{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:20:04Z","timestamp":1760242804490,"version":"build-2065373602"},"reference-count":43,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2016,11,28]],"date-time":"2016-11-28T00:00:00Z","timestamp":1480291200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Several factors may influence children\u2019s lifestyle. The main purpose of this study is to introduce a children\u2019s lifestyle index framework and model it based on structural equation modeling (SEM) with Maximum likelihood (ML) and Bayesian predictors. This framework includes parental socioeconomic status, household food security, parental lifestyle, and children\u2019s lifestyle. The sample for this study involves 452 volunteer Chinese families with children 7\u201312 years old. The experimental results are compared in terms of root mean square error, coefficient of determination, mean absolute error, and mean absolute percentage error metrics. An analysis of the proposed causal model suggests there are multiple significant interconnections among the variables of interest. According to both Bayesian and ML techniques, the proposed framework illustrates that parental socioeconomic status and parental lifestyle strongly impact children\u2019s lifestyle. The impact of household food security on children\u2019s lifestyle is rejected. However, there is a strong relationship between household food security and both parental socioeconomic status and parental lifestyle. Moreover, the outputs illustrate that the Bayesian prediction model has a good fit with the data, unlike the ML approach. The reasons for this discrepancy between ML and Bayesian prediction are debated and potential advantages and caveats with the application of the Bayesian approach in future studies are discussed.<\/jats:p>","DOI":"10.3390\/sym8120141","type":"journal-article","created":{"date-parts":[[2016,11,28]],"date-time":"2016-11-28T10:25:22Z","timestamp":1480328722000},"page":"141","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Comparing Bayesian and Maximum Likelihood Predictors in Structural Equation Modeling of Children\u2019s Lifestyle Index"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7727-2077","authenticated-orcid":false,"given":"Che","family":"Radzi","sequence":"first","affiliation":[{"name":"Department of Science and Technology Studies, Faculty of Science, University of Malaya, Kuala Lumpur 50603, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huang","family":"Hui","sequence":"additional","affiliation":[{"name":"Department of Science and Technology Studies, Faculty of Science, University of Malaya, Kuala Lumpur 50603, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hashem","family":"Salarzadeh Jenatabadi","sequence":"additional","affiliation":[{"name":"Department of Science and Technology Studies, Faculty of Science, University of Malaya, Kuala Lumpur 50603, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,11,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1816","DOI":"10.1016\/j.socscimed.2010.01.040","article-title":"Do working mothers raise couch potato kids? 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