Results 151 to 160 of about 1,252,930 (316)
Bernoulli Regression Models: Re-examining Statistical Models with Binary Dependent Variables [PDF]
The classical approach for specifying statistical models with binary dependent variables in econometrics using latent variables or threshold models can leave the model misspecified, resulting in biased and inconsistent estimates as well as erroneous ...
Spanos, Aris, Bergtold, Jason S.
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Cultivating Complexity in an Age of Digital Dominance and Binary Oppositional Thinking
HumanitiesThe work represented in the following essay explores meaning-making in the context of creating in a digitally saturated culture. The digital imperative, with its binary oppositional structure (ones and zeroes), has increasingly asserted itself as the ...
Amy Nolan
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High Health Care Utilization Preceding Diagnosis With Juvenile Idiopathic Arthritis
Arthritis Care &Research, EarlyView.Objective Although early diagnosis improves long‐term outcomes, patients with juvenile idiopathic arthritis (JIA) often experience prolonged, circuitous paths to diagnosis. To inform diagnostic improvement, we sought to characterize health care utilization in the year preceding diagnosis. Methods We identified 10,021 patients with an incident diagnosis
Anna Costello +5 more
wiley +1 more source
Some robust design strategies for percentile estimation in binary response models [PDF]
For the problem of percentile estimation of a quantal response curve, we determine multi-objective designs which are robust with respect to misspecifications of the model assumptions.
Dette, Holger +2 more
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Binary payment schemes moral hazard and loss aversion [PDF]
, 2010 We modify the principal-agent model with moral hazard by assuming that the agent is expectation-based loss averse according to Köszegi and Rabin (2006, 2007).
Müller, Daniel 1978- +2 more
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Analysis of incomplete longitudinal binary responses with Bayesian method
Journal of Biostatistics and Epidemiology, 2015 Longitudinal study plays an important role in the epidemiological, clinical, and social science studies. In these kinds of studies, every individual is observed frequently during a period of time.
Habibollah Esmaily +4 more
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Comprehensive Validation of Novel Deep Learning Architectures to Forecast Geomagnetic Substorms
Space WeatherMagnetic substorms are disturbances in the terrestrial magnetosphere that can have significant space weather impacts, although forecasting their onset accurately remains an open problem.
A. Essop, N. Mbatha, J. A. E. Stephenson
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Arthritis Care &Research, EarlyView.Objective Social determinants of health (SDOH) contribute to juvenile idiopathic arthritis (JIA) disparities, but most studies have assessed SDOH independently rather than cumulatively across individual, family, and neighborhood levels. Using a socioecological framework, we investigated the relationship among cumulative social disadvantage ...
William Daniel Soulsby +448 more
wiley +1 more source
Causal inference for binary regression with observational data [PDF]
Special problems arise when trying to do causal inference for binary regression with observational data; we will examine some of these problems and critically examine several common and not-so-common solutions.
Austin Nichols
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Arthritis Care &Research, EarlyView.Objective Despite well‐described biologic causes, the public views unhealthy lifestyle choices as the primary cause of gout. This study investigated how causal beliefs about gout influence the public's views about its management. Methods In a randomized study, 201 members of the public viewed one of two 2‐minute videos about gout.
Rachel Murdoch +6 more
wiley +1 more source