Factors Affecting the Academic Persistence of Adult Online Learners Using Hierarchical Generalized Linear Model Approach

2021 ◽  
Vol 17 (4) ◽  
pp. 65-84
Author(s):  
Sueyeon Song ◽  
Mihee Park ◽  
Hankyoung Kim
Keyword(s):  
Linear Model ◽  
Generalized Linear Model ◽  
Academic Persistence ◽  
Online Learners ◽  
Factors Affecting ◽  
Hierarchical Generalized Linear Model ◽  
Adult Online Learners ◽  
Model Approach

Air pollution epidemiology: A simplified Generalized Linear Model approach optimized by bio-inspired metaheuristics

2020 ◽  
Vol 191 ◽  
pp. 110106 ◽  
Author(s):  
Jônatas T. Belotti ◽  
Diego S. Castanho ◽  
Lilian N. Araujo ◽  
Lucas V. da Silva ◽  
Thiago Antonini Alves ◽  
...  
Keyword(s):  
Air Pollution ◽  
Linear Model ◽  
Generalized Linear Model ◽  
Air Pollution Epidemiology ◽  
Model Approach

scholarly journals The Adoption of IFRS and Earnings Quality of Financial Statements of Nigerian Breweries Plc: Generalised Linear Model Approach

2021 ◽  
Vol 04 (09) ◽  
Author(s):  
Michael Rotimi SANNI Phd ◽  
Keyword(s):  
Linear Model ◽  
Generalized Linear Model ◽  
Earnings Quality ◽  
Financial Statements ◽  
Share Price ◽  
Earnings Per Share ◽  
Research Period ◽  
Model Approach

The adoption of IFRS is expected to improve the earnings quality of firms that adopt them. It is against this background that this study investigated how the adoption of IFRS has affected earnings quality of Nigerian Breweries Plc. The company was selected because of its importance to the Nigerian economy. The 18 -year research period (2003 – 2020) was divided equally between (2003 – 2011) Pre- IFRS period (9 years) and (2012 – 2020) Post – IFRS period (9 years). Data on share price and Earnings per Share used to calculate earnings yield and change in earnings yield used to proxy earnings quality were sourced from the published financial statements of the company. Findings from Generalized Linear Model revealed no improvement in the earnings quality of the company after the adoption. Findings further showed that the company faced a lot of macro and micro economic challenges that affected its operating performances during the research period. The study therefore recommends to government to address those ident fied challenges because of the importance of the industry to the Nigerian economy.

Genetic Basics of Seed Traits in Soybean with Bayes Hierarchical Generalized Linear Model Method

2013 ◽  
Vol 39 (2) ◽  
pp. 258 ◽  
Author(s):  
Ning YAN ◽  
Shang-Qian XIE ◽  
Qing-Chun GENG ◽  
Yu XU ◽  
Guang-Jun LI ◽  
...  
Keyword(s):  
Linear Model ◽  
Generalized Linear Model ◽  
Seed Traits ◽  
Hierarchical Generalized Linear Model ◽  
Model Method

scholarly journals Generalized linear modeling of a panel mobility index with correlated multivariate categorical responses

2021 ◽  
Vol 54 (2) ◽  
pp. 207-221
Author(s):  
Drew M. Lazar ◽  
Munni Begum
Keyword(s):  
Linear Model ◽  
Generalized Linear Model ◽  
Goodness Of Fit ◽  
Linear Modeling ◽  
Older Americans ◽  
Binary Responses ◽  
Explanatory Variables ◽  
Categorical Responses ◽  
Multivariate Categorical ◽  
Model Approach

Data with multivariate, longitudual categorical responses often occur in applications. It can be difficult to analyze and model such data while simultaneously taking into account explanatory variables and correlations between the responses over time. We take a generalized linear model approach to this problem in analyzing panel data from the Health and Retirement Survey (HRS) that includes older Americans’ mobility over several years as a response. We provide a general formula for the likelihood of such data and apply it to the case when there are three binary responses. This approach can be taken, with computational limits, for data with multivariate, categorical responses with any number of categories. We consider, simultaneously, interpretations of coefficients, dependence of responses and goodness-of-fit in reduced models for parsimony while taking into account explanatory data. The gradient of the objective function is provided for use in gradient descent and the coded optimization algorithm is tested with a Monte Carlo simulation. Dependence of responses in mobility is shown before taking explanatory variables into account, and dependence is shown in a Markov logistic regression model and in the generalized linear model taking into account race, age, gender and interactions between them.

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