%0 Journal Article
%J Alzheimer's & Dementia: Translational Research & Clinical Interventions
%D 2020
%T Comparison of Cox proportional hazards regression and generalized Cox regression models applied in dementia risk prediction
%A Goerdten, Jantje
%A Carrière, Isabelle
%A Muniz-Terrera, Graciela
%K Cox proportional hazards regression
%K Dementia
%K dementia risk model
%K Prediction
%K splines
%X Abstract Introduction The frequently used Cox regression applies two critical assumptions, which might not hold for all predictors. In this study, the results from a Cox regression model (CM) and a generalized Cox regression model (GCM) are compared. Methods Data are from the Survey of Health, Ageing and Retirement in Europe (SHARE), which includes approximately 140,000 individuals aged 50 or older followed over seven waves. CMs and GCMs are used to estimate dementia risk. The results are internally and externally validated. Results None of the predictors included in the analyses fulfilled the assumptions of Cox regression. Both models predict dementia moderately well (10-year risk: 0.737; 95% confidence interval [CI]: 0.699, 0.773; CM and 0.746; 95% CI: 0.710, 0.785; GCM). Discussion The GCM performs significantly better than the CM when comparing pseudo-R2 and the log-likelihood. GCMs enable researcher to test the assumptions used by Cox regression independently and relax these assumptions if necessary.
%B Alzheimer's & Dementia: Translational Research & Clinical Interventions
%V 6
%G eng
%N 1
%R 10.1002/trc2.12041
%0 Journal Article
%J Collabra: Psychology
%D 2020
%T Is Healthy Neuroticism Associated with Health Behaviors? A Coordinated Integrative Data Analysis
%A Graham, Eileen
%A Sara J Weston
%A Nicholas A. Turiano
%A Ashwanden, Damaris
%A Booth, Tom
%A Harrison, Fleur
%A James, Byran
%A Nathan A Lewis
%A Makkar, Steven
%A Mueller, Swantje
%A Wisniewski, Kristi
%A Yoneda, Tomiko
%A Zhaoyang, Ruixue
%A Avron Spiro III
%A Willis, Sherry
%A K. Warner Schaie
%A Sliwinski, Martin
%A Lipton, Richard
%A Katz, Mindy
%A Ian J Deary
%A Elizabeth Zelinski
%A David A. Bennett
%A Sachdev, P S
%A Brodaty, H
%A Troller, Julian
%A Ames, David
%A Margaret J Wright
%A Denis Gerstorf
%A Allemand, Mathias
%A Drewelies, Johanna
%A Wagner, Gert G
%A Muniz-Terrera, Graciela
%A Andrea M Piccinin
%A Scott M Hofer
%A Daniel K. Mroczek
%K Coordinated IDA
%K Health behaviors
%K Healthy Neuroticism
%X Current literature suggests that neuroticism is positively associated with maladaptive life choices, likelihood of disease, and mortality. However, recent research has identified circumstances under which neuroticism is associated with positive outcomes. The current project examined whether “healthy neuroticism”, defined as the interaction of neuroticism and conscientiousness, was associated with the following health behaviors: smoking, alcohol consumption, and physical activity. Using a pre-registered multi-study coordinated integrative data analysis (IDA) approach, we investigated whether “healthy neuroticism” predicted the odds of engaging in each of the aforementioned activities. Each study estimated identical models, using the same covariates and data transformations, enabling optimal comparability of results. These results were then meta-analyzed in order to estimate an average (N-weighted) effect and to ascertain the extent of heterogeneity in the effects. Overall, these results suggest that neuroticism alone was not related to health behaviors, while individuals higher in conscientiousness were less likely to be smokers or drinkers, and more likely to engage in physical activity. In terms of the healthy neuroticism interaction of neuroticism and conscientiousness, significant interactions for smoking and physical activity suggest that the association between neuroticism and health behaviors was smaller among those high in conscientiousness. These findings lend credence to the idea that healthy neuroticism may be linked to certain health behaviors and that these effects are generalizable across several heterogeneous samples.
%B Collabra: Psychology
%V 6
%G eng
%N 1
%R http://doi.org/10.1525/collabra.266