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Comparative Analysis of Some Structural Equation Model Estimation Methods with Application to Coronary Heart Disease Risk
Joint Authors
Adedia, David
Adebanji, Atinuke O.
Appiah, Simon Kojo
Source
Journal of Probability and Statistics
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-22
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
This study compared a ridge maximum likelihood estimator to Yuan and Chan (2008) ridge maximum likelihood, maximum likelihood, unweighted least squares, generalized least squares, and asymptotic distribution-free estimators in fitting six models that show relationships in some noncommunicable diseases.
Uncontrolled hypertension has been shown to be a leading cause of coronary heart disease, kidney dysfunction, and other negative health outcomes.
It poses equal danger when asymptomatic and undetected.
Research has also shown that it tends to coexist with diabetes mellitus (DM), with the presence of DM doubling the risk of hypertension.
The study assessed the effect of obesity, type II diabetes, and hypertension on coronary risk and also the existence of converse relationship with structural equation modelling (SEM).
The results showed that the two ridge estimators did better than other estimators.
Nonconvergence occurred for most of the models for asymptotic distribution-free estimator and unweighted least squares estimator whilst generalized least squares estimator had one nonconvergence of results.
Other estimators provided competing outputs, but unweighted least squares estimator reported unreliable parameter estimates such as large chi-square test statistic and root mean square error of approximation for Model 3.
The maximum likelihood family of estimators did better than others like asymptotic distribution-free estimator in terms of overall model fit and parameter estimation.
Also, the study found that increase in obesity could result in a significant increase in both hypertension and coronary risk.
Diastolic blood pressure and diabetes have significant converse effects on each other.
This implies those who are hypertensive can develop diabetes and vice versa.
American Psychological Association (APA)
Adedia, David& Adebanji, Atinuke O.& Appiah, Simon Kojo. 2020. Comparative Analysis of Some Structural Equation Model Estimation Methods with Application to Coronary Heart Disease Risk. Journal of Probability and Statistics،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1190171
Modern Language Association (MLA)
Adedia, David…[et al.]. Comparative Analysis of Some Structural Equation Model Estimation Methods with Application to Coronary Heart Disease Risk. Journal of Probability and Statistics No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1190171
American Medical Association (AMA)
Adedia, David& Adebanji, Atinuke O.& Appiah, Simon Kojo. Comparative Analysis of Some Structural Equation Model Estimation Methods with Application to Coronary Heart Disease Risk. Journal of Probability and Statistics. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1190171
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1190171