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May 20, 2010 2:47 PM
(1772 views)

Thanks for the help in advance.

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Nov 21, 2017 9:53 AM
(1551 views)

Solution

As stated above,

Hello again - I've set up below some SAS code to do the analysis as per the description in the earlier references, and then run the same analysis through JMP...

To do the same thing in JMP, download the following note by James Abbey at www.personal.psu.edu/jda188/JMP/Signedrank.doc and follow the instructions there on the DIFF column of your data set.

That is, import either FERTILIZER1.SAS7BDAT or FERTILIZER3.SAS7BDAT from your WILC library into JMP, and analyze the DIFF column using Analyze | Distribution. Copy the DIFF column into the "Y, Columns" placeholder and click OK. Next, click on the second red triangle and select "Test Mean". Put 0 into "Specify Hypothesized Mean", and check the "Wilcoxon Signed Rank" box, then click OK. In the "Test Mean=value" section of the output you should find the test statistic = 74, and the P value of 0.0017 - which is the same answer as the one that SAS produces.

Is that okay?

Duane Hayes

9 REPLIES

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May 21, 2010 12:05 AM
(1503 views)

My second thought would be that maybe either the SAS or the JMP test you're performing isn't actually the signed-rank test for

http://en.wikipedia.org/wiki/Wilcoxon_signed-rank_test

http://en.wikipedia.org/wiki/Mann-Whitney-Wilcoxon_test

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May 21, 2010 7:41 AM
(1503 views)

Here is an example with sample data from UCLA Stat Academic Tech Services that agrees:

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May 24, 2010 8:06 AM
(1503 views)

David Q/R I was using a book example which is why I was so surprised to get different answers.

Is there any way to get the source code to work through the problem by hand and see at which step the code may do differently?

Thanks again.

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May 24, 2010 9:47 AM
(1503 views)

Below is another reference showing how to perform a Wilcoxon Matched-Pairs Signed-Ranks test in SAS, suggesting that the basic test is not actually one of those supplied as a simple procedure (or why go to the trouble of doing it in this slightly roundabout way?):

http://udel.edu/~mcdonald/statsignedrank.html

If you'd like to post a copy of the code you're running I'll be happy to check to see if I'm right about this.

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May 25, 2010 12:43 PM
(1503 views)

data fertilizer;

input typea typeb;

diff= typea-typeb;

cards;

211.40000000000001000 186.30000000000001000

204.40000000000001000 205.69999999999999000

202.00000000000000000 184.40000000000001000

201.90000000000001000 203.59999999999999000

202.40000000000001000 180.40000000000001000

202.00000000000000000 202.00000000000000000

202.40000000000001000 181.50000000000000000

207.09999999999999000 186.69999999999999000

203.59999999999999000 205.69999999999999000

216.00000000000000000 189.09999999999999000

208.90000000000001000 183.59999999999999000

208.69999999999999000 188.69999999999999000

213.80000000000001000 188.59999999999999000

201.59999999999999000 204.19999999999999000

201.80000000000001000 181.59999999999999000

200.30000000000001000 208.69999999999999000

201.80000000000001000 181.50000000000000000

201.50000000000000000 208.69999999999999000

212.09999999999999000 186.80000000000001000

203.40000000000001000 182.90000000000001000

;

proc univariate;

var diff;

run;

data fertilizer;

input type $ fert;

cards;

a 211.40000000000001000

b 186.30000000000001000

a 204.40000000000001000

b 205.69999999999999000

a 202.00000000000000000

b 184.40000000000001000

a 201.90000000000001000

b 203.59999999999999000

a 202.40000000000001000

b 180.40000000000001000

a 202.00000000000000000

b 202.00000000000000000

a 202.40000000000001000

b 181.50000000000000000

a 207.09999999999999000

b 186.69999999999999000

a 203.59999999999999000

b 205.69999999999999000

a 216.00000000000000000

b 189.09999999999999000

a 208.90000000000001000

b 183.59999999999999000

a 208.69999999999999000

b 188.69999999999999000

a 213.80000000000001000

b 188.59999999999999000

a 201.59999999999999000

b 204.19999999999999000

a 201.80000000000001000

b 181.59999999999999000

a 200.30000000000001000

b 208.69999999999999000

a 201.80000000000001000

b 181.50000000000000000

a 201.50000000000000000

b 208.69999999999999000

a 212.09999999999999000

b 186.80000000000001000

a 203.40000000000001000

b 182.90000000000001000

;

proc npar1way wilcoxon;

class type;

var fert;

run;

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May 26, 2010 2:21 AM
(1503 views)

To do the same thing in JMP, download the following note by James Abbey at www.personal.psu.edu/jda188/JMP/Signedrank.doc and follow the instructions there on the DIFF column of your data set.

That is, import either FERTILIZER1.SAS7BDAT or FERTILIZER3.SAS7BDAT from your WILC library into JMP, and analyze the DIFF column using Analyze | Distribution. Copy the DIFF column into the "Y, Columns" placeholder and click OK. Next, click on the second red triangle and select "Test Mean". Put 0 into "Specify Hypothesized Mean", and check the "Wilcoxon Signed Rank" box, then click OK. In the "Test Mean=value" section of the output you should find the test statistic = 74, and the P value of 0.0017 - which is the same answer as the one that SAS produces.

Is that okay?

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May 26, 2010 10:47 AM
(1503 views)

Michael

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Jun 23, 2010 10:37 AM
(1503 views)

Thank you all again for your help. I have been able to get the solutions to match.

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Nov 21, 2017 9:53 AM
(1552 views)

As stated above,

To do the same thing in JMP, download the following note by James Abbey at www.personal.psu.edu/jda188/JMP/Signedrank.doc and follow the instructions there on the DIFF column of your data set.

That is, import either FERTILIZER1.SAS7BDAT or FERTILIZER3.SAS7BDAT from your WILC library into JMP, and analyze the DIFF column using Analyze | Distribution. Copy the DIFF column into the "Y, Columns" placeholder and click OK. Next, click on the second red triangle and select "Test Mean". Put 0 into "Specify Hypothesized Mean", and check the "Wilcoxon Signed Rank" box, then click OK. In the "Test Mean=value" section of the output you should find the test statistic = 74, and the P value of 0.0017 - which is the same answer as the one that SAS produces.

Is that okay?

Duane Hayes