scholarly journals Reviewing of Different Methods for Handling Longitudinal Count data

2021 ◽  
Vol 23 (08) ◽  
pp. 195-206
Author(s):  
Amany. M ◽  
◽  
Mousa ◽  
Ahmed. A ◽  
El sheikh ◽  
...  
Keyword(s):  
Method Of Moments ◽  
Count Data ◽  
Generalized Estimating Equations ◽  
Generalized Method Of Moments ◽  
Marginal Models ◽  
Advantages And Disadvantages ◽  
Population Average ◽  
Longitudinal Count Data ◽  
Quadratic Inference Functions ◽  
Primary Focus

In this paper, we will review the methods that used to handle longitudinal data in the case of marginal models when inferences about the population average are the primary focus [1] or when future applications of the results require the expectation of the response as a function of the current covariates [7]. We will review the generalized estimating equations method (GEE), quadratic inference functions (QIF), generalized quasi likelihood (GQL) and the generalized method of moments (GMM). These methods will be reviewed by discussing its advantages and disadvantages in more details.

scholarly journals Marginal models for longitudinal count data with dropouts

2020 ◽  
Vol 54 (1) ◽  
pp. 27-42
Author(s):  
Seema Zubair ◽  
Sanjoy K. Sinha
Keyword(s):  
Count Data ◽  
Generalized Estimating Equations ◽  
Linear Models ◽  
Estimating Equations ◽  
Finite Sample ◽  
Marginal Models ◽  
Missing Responses ◽  
Longitudinal Count Data ◽  
Log Linear ◽  
Generalized Estimating

In this article, we investigate marginal models for analyzing incomplete longitudinal count data with dropouts. Specifically, we explore commonly used generalized estimating equations and weighted generalized estimating equations for fitting log-linear models to count data in the presence of monotone missing responses. A series of simulations were carried out to examine the finite-sample properties of the estimators in the presence of both correctly specified and misspecified dropout mechanisms. An application is provided using actual longitudinal survey data from the Health and Retirement Study (HRS) (HRS, 2019)

Analyzing discontinuities in longitudinal count data: A multilevel generalized linear mixed model.

2020 ◽  
Author(s):  
James L. Peugh ◽  
Sarah J. Beal ◽  
Meghan E. McGrady ◽  
Michael D. Toland ◽  
Constance Mara
Keyword(s):  
Count Data ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Generalized Linear Mixed Model ◽  
Longitudinal Count Data

Using information from singletons in fixed-effects estimation: xtfesing

2020 ◽  
Vol 20 (4) ◽  
pp. 965-975
Author(s):  
Laura Magazzini ◽  
Randolph Luca Bruno ◽  
Marco Stampini
Keyword(s):  
Panel Data ◽  
Method Of Moments ◽  
Fixed Effects ◽  
Generalized Method Of Moments ◽  
Panel Data Regression ◽  
Data Regression ◽  
Method Of Moments Estimator ◽  
Fixed Effects Estimation

In this article, we describe the xtfesing command. The command implements a generalized method of moments estimator that allows exploiting singleton information in fixed-effects panel-data regression as in Bruno, Magazzini, and Stampini (2020, Economics Letters 186: Article 108519).

Does Bank Profitability Stimulate Economic Growth in the Arab Region?

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Omar Ghazy Aziz
Keyword(s):  
Financial Development ◽  
Method Of Moments ◽  
Positive Impact ◽  
Generalized Method Of Moments ◽  
Arab Countries ◽  
Return On Assets ◽  
Bank Profitability ◽  
Arab Region ◽  
Return On Equity ◽  
The Impact

AbstractThis study empirically investigates the impact of bank profitability, as a complementary measure of financial development, on growth in the Arab countries between 1985 and 2016. Using a generalized method of moments (GMM) estimation to test the impact of the bank profitability on growth, this study utilises two variables in the econometric model which are return on assets and return on equity. This study reveals that both variables of bank profitability are positive and significant. This confirms that the bank profitability, beside other financial development variables, has positive impact on the growth. This study points out some important implications based on this result.

scholarly journals Competing risks joint models using R-INLA

2021 ◽  
Vol 21 (1-2) ◽  
pp. 56-71
Author(s):  
Janet van Niekerk ◽  
Haakon Bakka ◽  
Håvard Rue
Keyword(s):  
Competing Risks ◽  
Count Data ◽  
Joint Model ◽  
Point Of View ◽  
Spatial Structures ◽  
Joint Models ◽  
Hazard Functions ◽  
Longitudinal Count Data ◽  
Non Gaussian ◽  
Made In

The methodological advancements made in the field of joint models are numerous. None the less, the case of competing risks joint models has largely been neglected, especially from a practitioner's point of view. In the relevant works on competing risks joint models, the assumptions of a Gaussian linear longitudinal series and proportional cause-specific hazard functions, amongst others, have remained unchallenged. In this article, we provide a framework based on R-INLA to apply competing risks joint models in a unifying way such that non-Gaussian longitudinal data, spatial structures, times-dependent splines and various latent association structures, to mention a few, are all embraced in our approach. Our motivation stems from the SANAD trial which exhibits non-linear longitudinal trajectories and competing risks for failure of treatment. We also present a discrete competing risks joint model for longitudinal count data as well as a spatial competing risks joint model as specific examples.

Assessing the bank profitability in the MENA region

2014 ◽  
Vol 7 (3) ◽  
pp. 305-332 ◽  
Author(s):  
Rim Ben Selma Mokni ◽  
Houssem Rachdi
Keyword(s):  
Method Of Moments ◽  
North Africa ◽  
Banking Sector ◽  
Middle Eastern ◽  
Generalized Method Of Moments ◽  
Mena Region ◽  
Bank Profitability ◽  
Content Type ◽  
Conventional Banks ◽  
Econometric Technique

Purpose – Which of the banking stream is relatively more profitable in Middle Eastern and North Africa (MENA) region? Design/methodology/approach – The empirical study covers a sample of 15 conventional and 15 Islamic banks for the period 2002-2009.The authors estimate models using the generalized method of moments in system, of Blundell and Bond (1998). They exploit an up-to-date econometric technique which takes into consideration the issue of endogeneity of regressors to evaluate the comparative profitability of Islamic and conventional banks in the MENA region. Findings – Empirical analysis results show that the determinants’ significance varies between Islamic and conventional banks. Profitability seems to be quite persistent in the MENA region reflecting a higher degree of government intervention and may signal barriers to competition. Originality/value – The main interest is to develop a comprehensive model that integrates macroeconomic, industry-specific and bank-specific determinants. The paper makes comparison of the performance between two different banking systems in the MENA region. The authors consider a variable crisis to gain additional insights into the impacts of the financial crisis on MENA banking sector.

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