Repeated Measures Part 2: Cartoon data
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1 Repeated Measures Part 2: Cartoon data /*********************** cartoonglm.sas ******************/ options linesize=79 noovp formdlim='_'; title 'Cartoon Data: STA442/1008 F 2005'; proc format; /* value labels used in data step below */ value cfmt 0 = 'Black & White' 1 = 'Colour'; data disney; infile 'cartoon.dat'; input id colour educ location otis cartoon1 real1 cartoon2 real2; label colour = 'Colour versus Black & white training materials' educ = 'Education' location = 'Where did respondent come from?' otis = 'Otis Mental Ability Test' cartoon1 = 'Cartoon test score at time 1' real1 = 'Realistic test score at time 1' cartoon2 = 'Cartoon test score at time 2' real2 = 'Realistic test score at time 2' memory = 'Recall of training materials' type = 'Training materials: Cartoon versus realistic '; format colour cfmt.; util = real2+cartoon2; if util =. then miss2='yes'; else miss2='no '; label miss2 = 'Time 2 data missing'; proc glm; title2 ''; class colour; model real1 real2 cartoon1 cartoon2 = colour / nouni; repeated r_vs_car 2, time 2 / short summary; means colour; proc glm; title2 ''; class colour; model real1 real2 cartoon1 cartoon2 = otis colour / nouni; repeated r_vs_car 2, time 2 / short summary; lsmeans colour; proc ttest; title2 'Time 2 missing at random?'; class miss2; var real1 cartoon1 otis; page numberspage numbers Page 1 of 15
2 Cartoon Data: STA442/1008 F Class Level Information Class Levels Values colour 2 Black & White Colour Number of observations 179 NOTE: Observations with missing values will not be included in this analysis. Thus, only 104 observations can be used in this analysis. Cartoon Data: STA442/1008 F Repeated Measures Level Information Dependent Variable real1 real2 cartoon1 cartoon2 Level of r_vs_car Level of time Manova Test Criteria and Exact F Statistics for the Hypothesis of no r_vs_car Effect H = Type III SSCP Matrix for r_vs_car S=1 M=-0.5 N=50 Wilks' Lambda <.0001 Pillai's Trace <.0001 Hotelling-Lawley Trace <.0001 Roy's Greatest Root <.0001 Page 2 of 15
3 Manova Test Criteria and Exact F Statistics for the Hypothesis of no r_vs_car*colour Effect H = Type III SSCP Matrix for r_vs_car*colour S=1 M=-0.5 N=50 Wilks' Lambda Pillai's Trace Hotelling-Lawley Trace Roy's Greatest Root Manova Test Criteria and Exact F Statistics for the Hypothesis of no time Effect H = Type III SSCP Matrix for time S=1 M=-0.5 N=50 Wilks' Lambda <.0001 Pillai's Trace <.0001 Hotelling-Lawley Trace <.0001 Roy's Greatest Root <.0001 Cartoon Data: STA442/1008 F Manova Test Criteria and Exact F Statistics for the Hypothesis of no time*colour Effect H = Type III SSCP Matrix for time*colour S=1 M=-0.5 N=50 Wilks' Lambda Pillai's Trace Hotelling-Lawley Trace Roy's Greatest Root Page 3 of 15
4 Manova Test Criteria and Exact F Statistics for the Hypothesis of no r_vs_car*time Effect H = Type III SSCP Matrix for r_vs_car*time S=1 M=-0.5 N=50 Wilks' Lambda Pillai's Trace Hotelling-Lawley Trace Roy's Greatest Root Manova Test Criteria and Exact F Statistics for the Hypothesis of no r_vs_car*time*colour Effect H = Type III SSCP Matrix for r_vs_car*time*colour S=1 M=-0.5 N=50 Wilks' Lambda Pillai's Trace Hotelling-Lawley Trace Roy's Greatest Root Cartoon Data: STA442/1008 F Tests of Hypotheses for Between Subjects Effects colour Error Page 4 of 15
5 Cartoon Data: STA442/1008 F Univariate Tests of Hypotheses for Within Subject Effects r_vs_car <.0001 r_vs_car*colour Error(r_vs_car) time <.0001 time*colour Error(time) r_vs_car*time r_vs_car*time*colour Error(r_vs_car*time) Cartoon Data: STA442/1008 F Analysis of Variance of Contrast Variables r_vs_car_n represents the contrast between the nth level of r_vs_car and the last Contrast Variable: r_vs_car_1 Mean <.0001 colour Error Page 5 of 15
6 Cartoon Data: STA442/1008 F Analysis of Variance of Contrast Variables time_n represents the contrast between the nth level of time and the last Contrast Variable: time_1 Mean <.0001 colour Error Cartoon Data: STA442/1008 F Analysis of Variance of Contrast Variables r_vs_car_n represents the contrast between the nth level of r_vs_car and the last time_n represents the contrast between the nth level of time and the last Contrast Variable: r_vs_car_1*time_1 Mean colour Error Page 6 of 15
7 Cartoon Data: STA442/1008 F Level of real real colour N Mean Std Dev Mean Std Dev Black & White Colour Level of cartoon cartoon colour N Mean Std Dev Mean Std Dev Black & White Colour Cartoon Data: STA442/1008 F Class Level Information Class Levels Values colour 2 Black & White Colour Number of observations 179 NOTE: Observations with missing values will not be included in this analysis. Thus, only 104 observations can be used in this analysis. Cartoon Data: STA442/1008 F Repeated Measures Level Information Dependent Variable real1 real2 cartoon1 cartoon2 Level of r_vs_car Level of time Page 7 of 15
