A New SEYHAN's Approach in Case of Heterogeneity of Regression Slopes in ANCOVA
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Date
2018
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Heidelberg
Access Rights
info:eu-repo/semantics/closedAccess
Abstract
In this study, when the assumptions of linearity and homogeneity of regression slopes of conventional ANCOVA are not met, a new approach named as SEYHAN has been suggested to use conventional ANCOVA instead of robust or nonlinear ANCOVA. The proposed SEYHAN's approach involves transformation of continuous covariate into categorical structure when the relationship between covariate and dependent variable is nonlinear and the regression slopes are not homogenous. A simulated data set was used to explain SEYHAN's approach. In this approach, we performed conventional ANCOVA in each subgroup which is constituted according to knot values and analysis of variance with two-factor model after MARS method was used for categorization of covariate. The first model is a simpler model than the second model that includes interaction term. Since the model with interaction effect has more subjects, the power of test also increases and the existing significant difference is revealed better. We can say that linearity and homogeneity of regression slopes are not problem for data analysis by conventional linear ANCOVA model by helping this approach. It can be used fast and efficiently for the presence of one or more covariates.
Description
Ankarali, Handan Camdeviren/0000-0002-3613-0523; ankarali, seyit/0000-0003-3752-0846
WOS: 000432000500006
PubMed: 27757767
WOS: 000432000500006
PubMed: 27757767
Keywords
ANCOVA, Homogeneity of regression slopes, Generalized Johnson-Neyman, Nonlinear ANCOVA, Robust ANCOVA
Journal or Series
Interdisciplinary Sciences-Computational Life Sciences
WoS Q Value
Q3
Scopus Q Value
Q2
Volume
10
Issue
2
