0
$\begingroup$

I conducted a repeated measures ANOVA in SPSS, using the command Generalised Linear Model > Repeated Measures. I have a within subject factor with two levels (A), a measure (B) and a covariate (C). The within subject variables based on the factor are AB_1, AB_2.

According to the literature, ANCOVA has an additional assumption, the one of homogeneity of slopes. I have been trying to conduct the test in SPSS using the syntax commands I found here : https://www.ibm.com/support/pages/testing-homogeneity-slopes-hos-assumption-factorial-ancova-spss, which however refers to factorial ANCOVA. Specifically, I wrote:

DATASET ACTIVATE DataSet2.
GLM AB_1 AB_2 WITH C
  /WSFACTOR=A 2 Simple(1) 
  /MEASURE=B
  /METHOD=SSTYPE(3)
  /PLOT=PROFILE(B)
  /PRINT=DESCRIPTIVE HOMOGENEITY 
  /CRITERIA=ALPHA(.05)
  /WSDESIGN=B
  /DESIGN=C*A

I keep getting the following error:

A syntax error was detected in the effect specification where the symbol dur was encountered. Effect specification should have the following structure effect = BY-expression [WITHIN BY-expression [...]] BY-expression = variable [BY variable [...]] where variable is a factor or a covariate.

My question is if there's any was to test this assumption for repeated measures designs?

$\endgroup$
0
$\begingroup$

I'm not sure "dur" comes from, but there are a few things wrong in the syntax.

First, B is a measure name rather than a factor, and doesn't belong on WSDESIGN. You can remove the WSDESIGN subcommand altogether, or substitute A for B there.

Second, substitute A for B on the PLOT subcommand for the same reason.

Finally, A is a within-subjects effect, and can't go on the DESIGN subcommand, which specifies the between-subjects part of the model. You can remove the DESIGN subcommand altogether or just change C*A to C.

GLM uses the multivariate general linear model approach to repeated measures, with some post-estimation finagling to get some repeated-measures tests and such. In this model, all within-subjects factors are automatically crossed with each other, and also with anything from the between-subjects part of the design, which in this case is the covariate C. So you'll get an interaction of A and C automatically.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.