Empirical performance of estimation methods in Beta mixed models with application to ecological data

2020 ◽  
Vol 15 (2) ◽  
pp. 2279-2293
Author(s):  
Saliou Diouf ◽  
Bruno Enagnon Lokonon ◽  
Freedath Djibril Moussa ◽  
GLèLè KAKAï
Keyword(s):  
Mixed Models ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Real Life ◽  
Estimation Methods ◽  
Simulation Design ◽  
Ecological Data ◽  
Factors Affecting ◽  
Real Life Data ◽  
Empirical Performance

This study uses a Monte Carlo simulation design to assess the performance of Beta and linear mixed models on bounded response variables through comparison of four estimation methods. Four factors affecting the performance of the estimation methods were considered: the number of groups, the number of observations per group, the variance and distribution of the random effects. Our results showed that, for small number of groups (less than 30), the Beta mixed model outperformed the linear mixed model whatever the size of the groups. In the case of a large number of groups (superior or equal to 30), both approaches showed relatively close performance. The results from the simulation study have been illustrated with real life data.

scholarly journals Analyzing Child Malnutrition in Bangladesh: Generalized Linear Mixed Model Approach

2016 ◽  
Vol 64 (2) ◽  
pp. 163-167
Author(s):  
Tahmidul Islam ◽  
Md Golam Rabbani ◽  
Wasimul Bari
Keyword(s):  
Mixed Model ◽  
Sampling Design ◽  
Linear Mixed Model ◽  
Generalized Linear Mixed Model ◽  
Child Malnutrition ◽  
Demographic Health Survey ◽  
Factors Affecting ◽  
Mixed Model Approach ◽  
Potential Factors ◽  
Model Approach

Child malnutrition is a serious issue for overall child health and future development. Stunting is a key anthropometric indicator of child malnutrition. Because of the nature of sampling design used in Bangladesh Demographic Health Survey, 2011, responses obtained from children under same family might be correlated. Again, children residing in same cluster may also be correlated. To tackle this problem, generalized linear mixed model (GLMM), instead of usual fixed effect logistic regression model, has been utilized in this paper to find out potential factors affecting child malnutrition. Model performances have also been compared. Dhaka Univ. J. Sci. 64(2): 163-167, 2016 (July)

Full Credibility with Generalized Linear and Mixed Models

2009 ◽  
Vol 39 (1) ◽  
pp. 61-80 ◽  
Author(s):  
José Garrido ◽  
Jun Zhou
Keyword(s):  
Mixed Models ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Linear Models ◽  
Link Function ◽  
Analysis Method ◽  
Risk Class ◽  
Statistical Analysis Method ◽  
Car Insurance ◽  
Insurance Data

AbstractGeneralized linear models (GLMs) are gaining popularity as a statistical analysis method for insurance data. For segmented portfolios, as in car insurance, the question of credibility arises naturally; how many observations are needed in a risk class before the GLM estimators can be considered credible? In this paper we study the limited fluctuations credibility of the GLM estimators as well as in the extended case of generalized linear mixed model (GLMMs). We show how credibility depends on the sample size, the distribution of covariates and the link function. This provides a mechanism to obtain confidence intervals for the GLM and GLMM estimators.

Generalized linear mixed models for multi-reader multi-case studies of diagnostic tests

2015 ◽  
Vol 26 (3) ◽  
pp. 1373-1388 ◽  
Author(s):  
Wei Liu ◽  
Norberto Pantoja-Galicia ◽  
Bo Zhang ◽  
Richard M Kotz ◽  
Gene Pennello ◽  
...  
Keyword(s):  
Mixed Models ◽  
Diagnostic Tests ◽  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Generalized Linear Mixed Models ◽  
Characteristic Curve ◽  
Linear Mixed Models ◽  
Parametric Bootstrap ◽  
Pseudo Likelihood

Diagnostic tests are often compared in multi-reader multi-case (MRMC) studies in which a number of cases (subjects with or without the disease in question) are examined by several readers using all tests to be compared. One of the commonly used methods for analyzing MRMC data is the Obuchowski–Rockette (OR) method, which assumes that the true area under the receiver operating characteristic curve (AUC) for each combination of reader and test follows a linear mixed model with fixed effects for test and random effects for reader and the reader–test interaction. This article proposes generalized linear mixed models which generalize the OR model by incorporating a range-appropriate link function that constrains the true AUCs to the unit interval. The proposed models can be estimated by maximizing a pseudo-likelihood based on the approximate normality of AUC estimates. A Monte Carlo expectation-maximization algorithm can be used to maximize the pseudo-likelihood, and a non-parametric bootstrap procedure can be used for inference. The proposed method is evaluated in a simulation study and applied to an MRMC study of breast cancer detection.

Linear mixed model better than repeated measures analysis

2019 ◽  
Vol 30 (6) ◽  
pp. NP1-NP2 ◽  
Author(s):  
Işıl Kutluturk Karagoz ◽  
Berhan Keskin ◽  
Flora Özkalaycı ◽  
Ali Karagöz
Keyword(s):  
Mixed Models ◽  
Repeated Measures ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Linear Time ◽  
Case Series ◽  
Model Fit ◽  
Repeated Measures Analysis ◽  
Technical Issues ◽  
Better Than

We have some criticism regarding some technical issues. Mixed models have begun to play a pivotal role in statistical analyses and offer many advantages over more conventional analyses regarding repeated variance analyses. First, they allow to avoid conducting multiple t-tests; second, they can accommodate for within-patient correlation; third, they allow to incorporate not only a random coefficient, but also a random slope, typically ‘linear’ time in longitudinal case series when there are enough data and patients’ trajectories vary a lot and improving model fit.

