Results 61 to 70 of about 122,135 (259)
Background When analysing spatial data, it is important to account for spatial autocorrelation. In Bayesian statistics, spatial autocorrelation is commonly modelled by the intrinsic conditional autoregressive prior distribution.
Earl W. Duncan +2 more
doaj +1 more source
Goodness of fit in models for mortality data [PDF]
Mortality data on an aggregate level are characterized by very large sample sizes. For this reason, uninformative outcomes are evident in common Goodness-of-Fit measures.
Camarda, Carlo Giovanni, Durbán, María
core +1 more source
Examining residuals such as Pearson and deviance residuals, is a standard tool for assessing normal regression. However, for discrete response, these residuals cluster on lines corresponding to distinct response values.
Feng, Cindy +2 more
core +1 more source
Modelling count data with overdispersion and spatial effects [PDF]
In this paper we consider regression models for count data allowing for overdispersion in a Bayesian framework. We account for unobserved heterogeneity in the data in two ways. On the one hand, we consider more flexible models than a common Poisson model
Czado, Claudia, Gschlößl, Susanne
core +4 more sources
ABSTRACT Introduction Cognitive impairment and exercise intolerance are common in dialysis patients. Cerebral perfusion and oxygenation play a major role in both cognitive function and exercise execution; HD session per se aggravates cerebral ischemia in this population. This study aimed to compare cerebral oxygenation and perfusion at rest and in mild
Marieta P. Theodorakopoulou +10 more
wiley +1 more source
An intracellular transporter mitigates the CO2‐induced decline in iron content in Arabidopsis shoots
This study identifies a gene encoding a transmembrane protein, MIC, which contributes to the reduction of shoot Fe content observed in plants under elevated CO2. MIC is a putative Fe transporter localized to the Golgi and endosomal compartments. Its post‐translational regulation in roots may represent a potential target for improving plant nutrition ...
Timothy Mozzanino +7 more
wiley +1 more source
This paper presents a new statistical method that enables the use of systematic errors in the maximum-likelihood regression of integer-count Poisson data to a parametric model.
Massimiliano Bonamente +2 more
doaj +1 more source
Explore poverty with statistical modeling: The bivariate polynomial binary logit regression (BPBLR)
Logit regression (or logistic regression) is a statistical analysis of categorical data. The binary responses have two categories. We present the Bivariate Polynomial Binary Logit Regression (BPBLR), which extends logit regression by modeling two ...
Vita Ratnasari +3 more
doaj +1 more source
Social Exclusion of Australian Childless Women in Their Reproductive Years
Research suggests Australian childless women are at risk of pronatalism-driven social exclusion. This exploratory, mixed methods, cross-sectional study described and explored the social exclusion of Australian childless women aged 25 to 44 years, and ...
Beth Turnbull +2 more
doaj +1 more source
Reproducible Econometric Research. A Critical Review of the State of the Art. [PDF]
Recent software developments are reviewed from the vantage point of reproducible econometric research. We argue that the emergence of new tools, particularly in the open-source community, have greatly eased the burden of documenting and archiving both ...
Koenker, Roger, Zeileis, Achim
core

