Results 21 to 30 of about 309,621 (292)
An introduction to the full random effects model
CPT: Pharmacometrics & Systems Pharmacology, 2022 The full random‐effects model (FREM) is a method for determining covariate effects in mixed‐effects models. Covariates are modeled as random variables, described by mean and variance.
Gunnar Yngman +4 more
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The Modified Borel–Tanner (Mbt) Regression Model
Revstat Statistical Journal, 2017 A new one-parameter family of discrete distributions is presented. It has some advantages against the Poisson distribution as a suitable model for modelling data with a high frequencies of zeros and showing over-dispersion (variance larger than the mean)
Emilio Gómez-Déniz +2 more
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Covariant residual entropy [PDF]
Journal of High Energy Physics, 2014 35 pages, 6 figures; v2: references added, matches the published ...
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Modeling of Cellular Networks Using Stationary and Nonstationary Point Processes
IEEE Access, 2018 The spatial topology of the base stations in wireless networks has a profound impact on their performance evaluation and analysis. It is important to identify a proper and accurate point process model before applying any theoretical stochastic geometry ...
Chunlin Chen +3 more
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Covariance-on-covariance regression
BiometricsABSTRACT A covariance-on-covariance regression model is introduced in this manuscript. It is assumed that there exists (at least) a pair of linear projections on outcome covariance matrices and predictor covariance matrices such that a log-linear model links the variances in the projection spaces, as well as additional covariates of ...
Yi Zhao, Yize Zhao
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A Review on ROC Curves in the Presence of Covariates
Revstat Statistical Journal, 2014 In this paper we review the literature on ROC curves in the presence of covariates. We discuss the different approaches that have been proposed in the literature to define, model, estimate and do asymptotics for ROC curves that incorporate covariates ...
Juan Carlos Pardo-Fernández +2 more
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BMC Medical Research Methodology, 2021 Background Cardinality matching (CM), a novel matching technique, finds the largest matched sample meeting prespecified balance criteria thereby overcoming limitations of propensity score matching (PSM) associated with limited covariate overlap, which ...
Stephen P. Fortin +2 more
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Robustness of meta-analyses in finding gene × environment interactions. [PDF]
PLoS ONE, 2017 Meta-analyses that synthesize statistical evidence across studies have become important analytical tools for genetic studies. Inspired by the success of genome-wide association studies of the genetic main effect, researchers are searching for gene ...
Gang Shi, Arye Nehorai
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To Adjust or Not to Adjust? Sensitivity Analysis of M-Bias and Butterfly-Bias
Journal of Causal Inference, 2015 “M-Bias,” as it is called in the epidemiologic literature, is the bias introduced by conditioning on a pretreatment covariate due to a particular “M-Structure” between two latent factors, an observed treatment, an outcome, and a “collider.” This ...
Ding Peng, Miratrix Luke W.
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Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, 2019 Background Smoker's paradox has been observed with several vascular disorders, yet there are limited data in patients with acute heart failure (HF). We examined the effects of smoking in patients with acute HF using data from a large multicenter registry.
Suhail A. Doi +19 more
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