8 Manova Test Criteria and Exact F Statistics for the Hypothesis of no r_vs_car Effect H = Type III SSCP Matrix for r_vs_car Wilks' Lambda Pillai's Trace Hotelling-Lawley Trace Roy's Greatest Root Manova Test Criteria and Exact F Statistics for the Hypothesis of no r_vs_car*otis Effect H = Type III SSCP Matrix for r_vs_car*otis Wilks' Lambda Pillai's Trace Hotelling-Lawley Trace Roy's Greatest Root Manova Test Criteria and Exact F Statistics for the Hypothesis of no r_vs_car*colour Effect H = Type III SSCP Matrix for r_vs_car*colour Wilks' Lambda Pillai's Trace Hotelling-Lawley Trace Roy's Greatest Root Cartoon Data: STA442/1008 F Page 8 of 15
9 Manova Test Criteria and Exact F Statistics for the Hypothesis of no time Effect H = Type III SSCP Matrix for time Wilks' Lambda Pillai's Trace Hotelling-Lawley Trace Roy's Greatest Root Manova Test Criteria and Exact F Statistics for the Hypothesis of no time*otis Effect H = Type III SSCP Matrix for time*otis Wilks' Lambda Pillai's Trace Hotelling-Lawley Trace Roy's Greatest Root Manova Test Criteria and Exact F Statistics for the Hypothesis of no time*colour Effect H = Type III SSCP Matrix for time*colour Wilks' Lambda Pillai's Trace Hotelling-Lawley Trace Roy's Greatest Root Page 9 of 15
10 Cartoon Data: STA442/1008 F Manova Test Criteria and Exact F Statistics for the Hypothesis of no r_vs_car*time Effect H = Type III SSCP Matrix for r_vs_car*time Wilks' Lambda Pillai's Trace Hotelling-Lawley Trace Roy's Greatest Root Manova Test Criteria and Exact F Statistics for the Hypothesis of no r_vs_car*time*otis Effect H = Type III SSCP Matrix for r_vs_car*time*otis Wilks' Lambda Pillai's Trace Hotelling-Lawley Trace Roy's Greatest Root Manova Test Criteria and Exact F Statistics for the Hypothesis of no r_vs_car*time*colour Effect H = Type III SSCP Matrix for r_vs_car*time*colour Wilks' Lambda Pillai's Trace Hotelling-Lawley Trace Roy's Greatest Root Page 10 of 15
11 Cartoon Data: STA442/1008 F Tests of Hypotheses for Between Subjects Effects otis <.0001 colour Error Cartoon Data: STA442/1008 F Univariate Tests of Hypotheses for Within Subject Effects r_vs_car r_vs_car*otis r_vs_car*colour Error(r_vs_car) time time*otis time*colour Error(time) r_vs_car*time r_vs_car*time*otis r_vs_car*time*colour Error(r_vs_car*time) Page 11 of 15
12 Cartoon Data: STA442/1008 F Analysis of Variance of Contrast Variables r_vs_car_n represents the contrast between the nth level of r_vs_car and the last Contrast Variable: r_vs_car_1 Mean otis colour Error Cartoon Data: STA442/1008 F Analysis of Variance of Contrast Variables time_n represents the contrast between the nth level of time and the last Contrast Variable: time_1 Mean otis colour Error Page 12 of 15
13 Cartoon Data: STA442/1008 F Analysis of Variance of Contrast Variables r_vs_car_n represents the contrast between the nth level of r_vs_car and the last time_n represents the contrast between the nth level of time and the last Contrast Variable: r_vs_car_1*time_1 Mean otis colour Error Cartoon Data: STA442/1008 F Least Squares Means cartoon1 cartoon2 colour real1 LSMEAN real2 LSMEAN LSMEAN LSMEAN Black & White Colour Page 13 of 15
14 Cartoon Data: STA442/1008 F Time 2 missing at random? Class Level Information Class Levels Values miss2 2 No Yes Number of observations 179 Cartoon Data: STA442/1008 F Time 2 missing at random? Dependent Variable: real1 Realistic test score at time 1 Sum of Source DF Squares Mean Square F Value Pr > F Model Error Corrected Total R-Square Coeff Var Root MSE real1 Mean Source DF Type I SS Mean Square F Value Pr > F miss miss Page 14 of 15
15 Cartoon Data: STA442/1008 F Time 2 missing at random? 11:01 Friday, November 25, 2005 The TTEST Procedure Statistics Lower CL Upper CL Lower CL Variable miss2 N Mean Mean Mean Std Dev Std Dev real1 No real1 Yes real1 Diff (1-2) cartoon1 No cartoon1 Yes cartoon1 Diff (1-2) otis No otis Yes otis Diff (1-2) Statistics Upper CL Variable miss2 Std Dev Std Err Minimum Maximum real1 No real1 Yes real1 Diff (1-2) cartoon1 No cartoon1 Yes cartoon1 Diff (1-2) otis No otis Yes otis Diff (1-2) T-Tests Variable Method Variances DF t Value Pr > t real1 Pooled Equal real1 Satterthwaite Unequal cartoon1 Pooled Equal cartoon1 Satterthwaite Unequal otis Pooled Equal otis Satterthwaite Unequal Page 15 of 15 Equality of Variances Variable Method Num DF Den DF F Value Pr > F real1 Folded F cartoon1 Folded F otis Folded F
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