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Wilcoxon Signed Rank Test Results: Variations in p-values and z-values Compared to SPSS

조회 수: 17 (최근 30일)
Hi, I am using the signrank() function from the Matlab library.
1) To verify the p-value, h and z-value. I have compared the results with the Wilcoxon signed rank test in SPSS. I found out that in some cases the Matlab p-value is different and z-value sometimes can't be found in Matlab. May I know what the reasons that lead to these differences? I have attached the result of SPSS for references and codes for three types of cases. Only the 3rd case get the similar p-value and z-value when compared to SPSS.
2) In addition, I found out that in case 1, the result of hypothesis test (h1) gets (0 in double mode)... isn't it should get in the logical mode?
3) Is there anything I should edit in the Matlab code to get more reliable answer?
Thanks in advance.
% Perform Wilcoxon Signed Rank Test
clear
clc
load Workspace_Data_WilcoxonSignedRank
% Compare dataset for Pair1 (1st Case)
[p1,h1,stats1] = signrank(Pair1_A,Pair1_B,'tail','both','alpha',0.05,'method','approximate')
p1 = 1
h1 = 0
stats1 = struct with fields:
signedrank: 0
% When I perform the wilcoxon signed Rank test to Pair 1, why does h1 get (0 in double mode?)
% supposely it should get in logical mode like Pair 2 and Pair 3.
% Is p1 is the correct value?
% Compare dataset for Pair2 (2nd Case)
[p2,h2,stats2] = signrank(Pair2_A,Pair2_B,'tail','both','alpha',0.05,'method','approximate')
p2 = 0.0588
h2 = logical
0
stats2 = struct with fields:
zval: -1.8898 signedrank: 0
% Correct compared to
% Compare dataset for Pair3 (3rd Case)
[p3,h3,stats3] = signrank(Pair3_A,Pair3_B,'tail','both','alpha',0.05,'method','approximate')
p3 = 1.7344e-06
h3 = logical
1
stats3 = struct with fields:
zval: 4.7821 signedrank: 465

답변 (1개)

Suraj Kumar
Suraj Kumar 2024년 9월 26일 4:13
Hi Wei,
Based on my understanding, you are facing issues in getting the z-value in MATLAB for some cases. To resolve this issue, you can refer the following steps:
The zval is not generated in the first case as the values are all identical. Hence, this is a degenerate case of all ties.
Now to generate the zval in such cases , we can create a default value for zval and generate it like this:
[p1,h1,stats1] = signrank(Pair1_A,Pair1_B,'tail','both','alpha',0.05,'method','approximate') ;
if ~isfield(stats1, 'zval')
stats1.zval = nan;
end
[p,h,statsrnd1] = signrank(Pair1_A,Pair1_B+randn(size(Pair1_B)));
statsvector1 = [stats1;statsrnd1]
Additionally, the type of the hypothesis result being returned as double instead of logical is also due to the values being treated as ties.
signrank function uses a tolerance defined as epsdiff = eps(x) + eps(y). It calculates the absolute differences and considers values with abs(d(i)) < epsdiff as ties.
To know more about this, you can refer to the following documentation link:
Hope this answers your query!

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