Results 51 to 60 of about 3,733,122 (330)
AxiomsThis study introduces a new two-parameter Liu estimator (PMTPLE) for addressing the multicollinearity problem in the Poisson regression model (PRM). The estimation of the PRM is traditionally accomplished through the Poisson maximum likelihood estimator (
Mahmoud M. Abdelwahab +3 more
semanticscholar +1 more source
BMC Medical Research Methodology, 2018 BackgroundLog-binomial and robust (modified) Poisson regression models are popular approaches to estimate risk ratios for binary response variables. Previous studies have shown that comparatively they produce similar point estimates and standard errors ...
Wansu Chen +3 more
semanticscholar +1 more source
EM Estimation for Zero- and k-Inflated Poisson Regression Model
Computation, 2021 Count data with excessive zeros are ubiquitous in healthcare, medical, and scientific studies. There are numerous articles that show how to fit Poisson and other models which account for the excessive zeros. However, in many situations, besides zero, the
Monika Arora, N. Rao Chaganty
doaj +1 more source
PLoS ONE, 2022 In the era of open data, Poisson and other count regression models are increasingly important. Still, conventional Poisson regression has remaining issues in terms of identifiability and computational efficiency.
Daisuke Murakami, Tomoko Matsui
doaj +1 more source
Unweighted regression models perform better than weighted regression techniques for respondent-driven sampling data: results from a simulation study [PDF]
, 2019 Background: It is unclear whether weighted or unweighted regression is preferred in the analysis of data derived from respondent driven sampling. Our objective was to evaluate the validity of various regression models, with and without weights and with ...
Avery, Lisa +5 more
core +1 more source
Jackknifed Liu-type Estimator in Poisson Regression Model
, 2020 The Liu estimator has consistently been demonstrated to be an attractive shrinkage method for reducing the effects of multicollinearity. The Poisson regression model is a well-known model in applications when the response variable consists of count data.
Ahmed Alkhateeb, Z. Algamal
semanticscholar +1 more source
Functional Connectivity Linked to Cognitive Recovery After Minor Stroke
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Patients with minor stroke exhibit slowed processing speed and generalized alterations in functional connectivity involving frontoparietal cortex (FPC). The pattern of connectivity evolves over time. In this study, we examine the relationship of functional connectivity patterns to cognitive performance, to determine ...
Vrishab Commuri +7 more
wiley +1 more source
Retractions in Rheumatology: Trends, Causes, and Implications for Research Integrity
Arthritis Care &Research, EarlyView.Objective We aimed to describe the trends and main reasons for study retraction in rheumatology literature. Methods We reviewed the Retraction Watch database to identify retracted articles in rheumatology. We recorded the main study characteristics, authors’ countries, reasons for retraction, time from publication to retraction, and trends over time ...
Anna Maria Vettori, Michele Iudici
wiley +1 more source
Modified Ridge Estimator for Poisson Regression
Cumhuriyet Science JournalPoisson regression is a statistical model used to model the relationship between a count-valued-dependent variable and one or more independent variables. A frequently encountered problem when modeling such relationships is multicollinearity, which occurs
Shuaib Mursal Ibrahim, Aydın Karakoca
doaj +1 more source
POISSON REGRESSION MODELS TO ANALYZE FACTORS THAT INFLUENCE THE NUMBER OF TUBERCULOSIS CASES IN JAVA
Barekeng, 2023 Tuberculosis is an infectious disease and one of the world's top 10 highest causes of mortality in Indonesia. Based on this fact, it is necessary to study what factors affect number of tuberculosis cases.
Yekti Widyaningsih +1 more
doaj +1 more source