1. Latent profile analysis for the classification of OECD countries with health indicators
- Author
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Hülya Özen and Doğukan Özen
- Subjects
classification ,health equipment ,healthcare workers ,latent profile analysis ,oecd ,Medicine - Abstract
Aims: Health indicators provide up-to-date information on the health status of a population. This study aimed to classify the Organization for Economic Co-operation and Development (OECD) countries according to health indicators and assess their status. Methods: The dataset was obtained from the OECD and World Bank databases. The most recent data from 2018 to 2022 were used. The dataset included the number of hospital beds, computed tomography scanners, magnetic resonance imaging (MRI) units, mammography machines, and radiotherapy machines as indicators of health equipment and the number of doctors, nurses, medical graduates, and nursing graduates as indicators of healthcare workers. The classification was performed using latent profile analysis (LPA). Estimated classes were compared using ANOVA or the Kruskal-Wallis test. Results: Three distinct classes were obtained from the models constructed with LPA (Akaike information criteria: 1674.91, Bayesian information criteria: 1726.87, Lo-Mendell-Rubin adjusted likelihood ratio test: p
- Published
- 2024
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