Comparison of Logistic Regression and Generalized Linear Model for Identifying Accurate At – Risk Students [PDF]
Alinteri Journal of Agriculture Sciences, 2021 Aim: To predict the accuracy percentage of At - risk students based on High withdrawal and Failure rate. Materials and methods: Logistic Regression with sample size = 20 and Generalised Linear Model (GLM) with sample size = 20 was iterated different times for predicting accuracy percentage of At - risk students.
K. Harini, K. Sashi Rekha
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Evaluating an Automated Number Series Item Generator Using Linear Logistic Test Models [PDF]
Journal of Intelligence, 2018 This study investigates the item properties of a newly developed Automatic Number Series Item Generator (ANSIG). The foundation of the ANSIG is based on five hypothesised cognitive operators. Thirteen item models were developed using the numGen R package and eleven were evaluated in this study.
Bao Loe +3 more
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Jeffreys-prior penalty, finiteness and shrinkage in binomial-response generalized linear models [PDF]
, 2020 Penalization of the likelihood by Jeffreys' invariant prior, or by a positive power thereof, is shown to produce finite-valued maximum penalized likelihood estimates in a broad class of binomial generalized linear models.
Firth, David, Kosmidis, Ioannis
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Normal-Power-Logistic Distribution: Properties and Application in Generalized Linear Model
Journal of the Indian Society for Probability and Statistics, 2022 The applications of Normal distribution in literature are verse, the new modified univariate normal power distribution is a new distribution which is adequate for modelling bimodal data. There are many data that would have been modelled by normal distribution, but because of their bimodality, they are not, since normal distribution is unimodal. In this
Matthew I. Ekum +2 more
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Grid multi-category response logistic models. [PDF]
, 2015 BackgroundMulti-category response models are very important complements to binary logistic models in medical decision-making. Decomposing model construction by aggregating computation developed at different sites is necessary when data cannot be moved ...
Jiang, Wenchao +5 more
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A generalized Liu-type estimator for logistic partial linear regression model with multicollinearity
AIMS Mathematics, 2023 <abstract><p>This paper is concerned with proposing a generalized Liu-type estimator (GLTE) to address the multicollinearity problem of explanatory variable of the linear part in the logistic partially linear regression model. Using the profile likelihood method, we propose the GLTE as a general class of Liu-type estimator, which includes ...
Dayang Dai, Dabuxilatu Wang
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Chain graph models of multivariate regression type for categorical data [PDF]
, 2011 We discuss a class of chain graph models for categorical variables defined by what we call a multivariate regression chain graph Markov property. First, the set of local independencies of these models is shown to be Markov equivalent to those of a chain ...
Lupparelli, Monia +1 more
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Robust inference for generalized linear models with application to logistic regression [PDF]
Statistics & Probability Letters, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
ADIMARI, GIANFRANCO, VENTURA, LAURA
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Approximate Bayesian Model Selection with the Deviance Statistic [PDF]
, 2015 Bayesian model selection poses two main challenges: the specification of parameter priors for all models, and the computation of the resulting Bayes factors between models.
Bové, Daniel Sabanés +2 more
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Cluster-Robust Variance Estimation for Dyadic Data [PDF]
, 2015 Dyadic data are common in the social sciences, although inference for such settings involves accounting for a complex clustering structure. Many analyses in the social sciences fail to account for the fact that multiple dyads share a member, and that ...
Aronow, Peter M. +2 more
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