title: Heteroscedasticity as a Basis of Direction Dependence in Reversible Linear Regression Models.
abstract: Heteroscedasticity is a well-known issue in linear regression modeling. When heteroscedasticity is observed, researchers are advised to remedy possible model misspecification of the explanatory part of the model (e.g., considering alternative functional forms and/or omitted variables). The present contribution discusses another source of heteroscedasticity in observational data: Directional model misspecifications in the case of nonnormal variables. Directional misspecification refers to situations where alternative models are equally likely to explain the data-generating process (e.g., x → y versus y → x). It is shown that the homoscedasticity assumption is likely to be violated in models that erroneously treat true nonnormal predictors as response variables. Recently, Direction Dependence Analysis (DDA) has been proposed as a framework to empirically evaluate the direction of effects in linear models. The present study links the phenomenon of heteroscedasticity with DDA and describes visual diagnostics and nine homoscedasticity tests that can be used to make decisions concerning the direction of effects in linear models. Results of a Monte Carlo simulation that demonstrate the adequacy of the approach are presented. An empirical example is provided, and applicability of the methodology in cases of violated assumptions is discussed.
authors.affiliation: a University of Missouri.
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Wiedermann
authors.affiliation: b University of Vienna.
authors.forename: Richard
authors.initials: R
authors.lastname: Artner
authors.affiliation: c Michigan State University.
authors.forename: Alexander
authors.initials: A
authors.lastname: von Eye
mesh_terms: D000465:Algorithms; D002648:Child; D002657:Child Development; D003071:Cognition; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D055641:Mathematical Concepts; D009010:Monte Carlo Method; D015999:Multivariate Analysis; D017711:Nonlinear Dynamics; D016011:Normal Distribution; D064887:Observational Studies as Topic; D011581:Psychological Tests; D012984:Software
keywords: Direction dependence analysis; heteroscedasticity; linear regression model; nonnormality