Results 81 to 90 of about 4,654,667 (290)

Data Transformation and Scaling Methods for Zero-Inflated Sparse Data Analysis

Information
Zero-inflated sparse count data are common in text analytics, where keyword frequencies contain many zeros and highly skewed positive values. This study proposes a systematic model-specific framework that treats predictor transformation and scaling as ...
Sunghae Jun
doaj   +1 more source

Zero-inflated models for the evaluation of colorectal polyps in colon cancer screening studies—a value-based biostatistics practice [PDF]

PeerJ
Background Colon cancer screening studies are needed for the early detection of colorectal polyps to reduce the risk of colorectal cancer. Unfortunately, the data generated on colon polyps are typically analyzed in their dichotomized form and sometimes ...
Alok K. Dwivedi, Sherif E. Elhanafi, Mohamed O. Othman, Marc J. Zuckerman   +3 more
doaj   +2 more sources

Order restricted row‐column cluster randomized design

Canadian Journal of Statistics, EarlyView.
Abstract This research introduces a novel two‐stage cluster randomized design, the order restricted row‐column cluster randomized design. The new design builds upon the cluster randomized block design by incorporating a second layer of blocking, achieved through ranking cluster units that are randomly sampled from the population.
Dalton Hopper, Omer Ozturk, Olena Kravchuk   +2 more
wiley   +1 more source

Multi-Task CNN-LSTM Modeling of Zero-Inflated Count and Time-to-Event Outcomes for Causal Inference with Functional Representation of Features

Axioms
We propose a novel deep learning framework for counterfactual inference on the COMPAS dataset, utilizing a multi-task CNN-LSTM architecture. The model jointly predicts multiple outcome types: (i) count outcomes with zero inflation, modeled using zero ...
Jong-Min Kim
doaj   +1 more source

SDG Reporting in Spanish Listed Companies: A Longitudinal Industry‐Level Analysis Using Natural Language Processing (2018–2023)

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT This study analyzes the evolution of Sustainable Development Goal (SDG) disclosure among IBEX 35 companies between 2018 and 2023, combining natural language processing for disclosure measurement with negative binomial generalized linear mixed models incorporating financial and governance controls.
Francisco Aguado‐Correa, Juan José de la Vega‐Jiménez, Nuria Padilla‐Garrido, Inmaculada Rabadán‐Martín, José María López‐Jiménez, Ignacio Peletier‐Ribera   +5 more
wiley   +1 more source

Modeling sparse Rift Valley fever incidence data: a Bayesian perspective on zero-inflated self-exciting and autoregressive models

BMC Infectious Diseases
Background Rift Valley fever (RVF) is a mosquito-borne zoonotic disease for which predictive modeling is often hindered by sparse data, particularly the high frequency of zero counts in both human and livestock surveillance systems.
Alexandros Angelakis, Bryan O. Nyawanda, Penelope Vounatsou   +2 more
doaj   +1 more source

Consistent estimation of zero-inflated count models [PDF]

Applications of zero-inflated count data models have proliferated in health economics. However, zero-inflated Poisson or zero-inflated negative binomial maximum likelihood estimators are not robust to misspecification.
Rainer Winkelmann, Kevin E. Staub
core  

CEO Conversational Receptiveness and Its Role in Reducing ESG Controversies

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Environmental, social, and governance (ESG) controversies can severely damage firms' legitimacy, reputation, and stakeholder trust. Yet little is known about how CEO leadership behaviors shape firms' exposure to such unfavorable ESG outcomes.
Thomas Hufnagel, Carolin Krieweth, Malte Brettel   +2 more
wiley   +1 more source

Finding the Right Distribution for Highly Skewed Zero-inflated Clinical Data

Epidemiology, Biostatistics and Public Health, 2022
Discrete, highly skewed distributions with excess numbers of zeros often result in biased estimates and misleading inferences if the zeros are not properly addressed.
Resmi Gupta , Bradley S. Marino , James F. Cnota, Richard F. Ittenbach   +3 more
doaj  

Zero Inflated Poisson and Zero Inflated Negative Binomial Models with Application to Number of Falls in the Elderly

Biostatistics and Biometrics Open Access Journal, 2017
The presence of excess zeros and the problem of over-dispersion often occur with count data. Few methods have been developed to deal with extra zeros that occur in response count variables. Such methods include zero inflated Poisson (ZIP) and zero inflated negative binomial (ZINB) regression models.
openaire   +1 more source