Mixed Model in SAS

Question

I want to analyse the data from an experiment.

The participants get different acoustic signals and judge them. The score is a high number, if they feel comfortable with the signal in the other case it is a lower number. I have 5 different signals and 15 participants. The experiment was performed 5 times for each subject, so I've get 65 values.

I want to use a mixed model. I get different results from SPSS and SAS and cannot find the error. It could be that I used PROC MIXED wrong.

proc mixed data=ein1;
class Signal ProNr;
model se = Signal;
random ProNr;
repeated /subject=ProNr;
run;
quit;

The result is:

                                    Die Prozedur MIXED

                              Covariance Parameter Estimates

                            Kov.Parm     Subjekt    Schätzwert

                            ProNr                            0
                            Residual     ProNr          112855


                                  Anpassungsstatistiken

                          -2 Res Log-Likelihood           881.1
                          AIC (kleiner ist besser)        883.1
                          AICC (kleiner ist besser)       883.2
                          BIC (kleiner ist besser)        883.7


                              Typ 3 Tests der festen Effekte

                               Zähler            Nenner
          Effekt       Freiheitsgrade    Freiheitsgrade    F-Statistik    Pr > F

          Signal                     4                48           1.00    0.4169

Did I choose the right parameters? I think that the result says that Signal isn't significant (0.4169 > 0.05). Is this the right interpretation of the results? I used in SPSS an anova with repeated measurements. SPSS corrected the results an the result with greenhouse geisser correction is 0.013. Why this results are so different?

EDIT1: The data looks like:

se   Pro_Nr signal
3.4799  1   1
3.3682  2   1
4.3217  3   1
2.9976  4   1
5.5861  5   1
6.7242  6   1
2.6379  7   1
1.9341  8   1

Pro_nr contains values from 1 to 15, every subject get one special number. signal contains numbers from 1 to 5. Each signal gets its own number.

Edit2: Proc glm isn't the right procedure to analyse this data, because no group variable can be defined. I have to use proc mixed for this problem.

Edit3: Is it possible to compare the results of an anova and a mixed model? Did I get the same results with both analyses?

New code:

PROC MIXED DATA=ein1;
CLASS Frequ ProNr;
MODEL se = Frequ;
REPEATED / subject=ProNr type=cs;
RUN;
QUIT;

Did I formulated the model (and so the program code) right to answer the question, wheater se depends on frequ (under the random and repeated effect of subjects)? Do you have some favourite literature to mixed models?

Answer 1

SPSS performs "repeated measures ANOVA", which can be done in SAS through PROC GLM, and not PROC MIXED. The latter can be used for repeated measures models, but the specific assumptions are somewhat different. UCLA has a wonderful page which explains how to do repeated measures ANOVA in SAS.

EDIT

Based on your comments, you are not actually trying to replicate SPSS's repeated measures ANOVA, but do a different analysis. As noted by Stephane, your PROC MIXED syntax is not quite right: you don't need both a random and a repeated statement (in this case). If you are looking for a compound symmetry structure (equal correlation), then either

RANDOM ProNr;

or

REPEATED / subject=ProNR type=cs;

would work, but you don't need both. With the REPEATED statement you can use more complicated correlation structures if needed, the RANDOM statement locks you into equal correlation (which is a more restrictive assumption than that of repeated measures ANOVA).