dc.creatorKOZAK, Marcin
dc.creatorAZEVEDO, Ricardo A.
dc.date.accessioned2012-10-19T02:26:56Z
dc.date.accessioned2018-07-04T14:53:57Z
dc.date.available2012-10-19T02:26:56Z
dc.date.available2018-07-04T14:53:57Z
dc.date.created2012-10-19T02:26:56Z
dc.date.issued2011
dc.identifierPHYSIOLOGIA PLANTARUM, v.141, n.3, p.197-200, 2011
dc.identifier0031-9317
dc.identifierhttp://producao.usp.br/handle/BDPI/19198
dc.identifier10.1111/j.1399-3054.2010.01431.x
dc.identifierhttp://dx.doi.org/10.1111/j.1399-3054.2010.01431.x
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1615988
dc.description.abstractCausal 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.
dc.languageeng
dc.publisherWILEY-BLACKWELL
dc.relationPhysiologia Plantarum
dc.rightsCopyright WILEY-BLACKWELL
dc.rightsrestrictedAccess
dc.titleDoes using stepwise variable selection to build sequential path analysis models make sense?
dc.typeArtículos de revistas


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