Modified ridge-type for the Poisson regression model: simulation and application

Lukman, Adewale F.; Aladeitan, Benedicta; Ayinde, Kayode; Abonazel, Mohamed R.

doi:10.1080/02664763.2021.1889998

“…Many investigators like: Liu [30], Kabria and Lukman [31], Lukman et al [32], and had proposed different techniques to manage the multicollinearity problem between the predictors when running regression models. Some of them, who developed methods for Poisson regression are Mansson and Shukur [33], Mansson et al [34], Lukman et al [35], [36], and Qasim et al [37]. In this paper, none of these methods were used as the Poisson model was mainly used to give preliminary vision about the effects of the high risk factors on the transition counts.…”

Section: Discussionmentioning

confidence: 99%

Log-Linear model and Multistate Model to Assess the Rate of Fibrosis in NAFLD Patients

Attia

¹

2022

Preprint

0

View full text Add to dashboard Cite

In the present paper, the deleterious effects of obesity, type 2diabetes and insulin resistance, systolic and diastolic hypertension on the rate of progression of fibrosis in non-alcoholic fatty liver disease (NAFLD) patients are illustrated using a new approach utilizing the Poisson regression to model the transition rate matrix. The observed counts in the transition counts matrix are used as response variables and the covariates are the risk factors for fatty liver. Then the estimated counts from running the Poisson regression are used to estimate the transition rates using the continuous time Markov chains (CTMCs) followed by exponentiation of the estimated rate matrix to obtain the transition probability matrix at specific time points. A depicted, hypothetical, observational, prospective longitudinal study of 150 participants followed up every year for a total of 28 years recording their demographic characteristics and their timeline follow up are demonstrated. The findings revealed that insulin resistance expressed by MOMA-IR 2 had the most deleterious effects among other factors for increasing the rate of forward progression of patients from state 1 to state 2 as well as from state 2 to state 3 and from state 3 to state 4. The higher the level of HOMA-IR is, the more rapid the rate of progression is. This analysis helps the health policy makers and medical insurance managers to allocate the financial and human resources for investigating and treating high risk patients for NAFLD. In addition, this analysis can be used by pharmaceutical companies to conduct longitudinal studies to assess the effectiveness of the newly emerging anti-fibrotic drugs.

show abstract

“…Many investigators like: Liu [30], Kabria and Lukman [31], Lukman et al [32], and had proposed different techniques to manage the multicollinearity problem between the predictors when running regression models. Some of them, who developed methods for Poisson regression are Mansson and Shukur [33], Mansson et al [34], Lukman et al[35], [36], and Qasim et al [37]. In this paper, none of these methods were used as the Poisson model was mainly used to give preliminary vision about the effects of the high risk factors on the transition counts.…”

Section: Discussionmentioning

confidence: 99%

Log-Linear model and Multistate Model to Assess the Rate of Fibrosis in NAFLD Patients

Attia

¹

2022

Preprint

0

View full text Add to dashboard Cite

In the present paper, the deleterious effects of obesity, type 2diabetes and insulin resistance, systolic and diastolic hypertension on the rate of progression of fibrosis in non-alcoholic fatty liver disease (NAFLD) patients are illustrated using a new approach utilizing the Poisson regression to model the transition rate matrix. The observed counts in the transition counts matrix are used as response variables and the covariates are the risk factors for fatty liver. Then the estimated counts from running the Poisson regression are used to estimate the transition rates using the continuous time Markov chains (CTMCs) followed by exponentiation of the estimated rate matrix to obtain the transition probability matrix at specific time points. A depicted, hypothetical, observational, prospective longitudinal study of 150 participants followed up every year for a total of 28 years recording their demographic characteristics and their timeline follow up are demonstrated. The findings revealed that insulin resistance expressed by MOMA-IR 2 had the most deleterious effects among other factors for increasing the rate of forward progression of patients from state 1 to state 2 as well as from state 2 to state 3 and from state 3 to state 4. The higher the level of HOMA-IR is, the more rapid the rate of progression is. This analysis helps the health policy makers and medical insurance managers to allocate the financial and human resources for investigating and treating high risk patients for NAFLD. In addition, this analysis can be used by pharmaceutical companies to conduct longitudinal studies to assess the effectiveness of the newly emerging anti-fibrotic drugs.

show abstract

“…Very recently, Dawoud and Kibria [5] proposed a new kind of two-parameter estimator called the Dawoud-Kibria (DK) estimator. There are other recent studies regarding the one parameter and two-parameter estimators in LR and GL models, such as Roozbeh et al [6], Lukman et al [7], Arashi et al [8], Farghali et al [9], Lukman et al [10,11], Algamal and Abonazel [12], Akram et al [13], and Abonazel et al [14]. In this article, we drive the Dawoud-Kibria estimator for the BR model in the presence of the multicollinearity problem.…”

Section: Introductionmentioning

confidence: 90%

Dawoud–Kibria Estimator for Beta Regression Model: Simulation and Application

Abonazel

¹

,

Dawoud

²

,

Awwad

³

et al. 2022

Front. Appl. Math. Stat.

Self Cite

View full text Add to dashboard Cite

The linear regression model becomes unsuitable when the response variable is expressed as percentages, proportions, and rates. The beta regression (BR) model is more appropriate for the variable of this form. The BR model uses the conventional maximum likelihood estimator (BML), and this estimator may not be efficient when the regressors are linearly dependent. The beta ridge estimator was suggested as an alternative to BML in the literature. In this study, we developed the Dawoud–Kibria estimator to handle multicollinearity in the BR model. The properties of the new estimator are derived. We compared the performance of the estimator with the existing estimators theoretically using the mean squared error criterion. A Monte Carlo simulation and a real-life application were carried out to show the benefits of the proposed estimator. The theoretical comparison, simulation, and real-life application results revealed the superiority of the proposed estimator.

show abstract

Modified ridge-type for the Poisson regression model: simulation and application

Cited by 32 publications

References 36 publications

Log-Linear model and Multistate Model to Assess the Rate of Fibrosis in NAFLD Patients

Log-Linear model and Multistate Model to Assess the Rate of Fibrosis in NAFLD Patients

Log-Linear model and Multistate Model to Assess the Rate of Fibrosis in NAFLD Patients

Dawoud–Kibria Estimator for Beta Regression Model: Simulation and Application

Contact Info

Product

Resources

About