Results 21 to 30 of about 6,119,704 (249)
The Specification of Dynamic Discrete-Time Two-State Panel Data Models
Econometrics, 2018 This paper compares two approaches to analyzing longitudinal discrete-time binary outcomes. Dynamic binary response models focus on state occupancy and typically specify low-order Markovian state dependence.
Tue Gørgens, Dean Robert Hyslop
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Efficient Robbins–Monro procedure for multivariate binary data
Statistical Theory and Related Fields, 2018 This paper considers the problem of jointly estimating marginal quantiles of a multivariate distribution. A sufficient condition for an estimator that converges in probability under a multivariate version of Robbins–Monro procedure is provided.
Cui Xiong, Jin Xu
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Constant Information Design for Binary Response Data
Sultan Qaboos University Journal for Science, 1998 A major problem is designing experiments when the assumed model is nonlinear, is the dependence of the designs on the values of the unknown parameters we consider in this article designs for binary data and generalize the constant information criterion ...
K.A. Abdelbasit
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General Psychiatry, 2023 Although logistic regression is the most popular for modelling regression relationships with binary responses, many find relative risk (RR), or risk ratio, easier to interpret and prefer to use this measure of risk in regression analysis.
Xin M Tu +5 more
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D-Optimal Designs for Binary and Weighted Linear Regression Models: One Design Variable
Mathematics, 2023 D-optimality is a well-known concept in experimental design that seeks to select an optimal set of design points to estimate the unknown parameters of a statistical model with a minimum variance.
Necla Gündüz, Bernard Torsney
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PLoS Biology, 2012 Erythropoietin (Epo)-induced Stat5 phosphorylation (p-Stat5) is essential for both basal erythropoiesis and for its acceleration during hypoxic stress. A key challenge lies in understanding how Stat5 signaling elicits distinct functions during basal and ...
Ermelinda Porpiglia +4 more
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RiskLogitboost Regression for Rare Events in Binary Response: An Econometric Approach
Mathematics, 2021 A boosting-based machine learning algorithm is presented to model a binary response with large imbalance, i.e., a rare event. The new method (i) reduces the prediction error of the rare class, and (ii) approximates an econometric model that allows ...
Jessica Pesantez-Narvaez +2 more
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Annealing Response of a Cold-Rolled Binary Al–10Mg Alloy
Metals, 2019 The effect of annealing temperature on microstructure and mechanical properties of a cold-rolled Al−10Mg alloy has been investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM), electron backscatter diffraction (EBSD) and tensile
Lei Feng +3 more
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Physiological dynamics as indicators of plant response to manganese binary effect
Frontiers in Plant Science, 2023 IntroductionHeavy metals negatively affect plant physiology. However, plants can reduce their toxicity through physiological responses. Broussonetia papyrifera is a suitable candidate tree for carrying out the phytoremediation of manganese (Mn ...
Xu Zhenggang +7 more
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The use of continuous data versus binary data in MTC models: A case study in rheumatoid arthritis
BMC Medical Research Methodology, 2012 Background Estimates of relative efficacy between alternative treatments are crucial for decision making in health care. When sufficient head to head evidence is not available Bayesian mixed treatment comparison models provide a powerful methodology to ...
Schmitz Susanne +2 more
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