Dear everyone,
I have a question about performing a Mixed Design ANOVA in SPSS, after multiple imputation. I have imputed my data, but when I perform the Mixed Design ANOVA, I do not get a pooled result. The syntax I used is like this: GLM Mg_preNTx Mg_D7 Mg_M1 Mg_M3 Mg_M6 Mg_M12 BY OBESITY /WSFACTOR=Magnesium 6 Polynomial /METHOD=SSTYPE(3) /PLOT=PROFILE(Magnesium*OBESITY) /CRITERIA=ALPHA(.05) /WSDESIGN=Magnesium /DESIGN=OBESITY. Is it possible to generate a pooled p-value for this analysis? Because what I want is one p-value (Sphericity assumed or with GreenhouseGeisser correction) that says: are the Mg values over time different for patients with and without obesity? Thank you in advance! -- Sent from: http://spssx-discussion.1045642.n5.nabble.com/ ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD |
Dear Lisa,
You should read:
Van Ginkel, J.R. & Kroonenberg, P.M. (2014). Analysis of variance of multiply imputed data. Multivariate Behavioral Research, 49, 78-91. doi: 10.1080/00273171.2013.855890
The paper comes with an SPSS macro that is available from my personal page:
If you (and any other people reading this) need any help, please let me know.
Best regards,
Joost van Ginkel
-----Original Message-----
From: SPSSX(r) Discussion [[hidden email]] On Behalf Of LisaSnel Sent: Tuesday, January 08, 2019 11:53 AM To: [hidden email] Subject: Mixed Design ANOVA after multiple imputation Dear everyone,
I have a question about performing a Mixed Design ANOVA in SPSS, after
multiple imputation. I have imputed my data, but when I perform the Mixed
Design ANOVA, I do not get a pooled result. The syntax I used is like this:
GLM Mg_preNTx Mg_D7 Mg_M1 Mg_M3 Mg_M6 Mg_M12 BY OBESITY
/WSFACTOR=Magnesium 6 Polynomial
/METHOD=SSTYPE(3)
/PLOT=PROFILE(Magnesium*OBESITY)
/CRITERIA=ALPHA(.05)
/WSDESIGN=Magnesium
/DESIGN=OBESITY.
Is it possible to generate a pooled p-value for this analysis? Because what
I want is one p-value (Sphericity assumed or with GreenhouseGeisser
correction) that says: are the Mg values over time different for patients
with and without obesity?
Thank you in advance!
--
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Dear Eduard,
Firstly, the syntax doesn't provide variable names. Maybe that is something to include in future versions if I have the time. However, the F-values are displayed in the same order as the order in which they are displayed in the output of the (non-pooled) Mixed models analysis (additionally, you can also see it in the number of model degrees of freedom). To give a little bit more explanation, the COMBINED OVERALL TEST is the F-test which tests whether there are any significant differences, the COMBINED RESULTS provide the F-values of the separate effects (with the F-test for the intercept on top), and the Estimate, SE, t, df, and p are the results of the pooled regression coefficients of the model. In ANOVA you normally don't interpret these coefficients. As for the correction for the violation of Sphericity assumption: In Mixed models there is an option for a Huyn-Feldt correction (under Random.., Covariance Type). If you select that option and you combine the results using my syntax, it will probably this correction into account in the pooling as well. I don't see any Greenhouse-Geisser correction option so that it probably not possible. Best, Joost -----Original Message----- From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of EduardNash Sent: Wednesday, January 09, 2019 9:40 AM To: [hidden email] Subject: Re: Mixed Design ANOVA after multiple imputation Dear Lisa and Joost, Thank you for your question and answer. I am dealing with a similar issue: I want to know if blood pressure over time is significantly different between patients receiving treatment A and patients receiving treatment B. I also performed a Mixed Design ANOVA and used the Sphericity assumption and the Greenhouse-Geisser correction to get the p-value for significance. However, I also needed to impute my data. I struggled with similar issues as Lisa and tried the approach Joost wrote down. But the output I get is strange: Run MATRIX procedure: COMBINED OVERALL TEST F-Value df1 df2 p 69.5618 11.0000 716.7493 .0000 COMBINED RESULTS F-Value df1 df2 p 10448.4401 1.0000 156.9713 .0000 3.8572 1.0000 156.5526 .0513 106.4352 5.0000 754.7524 .0000 2.2857 5.0000 727.0853 .0446 Estimate SE t df p .6997 .0068 102.2176 156.9713 .0000 -.0135 .0069 -1.9640 156.5526 .0513 .1752 .0088 19.9457 573.5050 .0000 .0341 .0089 3.8328 461.3061 .0001 -.1061 .0086 -12.3504 779.2266 .0000 -.0737 .0087 -8.4362 625.9757 .0000 -.0276 .0088 -3.1324 536.4563 .0018 .0235 .0089 2.6547 490.5419 .0082 .0099 .0093 1.0676 238.6150 .2868 -.0078 .0086 -.9081 785.6911 .3641 -.0181 .0087 -2.0703 634.4185 .0388 -.0056 .0088 -.6349 511.7262 .5258 ------ END MATRIX ----- In the combined results, I only see the F-statistic and not the variable name. Besides that, I do not get a p-value for the Sphericity assumption and/or Greenhous Geisser correction. And those two are the ones I am interested in. So my question is: is there a way to get to those two p-values? I would very appreciate the help. Best wishes, Eduard Nash -- Sent from: http://spssx-discussion.1045642.n5.nabble.com/ ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD |
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