Repeated Measure Analysis (Univariate Mixed Effect Model .

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Repeated Measure Analysis (Univariate Mixed Effect Model Approach)(Treatment as the Fixed Effect and the Subject as the Random Effect)(This univariate approach can be used for randomized block design analysis.)1) Setting up the data sheetSet up of the data is similar to theRandomized Block Design situation.2) To run repeated measure analysis with univariate approach, click through the followingsequence of SPSS options.Analyze/General Linear Model/ UnivariateA. Chang1

3) In the Univariate dialog box, put the response variable in the Dependent Variable box, put theTreatment variable in the Fixed Factor box, and put the Subject variable in the RandomFactor box.4) Click on Model button in the Univariate dialog box, and first click on the drop-sown menubelow Build Term(s) title and select Main effects option, and then use the selection button toselect and select trtmt (Treatment) and subject variables as Main effects, and click Continue.A. Chang2

5) For performing Post Hoc analysis: First, click Post Hoc button in the Univariate dialogbox and the following dialog will appear. Select the trtmt variable in Post Hoc Tests for: boxand check S-N-K box and then click Continue button.6) For making a profile chart, in Univariate dialog box, click on Plot button. Putsubject variable in Horizontal Axis and put trtmt variable in Separate Lines. SPSSwill draw profile line chart. Each line in the chart will represent outcome from each ofthe treatment group. Click Add to add the chart to the list to be plotted, and click onContinue button.7) After all the options have been selected, click OK in the Univariate dialog box to execute theanalysis.A. Chang3

Output for Using Univariate Approach with Treatment as the Fixed Effect and theSubject as the Random EffectTests of Between-Subjects EffectsDependent Variable: ResponseSourceInterceptTRTMTType III Sumof Squares24021040.33HypothesisdfMean Square1 rorSUBJECT 7805.0006089.5006b1014.917ba. MS(SUBJECT)b. .75001.0001.0001.000Means for groups in homogeneous subsets are displayed.Based on Type III Sum of SquaresThe error term is Mean Square(Error) 1014.917.a. Uses Harmonic Mean Sample Size 4.000.b. Alpha .05.Estimated Marginal Means of Response20001800Estimated Marginal .003.004.00SubjectA. Chang4

Repeated-Measures Design Analysis (Multivariate Approach)1)2)3) Enter the number of treatment levels and click Add and click Define.A. Chang5

4) Select each of the factor level and click the triangle button until the three levels are all selected asin the second picture.5) Click the options button and select factor1 (the treatment variable) into Display Means for: box,and check Compare main effects and select the multiple comparison method listed in the Confidenceinterval adjustment and click continue and OK.A. Chang6

SPSS OutputMultivariate TestsbEffectFACTOR1Pillai's TraceWilks' LambdaHotelling's TraceRoy's Largest RootValue.994.006163.698163.698FHypothesis .000Error df2.0002.0002.0002.000Sig.006.006.006.006a. Exact statisticb.Design: InterceptWithin Subjects Design: FACTOR1Mauchly's Test of SphericitybMeasure: MEASURE 1EpsilonWithin Subjects EffectFACTOR1Approx.Chi-Square1.594Mauchly's 925Lower-bound.500Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables isproportional to an identity matrix.a. May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in theTests of Within-Subjects Effects table.b.Design: InterceptWithin Subjects Design: FACTOR1Tests of Within-Subjects EffectsMeasure: MEASURE 1SourceFACTOR1Error(FACTOR1)Sphericity ericity e III Sumof 8735.5533.000Mean 258.237Sig.000.000.000.001Tests of Between-Subjects EffectsMeasure: MEASURE 1Transformed Variable: AverageSourceInterceptErrorA. ChangType III Sumof Squares24021040.3173415.000df13Mean Square24021040.3357805.000F415.553Sig.0007

Pairwise ComparisonsMeasure: MEASURE 1(I) FACTOR1123(J) 237.250*-274.250*511.500*274.250*Std. 001.006.001.001.00195% Confidence Interval foraDifferenceLower Bound Upper 6-337.055-211.445372.731650.269211.445337.055Based on estimated marginal means*. The mean difference is significant at the .05 level.a. Adjustment for multiple comparisons: Bonferroni.A. Chang8

2) To run repeated measure analysis with univariate approach, click through the following sequence of SPSS options. Analyze/General Linear Model/ Univariate Set up of the

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