, and pholm. And also, is the alpla level automatically adjusted when performing Conover's test in JASP? Thanks in advance!

  • I have included a screenshot below. If I set an alpha level at 0.05, and I have a total of 10 pairwise comparisons performed by Conover's test, which ones are significantly different based on the output below?


Comments

  • This depends on whether you wish to correct for multiplicity, and what method of multiplicity-correction you prefer, given the research context at hand. Usually Bonferonni is considered very strict. Your best bet is to consult the background literature on this tricky issue.

    Cheers,

    E.J.

  • edited February 2023

    Hi @EJ,

    Thanks for your response!

    I have decided to do a p-value correction due to multiple testing. If I want to use Bonferroni correction, given that I have 10 pairwise comparisons, the altered alpha level will be set at 0.05/10 = 0.005. Then based on the output of JASP, does that mean I should go to the column of pbonf and then find if there is any p-value <= 0.005 in order to decide it's statistically significant? Or, should I just use the original alpha level (0.05) as the threshold to compare with the pbonf column results and decide the result?

  • " should I just use the original alpha level (0.05) as the threshold to compare with the pbonf column results and decide the result"

    Yes. You can see that, for instance, the .008 p-value corresponds to a .080 p-bonf value.

    E.J.

  • @EJ

    Got it ! Thank you very much!

Sign In or Register to comment.