title: Does using stepwise variable selection to build sequential path analysis models make sense?
abstract: Causal inference methods--mainly path analysis and structural equation modeling--offer plant physiologists information about cause-and-effect relationships among plant traits. Recently, an unusual approach to causal inference through stepwise variable selection has been proposed and used in various works on plant physiology. The approach should not be considered correct from a biological point of view. Here, it is explained why stepwise variable selection should not be used for causal inference, and shown what strange conclusions can be drawn based upon the former analysis when one aims to interpret cause-and-effect relationships among plant traits.
authors.affiliation: Department of Experimental Design and Bioinformatics, Faculty of Agriculture and Biology, Warsaw University of Life Sciences, Nowoursynowska 159, 02-776 Warsaw, Poland. nyggus@gmail.com
authors.forename: Marcin
authors.initials: M
authors.lastname: Kozak
authors.forename: Ricardo A
authors.initials: RA
authors.lastname: Azevedo
mesh_terms: D015233:Models, Statistical; D008962:Models, Theoretical; D018521:Plant Physiological Phenomena; D010944:Plants / Q000235:genetics