Does Sample Attrition Affect the Assessment of Frailty Trajectories Among Older Adults? A Joint Model Approach

Gerontology ◽  
2018 ◽  
Vol 64 (5) ◽  
pp. 430-439 ◽  
Author(s):  
Erwin Stolz ◽  
Hannes Mayerl ◽  
Éva Rásky ◽  
Wolfgang Freidl
Keyword(s):  
Older Adults ◽  
Mixed Models ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Linear Mixed Models ◽  
Joint Model ◽  
Joint Models ◽  
Sample Attrition ◽  
Standard Linear ◽  
The Impact

Background: Frailty constitutes an important risk factor for adverse outcomes among older adults. In longitudinal studies on frailty, selective sample attrition may threaten the validity of results. Objective: To assess the impact of sample attrition on frailty index trajectories and gaps related to socio-economic status (education) therein among older adults in Europe. Methods: A total of 64,143 observations from 21,044 respondents (50+) from the Survey of Health, Ageing and Retirement in Europe across 12 years of follow-up (2004–2015) and subject to substantial sample attrition (59%) were analysed. We compared results of a standard linear mixed model assuming missing at random (MAR) sample attrition with a joint model assuming missing not at random sample attrition. Results: Estimated frailty trajectories of both the mixed and joint models were identical up to an age of 80 years, above which modest underestimation occurred when a standard linear mixed model was used rather than a joint model. The latter effect was larger for men than women. Substantial education-based inequality in frailty continued throughout old age in both the mixed and joint models. Conclusion: Linear mixed models assuming MAR sample attrition provided good estimates of frailty trajectories up until high age. Thus, the validity of existing studies estimating frailty trajectories based on standard linear mixed models seems not threatened by substantial sample attrition.

scholarly journals A New Three-parameter Xgamma Fréchet Distribution with Different Methods of Estimation and Applications

2021 ◽  
pp. 291-308
Author(s):  
Mohamed Ibrahim Mohamed ◽  
Laba Handique ◽  
Subrata Chakraborty ◽  
Nadeem Shafique Butt ◽  
Haitham M. Yousof
Keyword(s):  
Real Life ◽  
Estimation Methods ◽  
Data Sets ◽  
Clear Preference ◽  
Life Data ◽  
Fréchet Distribution ◽  
Real Life Data ◽  
Proposed Model ◽  
Frechet Distribution

In this article an attempt is made to introduce a new extension of the Fréchet model called the Xgamma Fréchet model. Some of its properties are derived. The estimation of the parameters via different estimation methods are discussed. The performances of the proposed estimation methods are investigated through simulations as well as real life data sets. The potentiality of the proposed model is established through modelling of two real life data sets. The results have shown clear preference for the proposed model compared to several know competing ones.

scholarly journals Factors affecting windstorm damage at the stand level in hemiboreal forests in Latvia: case study of 2005 winter storm

Silva Fennica ◽  
2018 ◽  
Vol 52 (4) ◽  
Author(s):  
Janis Donis ◽  
Mara Kitenberga ◽  
Guntars Snepsts ◽  
Edgars Dubrovskis ◽  
Aris Jansons
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Canopy Layer ◽  
Tree Species Composition ◽  
Management Planning ◽  
Factors Affecting ◽  
Forest Management Planning ◽  
Forest Resilience ◽  
Socio Economic Impact ◽  
Mineral Soils

In managed European hemiboreal forests, windstorms have a notable ecological and socio-economic impact. In this study, stand properties affecting windstorm damage occurrence at the stand-level were assessed using a Generalized Linear Mixed model. After 2005 windstorm, 5959 stands dominated by birch ( spp.), Scots pine ( L.) and Norway spruce ( (L.) Karst.), with mean height > 10 m were inventoried. Windstorm damage was positively associated with spruce and pine-dominated stands, increasing mean height, fresh forest edges, decreasing time since the last thinning and stronger wind gusts. Tree species composition – mixed or monodominant – was not statistically significant in the model; while, the admixture of spruce in the canopy layer was positively associated with higher windstorm damage. Stands on peat soils were more damaged than stands on mineral soils. Birch stands were more damaged than pine stands. This information could be used in forest management planning, selection of silvicultural treatments to increase forest resilience to natural disturbances.BetulaPinus sylvestrisPicea abies

A qualitative study of the optimal control model for an electric power generating system

2012 ◽  
Vol 23 (2) ◽  
pp. 65-72
Author(s):  
Yidiat O. Aderinto ◽  
Mathias O. Bamigbola
Keyword(s):  
Optimal Control ◽  
Electric Power ◽  
Real Life ◽  
Minimum Cost ◽  
Fuel Cost ◽  
Transmission Losses ◽  
Factors Affecting ◽  
Real Life Data ◽  
The Cost ◽  
Generating System

The economic independence of any nation depends largely on the supply of abundant and reliable electric power and the extension of electricity services to all towns and villages in the country. In this work, the mathematical study of an electric power generating system model was presented via optimal control theory, in an attempt to maximize the power generating output and minimize the cost of generation. The factors affecting power generation at minimum cost are operating efficiencies of generators, fuel cost and transmission losses, but the most efficient generator in the system may not guarantee minimum cost as it may be located in an area where fuel cost is high. We choose the generator capacity as our control ui(t), since we cannot neglect the operation limitation on the equipment because of its lifespan, the upper bound for ui(t) is choosing to be 1 to represent the total capability of the machine and 0 to be the lower bound. The model is analyzed, generation loss free equilibrium and stability is established, and finally applications using real life data is presented using one generator and three generator systems respectively.

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