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. 2023 Feb 22:14:1060963.
doi: 10.3389/fpsyg.2023.1060963. eCollection 2023.

Evaluation of depression and obesity indices based on applications of ANOVA, regression, structural equation modeling and Taguchi algorithm process

Nur Anisah Mohamed  1 , Ayed R A Alanzi  2 , Noor Azlinna Azizan  3 , Suzana Ariff Azizan  4 , Nadia Samsudin  4   5 , Hashem Salarzadeh Jenatabadi  4
Affiliations

Evaluation of depression and obesity indices based on applications of ANOVA, regression, structural equation modeling and Taguchi algorithm process

Nur Anisah Mohamed et al. Front Psychol. .

Abstract

Introduction: Depression and obesity are the main threat among women which have been considered by many research scholars in psychology studies. In their analysis for measuring and estimating obesity and depression they were involving statistical functions.

Methods: Regression, Analysis of Variance (ANOVA), and in the last two decades Structural Equation Modeling are the most familiar statistical methods among research scholars. Taguchi algorism process is one the statistical methods which mostly have been applying in engineering studies. In this study we are looking at two main objectives. The first one is to introduce Taguchi algorism process and apply it in a case study in psychology area. The second objective is challenging among four statistical techniques include ANOVA, regression, SEM, and Taguchi technique in a same data. To achieve those aims we involved depression and obesity indices with other familiar indicators contain socioeconomic, screen time, sleep time, and usage fitness and nutrition mobile applications.

Results and discussion: Outputs proved that Taguchi technique is able to analyze some correlations which are not achieved by applying ANOVA, regression, and SEM. Moreover, SEM has a special capability to estimate some hidden correlations which are not possible to evaluate them by using ANOVA, regression, and even Taguchi method. In the last, we found that some correlations are significant by SEM, however, in the same data with regression those correlation were not significant. This paper could be a warning for psychology research scholars to be more careful with involving statistical methods for measuring and estimating of their research variables.

Keywords: Taguchi; experimental design; mHealth apps; obesity and depression; women’s obesity.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
SEM outputs (dependent variables: Depression and BMI).
Figure 2
Figure 2
Taguchi output for BMI pattern with MINITAB software.
Figure 3
Figure 3
Taguchi output for depression pattern with MINITAB software.
See this image and copyright information in PMC

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