Results 1 to 10 of about 406,411 (253)
Boosted beta regression. [PDF]
PLoS ONE, 2013 Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale.
Matthias Schmid +5 more
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Studying the Interplay Between Apolipoprotein E and Education on Cognitive Decline in Centenarians Using Bayesian Beta Regression [PDF]
Frontiers in Genetics, 2021 Apolipoprotein E (APOE) is an important risk factor for cognitive decline and Alzheimer’s disease in aging individuals. Among the 3 known alleles of this gene: e2, e3, and e4, the e4 allele is associated with faster cognitive decline and increased risk ...
Qingyan Xiang +3 more
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A beta regression analysis of COVID-19 mortality in Brazil [PDF]
Infectious Disease Modelling, 2023 Brazil was one of the countries most impacted by the COVID-19 pandemic, with a cumulative total of nearly 700,000 deaths by early 2023. The country's federative units were unevenly affected by the pandemic and adopted mitigation measures of different ...
Francisco Cribari-Neto
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Mixed beta regression: A Bayesian perspective [PDF]
Computational Statistics and Data Analysis, 2013 This paper builds on recent research that focuses on regression modeling of continuous bounded data, such as proportions measured on a continuous scale. Specifically, it deals with beta regression models with mixed effects from a Bayesian approach. We use a suitable parameterization of the beta law in terms of its mean and a precision parameter, and ...
Silvia Ferrari +2 more
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A case for beta regression in the natural sciences
Ecosphere, 2022 Data in the natural sciences are often in the form of percentages or proportions that are continuous and bounded by 0 and 1. Statistical analysis assuming a normal error structure can produce biased and incorrect estimates when data are doubly bounded ...
Emilie A. Geissinger +4 more
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Process monitoring using inflated beta regression control chart. [PDF]
PLoS ONE, 2020 This paper provides a general framework for controlling quality characteristics related to control variables and limited to the intervals (0, 1], [0, 1), or [0, 1].
Luiz M A Lima-Filho +3 more
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A Beta Regression Approach to Modelling Country-Level Food Insecurity [PDF]
FoodsFood insecurity remains a persistent global challenge, despite significant advancements in agricultural production and technology. The main objective of this study is to identify and quantitatively assess some of the structural determinants influencing ...
Anamaria Roxana Martin +5 more
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Errors-in-variables beta regression models [PDF]
Journal of Applied Statistics, 2014 Beta regression models provide an adequate approach for modeling continuous outcomes limited to the interval (0, 1). This paper deals with an extension of beta regression models that allow for explanatory variables to be measured with error. The structural approach, in which the covariates measured with error are assumed to be random variables, is ...
Silvia Ferrari +2 more
exaly +6 more sources
Journal of Statistical Software, 2010 The class of beta regression models is commonly used by practitioners to model variables that assume values in the standard unit interval (0, 1). It is based on the assumption that the dependent variable is beta-distributed and that its mean is related ...
Francisco Cribari-Neto, Achim Zeileis
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A marginalized two-part Beta regression model for microbiome compositional data. [PDF]
PLoS Computational Biology, 2018 In microbiome studies, an important goal is to detect differential abundance of microbes across clinical conditions and treatment options. However, the microbiome compositional data (quantified by relative abundance) are highly skewed, bounded in [0, 1),
Haitao Chai +3 more
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