Introduction The relationship between clinical pathological conditions in older adults as depression, sarcopenia and cognitive status has been investigated among different populations using different statistical models [1,2,3]. A multivariate regression model has been used by Lyu et al. to investigate specific factors that could predict depression, building a structural equation model [4]. One study tried to assess this causal relationship with the use of Path Analysis [5]. In literature, logistic regression is compared to SEM models in different works [6-8].
THE BEST STATISTICAL MODEL TO ASSESS THE RELATIONSHIP BETWEEN DEPRESSION, COGNITIVE IMPAIRMENT, SARCOPENIA AND FRAILTY: DATA FROM A RETROSPECTIVE STUDY OF S.I.M.M.S. PROJECT
Lorusso Letizia;Bartolomeo Nicola;Trerotoli Paolo
2023-01-01
Abstract
Introduction The relationship between clinical pathological conditions in older adults as depression, sarcopenia and cognitive status has been investigated among different populations using different statistical models [1,2,3]. A multivariate regression model has been used by Lyu et al. to investigate specific factors that could predict depression, building a structural equation model [4]. One study tried to assess this causal relationship with the use of Path Analysis [5]. In literature, logistic regression is compared to SEM models in different works [6-8].File in questo prodotto:
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