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Does using stepwise variable selection to build sequential path analysis models make sense?

delete2010-12-08
delete6
PRE
AI
M
Marcin Kozak *
R
Ricardo Antunes Azevedo
DOI:10.1111/j.1399-3054.2010.01431.xdelete
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Abstract

Abstract

En 中文
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.
Keywords:
GRAIN-YIELD
TRAITS
LEAVES
L.
INTERRELATIONSHIPS
GENOTYPES
GRADIENT
CLIMATE
PLANT
AREA
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Physiologia Plantarum cover
Physiologia Plantarum
IF:
3.6
Papers:
6.8K
Citations:
2.0W

Organization

W
Warsaw University of Life Sciences
Scholars:
5.2K
Papers: 4.4K
Citations: 4.3K
U
universidade de sao paulo
Scholars:
10.6W
Papers: 6.7W
Citations: 93
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