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  • 1-way repeated measures Anova and post hoc test

    Hi all,

    So I am trying to perform a 1-way repeated measures Anova and a post hoc test on my data. In the data editor, I have:
    - variable 1 (labelled as 'id'): the participants id number (1 to 14),
    - variable 2 (labelled as 'time'): the time the measurements were made (pre= 1, post 1 min= 2, post 2 min= 3 and post 3 min= 4),
    - variable 3 (labelled as 'sbj'): a jump test in centimeters

    In the command window I typed 'anova sbj id time, repeated (time)' and it worked.

    Now when I want to perform a post hoc test to see where the differences occur I type 'pwcompare time subj time#sbj' BUT it gives me 'variable sbj not found - r(111);'

    Does anyone have an idea where the issue may come from?

    Thank you all for your precious help
    Last edited by Laurentseitz; 02 Jun 2015, 02:15.

  • #2
    Are you sure the error message wasn't "variable subj not found - r(111)"?

    It's usually best to show exactly what you typed and what resulted, as in copy-and-paste, or (better) attach a log file. See Section 12 of the forum's FAQ.

    Comment


    • #3
      Hello,

      Ok so I found my mistake. I can't include the outcome in the command, so it worked with:


      pwcompare time, effects

      Pairwise comparisons of marginal linear predictions

      Margins : asbalanced

      ------------------------------------------------------------------------------
      | Unadjusted Unadjusted
      | Contrast Std. Err. t P>|t| [95% Conf. Interval]
      -------------+----------------------------------------------------------------
      time |
      2 vs 1 | .0914286 .0234124 3.91 0.000 .0444482 .138409
      3 vs 1 | .0864286 .0234124 3.69 0.001 .0394482 .133409
      4 vs 1 | .1092857 .0234124 4.67 0.000 .0623053 .1562661
      5 vs 1 | .0921429 .0234124 3.94 0.000 .0451625 .1391233
      3 vs 2 | -.005 .0234124 -0.21 0.832 -.0519804 .0419804
      4 vs 2 | .0178571 .0234124 0.76 0.449 -.0291233 .0648375
      5 vs 2 | .0007143 .0234124 0.03 0.976 -.0462661 .0476947
      4 vs 3 | .0228571 .0234124 0.98 0.333 -.0241233 .0698375
      5 vs 3 | .0057143 .0234124 0.24 0.808 -.0412661 .0526947
      5 vs 4 | -.0171428 .0234124 -0.73 0.467 -.0641232 .0298376



      However, do you know how to get the exact p values?

      Comment


      • #4
        What do you mean by exact p-values? Do you want something like this?
        Code:
        pwcompare time, pveffects mcompare(bonferroni)

        Comment


        • #5
          Yes that is exactly what I want!!! Thank you so much.

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