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  • Skillings Mack test?

    Hello all,

    I have a dataset of 25 participants who were sampled at 3 time-points (pre-intervention, post-intervention, 3-mo follow-up). I would like to see if there is a change in various prespecified outcome measures over that time. Because of the small sample size and some loss to follow-up, I chose the Skillings Mack test as a non-parametric version of repeated measures ANOVA. However some of the Stata output is inconsistent, so I wanted to know if I'm writing the code incorrectly.

    When I run

    Code:
    skilmack updrs_2, id( record_id) repeated( visit)
    I get this:
    HTML Code:
    Weighted Sum of Centered Ranks
    
     visit |     N  WSumCRank        SE   WSum/SE  
    -------+-------------------------------------
     1     |    17       9.00      4.12      2.18  
     2     |    17      -9.00      4.12     -2.18  
    ---------------------------------------------
     Total               0 
    
    Note N= 8 not included as only had one observation
    
    Skillings Mack    =   4.765
    P-value (No ties) =   0.0290
    
      Ties exist. Above SEs and P-value approximate, if not too many ties;
      42 rows of [record_id, updrs_2_score]; 40 different combinations;  n(record_id) = 25
    
      Consider using the p-value below, (which is found from a simulated
            conditional null distribution of SM   - see options -
      simulating ...........)
    
    Empirical P-value (Ties)    ~   0.0110
    This suggests that there is a significant pre-post difference in the UPDRS_2 variable.


    However when I run this:
    Code:
    by visit, sort : summarize updrs_2, detail
    I get

    HTML Code:
    -> visit = 1
    
                            updrs_2_score
    -------------------------------------------------------------
          Percentiles      Smallest
     1%            2              2
     5%            3              3
    10%            4              4       Obs                  25
    25%            8              6       Sum of Wgt.          25
    
    50%            8                      Mean               9.56
                            Largest       Std. Dev.      4.213866
    75%           12             13
    90%           15             15       Variance       17.75667
    95%           17             17       Skewness       .6863663
    99%           21             21       Kurtosis       3.820296
    
    ------------------------------------------------------------------------------------------------------
    -> visit = 2
    
                            updrs_2_score
    -------------------------------------------------------------
          Percentiles      Smallest
     1%            2              2
     5%            2              3
    10%            3              4       Obs                  17
    25%            6              5       Sum of Wgt.          17
    
    50%            8                      Mean           8.176471
                            Largest       Std. Dev.      4.333522
    75%            9             11
    90%           13             13       Variance       18.77941
    95%           20             13       Skewness       1.106565
    99%           20             20       Kurtosis       4.390751
    which shows that the median is the same (although the interquartile range is shifted down a bit).

    I'm having trouble reconciling the SM p-value with the actual medians here. Note that this particular example has only two timepoints, although most of the other outcome variables do have a third. On the other outcome variables, the p-value only registers as significant when there is an obvious difference between medians (e.g. 31 to 24).

    So my question is:
    1. Is the Skillings-Mack an appropriate test to use in this situation?
    1a. If so, do I need to adjust my command?
    1b. If not, is there a different statistical test I should use?

    Thank you very much!

  • #2
    Do you want to look at the differences between time points within subjects? You might also look at the data with a spaghetti plot type graph.

    Comment


    • #3
      Originally posted by Dave Airey View Post
      Do you want to look at the differences between time points within subjects? You might also look at the data with a spaghetti plot type graph.
      Yes, I made a spaghetti plot, but it looks very messy with some people improving and others worsening. Perhaps that's why the medians are the same but SM says there's a difference?

      Comment

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