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16 papers · ranked by Valyu relevance

01
PPubMed24 Nov 2014
Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis
Ben G Armstrong, Antonio Gasparrini, Aurelio Tobias
Background The time stratified case cross-over approach is a popular alternative to conventional time series regression for analysing associations between time series of environmental exposures (air pollution, weather) and counts of health outcomes. These are almost always analyzed using conditional logistic regression…
81relevance
02
PPubMed8 Apr 2021
Closed-Form Results for Prior Constraints in Sum-Product Networks
Ioannis Papantonis, Vaishak Belle
Incorporating constraints is a major concern in probabilistic machine learning. A wide variety of problems require predictions to be integrated with reasoning about constraints, from modeling routes on maps to approving loan predictions. In the former, we may require the prediction model to respect the presence of…
77relevance
03
PPubMed10 Jan 2022
The Role of Conditional Likelihoods in Latent Variable Modeling
Anders Skrondal, Sophia Rabe-Hesketh
In psychometrics, the canonical use of conditional likelihoods is for the Rasch model in measurement. Whilst not disputing the utility of conditional likelihoods in measurement, we examine a broader class of problems in psychometrics that can be addressed via conditional likelihoods. Specifically, we consider…
75relevance
04
PPubMed7 Sep 2018
Modeling Nonlinear Conditional Dependence Between Response Time and Accuracy
Maria Bolsinova, Dylan Molenaar
The most common process variable available for analysis due to tests presented in a computerized form is response time. Psychometric models have been developed for joint modeling of response accuracy and response time in which response time is an additional source of information about ability and about the underlying…
73relevance
05
PPubMed26 Oct 2018
Imprecise Uncertain Reasoning: A Distributional Approach
Gernot D. Kleiter
The contribution proposes to model imprecise and uncertain reasoning by a mental probability logic that is based on probability distributions. It shows how distributions are combined with logical operators and how distributions propagate in inference rules. It discusses a series of examples like the Linda task, the…
72relevance
06
PPubMed24 Sep 2020
Can Short and Partial Observations Reduce Model Error and Facilitate Machine Learning Prediction?
Nan Chen
Predicting complex nonlinear turbulent dynamical systems is an important and practical topic. However, due to the lack of a complete understanding of nature, the ubiquitous model error may greatly affect the prediction performance. Machine learning algorithms can overcome the model error, but they are often impeded by…
72relevance
07
PPubMed16 Feb 2024
Conditional Dependence across Slow and Fast Item Responses: With a Latent Space Item Response Modeling Approach
Nana Kim, Minjeong Jeon, Ivailo Partchev
There recently have been many studies examining conditional dependence between response accuracy and response times in cognitive tests. While most previous research has focused on revealing a general pattern of conditional dependence for all respondents and items, it is plausible that the pattern may vary across…
71relevance
08
PPubMed16 Mar 2026
Learning earthquake ground motions via conditional generative modeling
Pu Ren, Rie Nakata, Maxime Lacour, Ilan Naiman + 8 more
Predicting high-fidelity ground motions for future earthquakes is crucial for seismic hazard assessment and infrastructure resilience. Conventional empirical simulations suffer from sparse sensor distribution and geographically localized earthquake locations, while physics-based methods are computationally intensive…
70relevance
09
PPubMed2 Jun 2023
Excursions in the Bayesian treatment of model error Bayesian treatment of model error
L. Mark Berliner, Radu Herbei, Christopher K. Wikle, Ralph F. Milliff + 1 more
'Ralph F. Milliff' 'Pablo Martin Rodriguez'] Advances in observational and computational assets have led to revolutions in the range and quality of results in many science and engineering settings. However, those advances have led to needs for new research in treating model errors and assessing their impacts. We…
67relevance
10
PPubMed9 May 2024
Conditional independence as a statistical assessment of evidence integration processes Conditional independence as a statistical assessment of evidence integration processes
Emilio Salinas, Terrence R. Stanford, Nicholas V Swindale
Intuitively, combining multiple sources of evidence should lead to more accurate decisions than considering single sources of evidence individually. In practice, however, the proper computation may be difficult, or may require additional data that are inaccessible. Here, based on the concept of conditional…
67relevance
11
PPubMed11 Nov 2021
Realizing the Application of EEG Modeling in BCI Classification: Based on a Conditional GAN Converter
Xiaodong Zhang, Zhufeng Lu, Teng Zhang, Hanzhe Li + 2 more
'Qing Tao'] Electroencephalogram (EEG) modeling in brain-computer interface (BCI) provides a theoretical foundation for its development. However, limited by the lack of guidelines in model parameter selection and the inability to obtain personal tissue information in practice, EEG modeling in BCI is mainly focused on…
66relevance
12
PPubMed7 Sep 2022
Relationship between Different Dimensions of Workplace Spirituality and Psychological Well-Being: Measuring Mediation Analysis through Conditional Process Modeling
Rizwan Raheem Ahmed, Farwa Abbas Soomro, Zahid Ali Channar, Alharthi Rami Hashem E + 5 more
'Alharthi Rami Hashem E' 'Hassan Abbas Soomro' 'Munwar Hussain Pahi' 'Nor Zafir Md Salleh' 'Begoña Espejo' 'Irene Checa'] The present study aims to identify the relationship between workplace spirituality, compassion, relationship with others at work, spiritual orientation, organizational value and alignment of…
65relevance
13
PPubMed14 Oct 2022
On Suitability of Mixture of Generalized Exponential Models in Modeling Right-Censored Medical Datasets Using Conditional Expectations
Navid Feroze, Ali Akgül, Ali A. Al-Alwan, Md. Moyazzem Hossain + 1 more
'R. Alshenawy'] The exploration of suitable models for modeling censored medical datasets is of great importance. There are numerous studies dealing with modeling the censored medical datasets. However, majority of the earlier contributions have utilized the conventional models for modeling the said datasets.…
64relevance
14
PPubMed30 Dec 2019
Decision Support Modeling: Data Assimilation, Uncertainty Quantification, and Strategic Abstraction J. Doherty and C. Moore Groundwater XX, no. X: XX–XX J. Doherty and C. Moore
John Doherty, Catherine Moore
We present a framework for design and deployment of decision support modeling based on metrics which have their roots in the scientific method. Application of these metrics to decision support modeling requires recognition of the importance of data assimilation and predictive uncertainty quantification in this type of…
60relevance
15
PPubMed8 Jan 2019
The use of mathematical modeling studies for evidence synthesis and guideline development: A glossary Porgo et al.
Teegwendé V. Porgo, Susan L. Norris, Georgia Salanti, Leigh F. Johnson + 4 more
'Leigh F. Johnson' 'Julie A. Simpson' 'Nicola Low' 'Matthias Egger' 'Christian L. Althaus'] Mathematical modeling studies are increasingly recognised as an important tool for evidence synthesis and to inform clinical and public health decision-making, particularly when data from systematic reviews of primary studies do…
52relevance
16
PPubMed11 Apr 2018
Bayesian evaluation of behavior change interventions: a brief introduction and a practical example HEALTH PSYCHOLOGY AND BEHAVIORAL MEDICINE M. T. HEINO ET AL.
Matti T. J. Heino, Matti Vuorre, Nelli Hankonen
Introduction Evaluating effects of behavior change interventions is a central interest in health psychology and behavioral medicine. Researchers in these fields routinely use frequentist statistical methods to evaluate the extent to which these interventions impact behavior and the hypothesized mediating processes in…
52relevance

