title: A strategy to evaluate a covariate by group interaction in an analysis of covariance.
abstract: Analysis of covariance (ANCOVA) is commonly used in psychiatric research to statistically adjust for illness severity when making group comparisons. A fundamental assumption of the procedure is that the groups' differences in outcome are constant across all levels of baseline severity. This is the classic assumption of equal linear slopes. The plausibility of this assumption is rarely reported in manuscripts that use an ANCOVA. A statistical model is discussed that can be used to test the assumption, and if the assumption is not fulfilled, the model can incorporate a covariate by group interaction. An application of this model, the multiple linear regression approach to analysis of covariance, is provided using data from a large clinical trial for patients with panic disorder. The authors recommend that manuscripts reporting results from an ANCOVA also report the results of the test of the covariate by group interaction and account for the interaction when the slopes are heterogeneous.
authors.affiliation: Department of Psychiatry, Cornell University Medical College, New York, NY 10021, USA.
authors.forename: A C
authors.initials: AC
authors.lastname: Leon
authors.forename: L
authors.initials: L
authors.lastname: Portera
authors.forename: K
authors.initials: K
authors.lastname: Lowell
authors.forename: D
authors.initials: D
authors.lastname: Rheinheimer
mesh_terms: D000525:Alprazolam / Q000627:therapeutic use; D000704:Analysis of Variance; D014151:Anti-Anxiety Agents / Q000627:therapeutic use; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D016584:Panic Disorder / Q000188:drug therapy / Q000523:psychology; D011570:Psychiatry / Q000379:methods*; D012107:Research Design
chemical_list: D014151:Anti-Anxiety Agents; D000525:Alprazolam