A recent study by Feng et al. [Feng S, Krueger A, Oppenheimer M (2010) Proc Natl Acad Sci USA 107:14257-14262] in PNAS reported statistical evidence of a weather-driven causal effect of crop yields on human migration from Mexico to the United States. We show that this conclusion is based on a different statistical model than the one stated in the paper. When we correct for this mistake, there is no evidence of a causal link.
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http://dx.doi.org/10.1073/pnas.1202049109 | DOI Listing |
Cad Saude Publica
January 2025
Instituto de Investigaciones en Ciencias de la Salud, Universidad Nacional de Córdoba, Córdoba, Argentina.
This study aimed to identify latent (unobservable) dimensions representing specific physical activity-related behaviors and explore their potential effects on obesity burden and spatial distribution in Colombia. A cross-sectional study (n = 9,658) was conducted based on the Colombian National Survey of Nutritional Status. A generalized structural equations model was proposed, combining exposure and measurement models to define a disease model.
View Article and Find Full Text PDFJ Chem Phys
January 2025
Department of Chemistry and Oden Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas 78712, USA.
Inferring underlying microscopic dynamics from low-dimensional experimental signals is a central problem in physics, chemistry, and biology. As a trade-off between molecular complexity and the low-dimensional nature of experimental data, mesoscopic descriptions such as the Markovian master equation are commonly used. The states in such descriptions usually include multiple microscopic states, and the ensuing coarse-grained dynamics are generally non-Markovian.
View Article and Find Full Text PDFJ Appl Stat
May 2024
Department of Community Health and Epidemiology, Faculty of Medicine, Dalhousie University, Halifax, CA, Canada.
Survival analysis often involves modeling hazard functions while considering frailty to account for unobserved cluster-level factors in clustered survival data. Shared frailty models have gained popularity for this purpose, but assessing covariate functional form in these models presents unique challenges. Martingale and deviance residuals are commonly used for visually assessing covariate functional form against continuous covariates.
View Article and Find Full Text PDFJ Appl Stat
May 2024
Institute of Mathematical and Computer Sciences, University of São Paulo, São Carlos, São Paulo, Brazil.
Survival data analysis often uses the Cox proportional hazards (PH) model. This model is widely applied due to its straightforward interpretation of the hazard ratio under the assumption that the hazard rates for two subjects remain constant over time. However, in several randomized clinical trials with long-term survival data comparing two new treatments, it is frequently observed that Kaplan-Meier plots exhibit crossing survival curves.
View Article and Find Full Text PDFConserv Biol
January 2025
Chair of Wildlife Ecology and Management, Albert Ludwigs University of Freiburg, Freiburg, Germany.
Survival and cause-specific mortality rates are vital for evidence-based population forecasting and conservation, particularly for large carnivores, whose populations are often vulnerable to human-caused mortalities. It is therefore important to know the relationship between anthropogenic and natural mortality causes to evaluate whether they are additive or compensatory. Further, the relation between survival and environmental covariates could reveal whether specific landscape characteristics influence demographic performance.
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