Results for conditional modeling

Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis

Closed-Form Results for Prior Constraints in Sum-Product Networks

The Role of Conditional Likelihoods in Latent Variable Modeling

Modeling Nonlinear Conditional Dependence Between Response Time and Accuracy

Imprecise Uncertain Reasoning: A Distributional Approach

Can Short and Partial Observations Reduce Model Error and Facilitate Machine Learning Prediction?

Conditional Dependence across Slow and Fast Item Responses: With a Latent Space Item Response Modeling Approach

Learning earthquake ground motions via conditional generative modeling

Excursions in the Bayesian treatment of model error Bayesian treatment of model error

Conditional independence as a statistical assessment of evidence integration processes Conditional independence as a statistical assessment of evidence integration processes

Realizing the Application of EEG Modeling in BCI Classification: Based on a Conditional GAN Converter

Relationship between Different Dimensions of Workplace Spirituality and Psychological Well-Being: Measuring Mediation Analysis through Conditional Process Modeling

On Suitability of Mixture of Generalized Exponential Models in Modeling Right-Censored Medical Datasets Using Conditional Expectations

Decision Support Modeling: Data Assimilation, Uncertainty Quantification, and Strategic Abstraction J. Doherty and C. Moore Groundwater XX, no. X: XX–XX J. Doherty and C. Moore

The use of mathematical modeling studies for evidence synthesis and guideline development: A glossary Porgo et al.

Bayesian evaluation of behavior change interventions: a brief introduction and a practical example HEALTH PSYCHOLOGY AND BEHAVIORAL MEDICINE M. T. HEINO ET AL.

Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis

Closed-Form Results for Prior Constraints in Sum-Product Networks

The Role of Conditional Likelihoods in Latent Variable Modeling

Modeling Nonlinear Conditional Dependence Between Response Time and Accuracy

Imprecise Uncertain Reasoning: A Distributional Approach

Can Short and Partial Observations Reduce Model Error and Facilitate Machine Learning Prediction?

Conditional Dependence across Slow and Fast Item Responses: With a Latent Space Item Response Modeling Approach

Learning earthquake ground motions via conditional generative modeling

Excursions in the Bayesian treatment of model error Bayesian treatment of model error

Conditional independence as a statistical assessment of evidence integration processes Conditional independence as a statistical assessment of evidence integration processes

Realizing the Application of EEG Modeling in BCI Classification: Based on a Conditional GAN Converter

Relationship between Different Dimensions of Workplace Spirituality and Psychological Well-Being: Measuring Mediation Analysis through Conditional Process Modeling

On Suitability of Mixture of Generalized Exponential Models in Modeling Right-Censored Medical Datasets Using Conditional Expectations

Decision Support Modeling: Data Assimilation, Uncertainty Quantification, and Strategic Abstraction J. Doherty and C. Moore Groundwater XX, no. X: XX–XX J. Doherty and C. Moore

The use of mathematical modeling studies for evidence synthesis and guideline development: A glossary Porgo et al.

Bayesian evaluation of behavior change interventions: a brief introduction and a practical example HEALTH PSYCHOLOGY AND BEHAVIORAL MEDICINE M. T. HEINO ET AL.