Results 11 to 20 of about 1,303,019 (294)
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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Parallel matrix factorization for binary response [PDF]
2013 IEEE International Conference on Big Data, 2013 Predicting user affinity to items is an important problem in applications like content optimization, computational advertising, and many more. While bilinear random effect models (matrix factorization) provide state-of-the-art performance when minimizing RMSE through a Gaussian response model on explicit ratings data, applying it to imbalanced binary ...
Khanna, Rajiv +3 more
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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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Single equation endogenous binary response models [PDF]
, 2009 This paper studies single equation models for binary outcomes incorporating instrumental variable restrictions. The models are incomplete in the sense that they place no restriction on the way in which values of endogenous variables are generated.
Chesher, A.
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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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Endogeneity in Semiparametric Binary Response Models [PDF]
Review of Economic Studies, 2004 Summary: This paper develops and implements semiparametric methods for estimating binary response (binary choice) models with continuous endogenous regressors. It extends existing results on semiparametric estimation in single-index binary response models to the case of endogenous regressors.
Richard W. Blundell, James L. Powell
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When binary and continuous responses disagree [PDF]
Annals of the Rheumatic Diseases, 2020 In the observational TOCERRA study by Lauper et al ,1 the authors showed that tocilizumab (TOC; either as monotherapy or combination therapy) had superior drug retention than tumour necrosis factor inhibitors (TNFi; as monotherapy or combination therapy), in patients with rheumatoid arthritis with prior exposure to at least one biologic disease ...
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Genetic evaluation for multiple binary responses [PDF]
Genetics Selection Evolution, 1986 A method of genetic evaluation for multiple binary responses is presented. An underlying multivariate normal distribution is rendered discrete, in m dimensions, via a set of m fixed thresholds. There are 2m categories of response and the probability of response in a given category is modeled with an m-dimensional multivariate normal integral.
Hoschele, I. +3 more
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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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IMEX evolution of scalar fields on curved backgrounds [PDF]
, 2009 Inspiral of binary black holes occurs over a time-scale of many orbits, far longer than the dynamical time-scale of the individual black holes. Explicit evolutions of a binary system therefore require excessively many time steps to capture interesting ...
Hesthaven, Jan S. +2 more
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