![]() ![]() The results are consistent with those of the ANOVA. As height is probably correlated with weight, this couldīelow we perform a standard ANCOVA. The ANOVA disregards the information that we have about the subject’s The two diets, and a difference between diet 1 and diet 2. The ANOVA results show an overall difference among all of the dietsĪnd the contrasts show a difference between the control group and The /contrast subcommand to compare the two diets (1 and 2) to the control This analysis compares the weights of the three groups. You could analyze this data with a standard ANOVA, as shown below. Height of the subject was measured, and after the study the Who used one of three diets, diet 1 (diet=1), diet 2 (diet=2) andĪ control group (diet=3). Here is an example data file we will use. The glm command, especially the lmatrix subcommand. This involves some complex topics in the use of When you have heterogeneous (different) regressions across groupsĪnd show some strategies for dealing with them. Include both categorical and continuous variables in a single model.ĪNCOVA assumes that the regression coefficients are homogeneous (the same)Īcross the categorical variable. Perform tests with separate slopes for allħ.2 Comparing diet groups 1 and 2 when pooling slopes forħ.3 Comparing diet groups 2 and 3 when pooling slopesĪnalysis of covariance (ANCOVA) is a statistical procedure that allows you to Test equality of slopes across diet groupsĥ. ![]()
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