data proc sort proc corr run proc reg run proc glm run proc glm run proc glm run proc reg CONMAIN CONINT run proc reg DUMMAIN DUMINT run proc reg
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1 data one; input id Y group X; I1=0;I2=0;I3=0;if group=1 then I1=1;if group=2 then I2=1;if group=3 then I3=1; IINT1=I1*X;IINT2=I2*X;IINT3=I3*X; *************************************************************************; if group=1 then C1=-1;if group=2 then C1=0;if group=3 then C1=1; if group=1 then C2=-1;if group=2 then C2=2;if group=3 then C2=-1; CINT1=C1*X;CINT2=C2*X; cards; ; proc sort data=one;by group; proc corr data=one;var y x;by group;run; proc reg data=one; model y = X ;by group;run; proc glm data=one;class group; model y = group ; means group;run; proc glm data=one;class group; model y = group X ; means group;lsmeans group;run; proc glm data=one;class group; model y = group x group*x / solution ; means group; lsmeans group / adjust=sidak tdiff; lsmeans group / adjust=tukey tdiff;run; proc reg data=one; model y = C1 C2 X CINT1 CINT2; CONMAIN: test C1=0, C2=0; CONINT: test CINT1=0, CINT2=0;run; proc reg data=one; model y = I2 I3 X IINT2 IINT3; DUMMAIN: test I2=0, I3=0; DUMINT: test IINT2=0, IINT3=0;run; proc reg data=one; model y = I1 I2 I3 IINT1 IINT2 IINT3 /noint ; CELLMAIN: test I1-I2=0, I2-I3=0; CELLINT: test IINT1-IINT2=0, IINT2-IINT3=0;run; 1
2 group= The CORR Procedure Simple Statistics Variable N Mean Std Dev Sum Minimum Maximum Y X Pearson Correlation Coefficients, N = 12 Prob > r under H0: Rho=0 Y X Y group= The CORR Procedure Simple Statistics Variable N Mean Std Dev Sum Minimum Maximum Y X Pearson Correlation Coefficients, N = 12 Prob > r under H0: Rho=0 Y X Y group= The CORR Procedure Simple Statistics Variable N Mean Std Dev Sum Minimum Maximum Y X Pearson Correlation Coefficients, N = 12 Prob > r under H0: Rho=0 Y X Y
3 group= The REG Procedure Model: MODEL1 Number of Observations Read 12 Number of Observations Used 12 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model Error Corrected Total Root MSE R-Square Dependent Mean Adj R-Sq Coeff Var Parameter Estimates Parameter Standard Variable DF Estimate Error t Value Pr > t Intercept X
4 group= The REG Procedure Model: MODEL1 Number of Observations Read 12 Number of Observations Used 12 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model Error Corrected Total Root MSE R-Square Dependent Mean Adj R-Sq Coeff Var Parameter Estimates Parameter Standard Variable DF Estimate Error t Value Pr > t Intercept X
5 group= The REG Procedure Model: MODEL1 Number of Observations Read 12 Number of Observations Used 12 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model Error Corrected Total Root MSE R-Square Dependent Mean Adj R-Sq Coeff Var Parameter Estimates Parameter Standard Variable DF Estimate Error t Value Pr > t Intercept X
6 The GLM Procedure Class Level Information Class Levels Values group Number of Observations Read 36 Number of Observations Used 36 Sum of Source DF Squares Mean Square F Value Pr > F Model <.0001 Error Corrected Total R-Square Coeff Var Root MSE Y Mean Source DF Type I SS Mean Square F Value Pr > F group <.0001 Source DF Type III SS Mean Square F Value Pr > F group <.0001 Level of Y group N Mean Std Dev
7 The GLM Procedure Class Level Information Class Levels Values group Number of Observations Read 36 Number of Observations Used 36 Sum of Source DF Squares Mean Square F Value Pr > F Model <.0001 Error Corrected Total R-Square Coeff Var Root MSE Y Mean Source DF Type I SS Mean Square F Value Pr > F group <.0001 X Source DF Type III SS Mean Square F Value Pr > F group <.0001 X Level of Y X group N Mean Std Dev Mean Std Dev Least Squares Means group Y LSMEAN
8 The GLM Procedure Class Level Information Class Levels Values group Number of Observations Read 36 Number of Observations Used 36 Sum of Source DF Squares Mean Square F Value Pr > F Model <.0001 Error Corrected Total R-Square Coeff Var Root MSE Y Mean Source DF Type I SS Mean Square F Value Pr > F group <.0001 X X*group Source DF Type III SS Mean Square F Value Pr > F group X X*group Standard Parameter Estimate Error t Value Pr > t Intercept B group B group B group B... X B X*group B X*group B X*group B... NOTE: The X'X matrix has been found to be singular, and a generalized inverse was used to solve the normal equations. Terms whose estimates are followed by the letter 'B' are not uniquely estimable. 8
9 Least Squares Means Level of Y X group N Mean Std Dev Mean Std Dev Y LSMEAN Total group y x Y = β + β LS ( j) 0( j) 1( j) X Y LS (1) = (13.75) = Y LS (2) = (13.75) = Y LS (3) = (13.75) = Sidak Least Squares Means for effect group t for H0: LSMean(i)=LSMean(j) / Pr > t i/j R Sq Linear = R Sq Linear = R Tukey Sq Linear = Least Squares Means for effect group R Sq Linear t for = H0: LSMean(i)=LSMean(j) / Pr > t i/j
10 The REG Procedure Number of Observations Read 36 Number of Observations Used 36 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model <.0001 Error Corrected Total Root MSE R-Square Dependent Mean Adj R-Sq Coeff Var Parameter Estimates Parameter Standard Variable DF Estimate Error t Value Pr > t Intercept C C X CINT CINT Test CONMAIN Results for Dependent Variable Y Mean Source DF Square F Value Pr > F Numerator Denominator Test CONINT Results for Dependent Variable Y Mean Source DF Square F Value Pr > F Numerator Denominator
11 The REG Procedure Number of Observations Read 36 Number of Observations Used 36 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model <.0001 Error Corrected Total Root MSE R-Square Dependent Mean Adj R-Sq Coeff Var Parameter Estimates Parameter Standard Variable DF Estimate Error t Value Pr > t Intercept I I X IINT IINT Test DUMMAIN Results for Dependent Variable Y Mean Source DF Square F Value Pr > F Numerator Denominator Test DUMINT Results for Dependent Variable Y Mean Source DF Square F Value Pr > F Numerator Denominator
12 The REG Procedure Number of Observations Read 36 Number of Observations Used 36 NOTE: No intercept in model. R-Square is redefined. Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model <.0001 Error Uncorrected Total Root MSE R-Square Dependent Mean Adj R-Sq Coeff Var Parameter Estimates Parameter Standard Variable DF Estimate Error t Value Pr > t I I I IINT IINT IINT Test CELLMAIN Results for Dependent Variable Y Mean Source DF Square F Value Pr > F Numerator Denominator Test CELLINT Results for Dependent Variable Y Mean Source DF Square F Value Pr > F Numerator Denominator
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