GENERALIZED LINEAR MODEL APPROACH TO ASSESS THE INFLUENCE OF CLIMATIC FACTORS ON THE CHIKUNGUNYA INCIDENCE DURING AN EPIDEMIC IN MYSORE DISTRICT

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.

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Estimating the Dose–Response Function through a Generalized Linear Model Approach

The Stata Journal Promoting communications on statistics and Stata ◽

10.1177/1536867x1401400110 ◽

2014 ◽

Vol 14 (1) ◽

pp. 141-158 ◽

Cited By ~ 22

Author(s):

Barbara Guardabascio ◽

Marco Ventura

Keyword(s):

Linear Model ◽

Response Function ◽

Dose Response ◽

Generalized Linear Model ◽

Dose Response Function ◽

Model Approach

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

10.47302/jsr.2020540207 ◽

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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