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Network analysis facilitates examination of the interactions between different populations in a community. It can provide a range of metrics describing the social characteristics of each population and emergent structural properties of the community, which may be used to address novel ecological questions. Using a publicly available dataset, this chapter provides point-by-point code and instructions to infer and analyze a SPIEC-EASI (SParse InversE Covariance Estimation for Ecological Association Inference) network using free, open source software (R and Gephi).
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http://dx.doi.org/10.1007/978-1-0716-1040-4_14 | DOI Listing |
Clin Anat
September 2025
Department of Communication Disorders and Sciences, Rush University Medical Center, Chicago, Illinois, USA.
This research sought to examine the prevalence and severity of hyperostosis frontalis interna (HFI) in the Chicagoland anatomical body donor population. The study further aimed to elucidate potential demographic risk factors for HFI, including sex, age at death, and structural vulnerability index (SVI), as well as any common comorbidities, as gleaned from death certificates. HFI is an irregular bony overgrowth of the endocranial surface of the frontal bone.
View Article and Find Full Text PDFHum Reprod Open
August 2025
Department of Clinical Laboratory, Institute of Translational Medicine, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
Study Question: Do social determinants of health (SDoH) influence the age at menopause among women?
Summary Answer: In our study, adverse SDoH, particularly family low income-to-poverty ratio (PIR), low education level, and the marital status of being widowed, are associated with earlier age at menopause.
What Is Known Already: Some prior studies have considered certain SDoH variables (such as educational attainment and marital status) as potential factors influencing age at menopause, but systematic evidence clearly defining the relationship between multidimensional SDoH and menopausal age remains lacking.
Study Design Size Duration: This cross-sectional analysis included 6083 naturally menopausal women from 10 cycles (1999-2018) of the United States National Health and Nutrition Examination Survey (NHANES) and excluded cases of surgical menopause.
Bayesian Anal
January 2025
Department of Statistics, University of Washington, Seattle, USA.
We introduce the BREASE framework for the Bayesian analysis of randomized controlled trials with binary treatment and outcome. Approaching the problem from a causal inference perspective, we propose parameterizing the likelihood in terms of the aseline isk, fficacy, and dverse ide ffects of the treatment, along with a flexible, yet intuitive and tractable jointly independent beta prior distribution on these parameters, which we show to be a generalization of the Dirichlet prior for the joint distribution of potential outcomes. Our approach has a number of desirable characteristics when compared to current mainstream alternatives: (i) it naturally induces prior dependence between expected outcomes in the treatment and control groups; (ii) as the baseline risk, efficacy and risk of adverse side effects are quantities commonly present in the clinicians' vocabulary, the hyperparameters of the prior are directly interpretable, thus facilitating the elicitation of prior knowledge and sensitivity analysis; and (iii) we provide analytical formulae for the marginal likelihood, Bayes factor, and other posterior quantities, as well as an exact posterior sampling algorithm and an accurate and fast data-augmented Gibbs sampler in cases where traditional MCMC fails.
View Article and Find Full Text PDFFront Public Health
September 2025
Department of Infectious Diseases, Yiyang Central Hospital, Yiyang, China.
Background: Dyslipidemia and chronic liver disease (CLD) remain major global health challenges with high morbidity and mortality rates. Although extensively studied, the association between dyslipidemia and CLD remains incompletely elucidated. Depressive symptoms, an increasingly prevalent comorbidity, have been widely implicated in both conditions.
View Article and Find Full Text PDFDetermining which statistical methods are appropriate for data is both user and data dependent and prone to change as new methodology becomes available. This process encompasses model ideation, model selection, and determining appropriate use of statistical methods. Literature on models for animal movement emerging in the past two decades has yielded a rich collection of statistical methods garnering much deserved positive attention.
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