scholarly journals A Convenient Method of Decomposing the Gini Index by Population Subgroups

2014 ◽  
Vol 30 (1) ◽  
pp. 91-105 ◽  
Author(s):  
Tomson Ogwang
Keyword(s):  
Convenient Method ◽  
Standard Error ◽  
Regression Models ◽  
Gini Index ◽  
Artificial Data ◽  
Estimated Parameters ◽  
Subgroup Decomposition

Abstract We propose a convenient method of estimating the within-group, between-group, and interaction components of the overall traditional Gini index from the estimated parameters of underlying “trick regression models” involving known forms of heteroscedasticity related to income. Two illustrative examples involving both real and artificial data are provided. The issue of appropriate standard error of the subgroup decomposition is also discussed.

Simplified biplanar classification for heterotopic ossification is more predictive of patient-reported outcomes than the Brooker classification after anterior total hip arthroplasty

2021 ◽  
pp. 112070002110391
Author(s):  
Leonard T Onsen ◽  
Vivian W Ouyang ◽  
Andrew E Jimenez ◽  
Peter F Monahan ◽  
Ajay C Lall ◽  
...  
Keyword(s):  
Total Hip Arthroplasty ◽  
Heterotopic Ossification ◽  
Hip Arthroplasty ◽  
Standard Error ◽  
Regression Models ◽  
Patient Reported Outcomes ◽  
Interobserver Reliability ◽  
Total Hip ◽  
Patient Reported ◽  
Grade 3

Background: Heterotopic ossification (HO) commonly occurs after total hip arthroplasty (THA) and can adversely impact clinical outcomes. The purpose of this study is to propose a more reliable HO grading method that is better predictive of patient-reported outcomes (PROs) after THA than the Brooker classification. Methods: 513 THAs (62 ± 10 years old) were reviewed. The incidence and grade of HO was evaluated using the Brooker grading system and a simplified biplanar classification system (grade 1: ⩾1 cm between bone on both anteroposterior and lateral views, grade 2: <1 cm between bone on either view). The modified Harris Hip Score (mHHS), Forgotten Joint Score (FJS), and visual analogue scale (VAS) for pain were collected at minimum of 2 years after surgery and were compared between HO grades using multiple regression models. Results: The incidence of HO varied by Brooker grade (grade 1, 23.4%; grade 2, 22.4%; grade 3, 7.2%; grade 4, 0%) and biplanar grade (grade 1: 45.6%; grade 2: 7.4%). The biplanar classification demonstrated higher interobserver reliability than the Brooker classification (κ = 0.95 and 0.91, respectively). Brooker grade 3 HO decreased the mHHS by 6.5 (standard error: 2.7) but did not have a significant effect on FJS or VAS. Biplanar grade 2 HO decreased the mHHS by 9.9 (standard error: 2.7), the FJS by 12.9 (standard error: 4.51) and increased the VAS pain score by 0.81 (standard error: 0.35). The Cox test was used to compare the fit of regression models and determined the biplanar classification was a significantly better predictor than the Brooker classification ( p < 0.001). Conclusions: Biplanar grade 2 HO had a significant negative influence on PROs. Contrary to previous literature, these results show clinical significance of non-bridging HO. Compared with the Brooker classification, the biplanar classification has greater interobserver reliability and is more predictive of outcomes after THA.

scholarly journals Fixed versus Random Effects in Poisson Regression Models for Claim Counts: A Case Study with Motor Insurance

2006 ◽  
Vol 36 (1) ◽  
pp. 285-301 ◽  
Author(s):  
Jean-Philippe Boucher ◽  
Michel Denuit
Keyword(s):  
Random Effects ◽  
Poisson Regression ◽  
Regression Models ◽  
Third Party ◽  
Numerical Illustration ◽  
Random Effects Models ◽  
Estimated Parameters ◽  
Motor Insurance ◽  
Actual Meaning

This paper examines the validity of some stylized statements that can be found in the actuarial literature about random effects models. Specifically, the actual meaning of the estimated parameters and the nature of the residual heterogeneity are discussed. A numerical illustration performed on a Belgian motor third party liability portfolio supports this discussion.

scholarly journals Physiological Aldosterone Concentrations Are Associated with Alterations of Lipid Metabolism: Observations from the General Population

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
M. Hannich ◽  
H. Wallaschofski ◽  
M. Nauck ◽  
M. Reincke ◽  
C. Adolf ◽  
...  
Keyword(s):  
Lipid Metabolism ◽  
General Population ◽  
Linear Regression ◽  
Standard Error ◽  
Regression Models ◽  
Adult Population ◽  
Density Lipoprotein ◽  
Lipoprotein Cholesterol ◽  
Inverse Association ◽  
Linear Regression Models

Objective. Aldosterone and high-density lipoprotein cholesterol (HDL-C) are involved in many pathophysiological processes that contribute to the development of cardiovascular diseases. Previously, associations between the concentrations of aldosterone and certain components of the lipid metabolism in the peripheral circulation were suggested, but data from the general population is sparse. We therefore aimed to assess the associations between aldosterone and HDL-C, low-density lipoprotein cholesterol (LDL-C), total cholesterol, triglycerides, or non-HDL-C in the general adult population. Methods. Data from 793 men and 938 women aged 25–85 years who participated in the first follow-up of the Study of Health in Pomerania were obtained. The associations of aldosterone with serum lipid concentrations were assessed in multivariable linear regression models adjusted for sex, age, body mass index (BMI), estimated glomerular filtration rate (eGFR), and HbA1c. Results. The linear regression models showed statistically significant positive associations of aldosterone with LDL-C (β-coefficient = 0.022, standard error = 0.010, p=0.03) and non-HDL-C (β-coefficient = 0.023, standard error = 0.009, p=0.01) as well as an inverse association of aldosterone with HDL-C (β-coefficient = −0.022, standard error = 0.011, p=0.04). Conclusions. The present data show that plasma aldosterone is positively associated with LDL-C and non-HDL-C and inversely associated with HDL-C in the general population. Our data thus suggests that aldosterone concentrations within the physiological range may be related to alterations of lipid metabolism.

Evaluation of standard error of forecast of runoff volume using linear regression models

2002 ◽  
Vol 29 (5) ◽  
pp. 635-640 ◽  
Author(s):  
Wuben Luo ◽  
Eric Weiss
Keyword(s):  
Linear Regression ◽  
Standard Error ◽  
Regression Models ◽  
Linear Regression Models ◽  
Modeling Error ◽  
Reservoir Operations ◽  
Microsoft Excel ◽  
Runoff Volume ◽  
Modeling Errors ◽  
Significant Underestimation

Optimizing reservoir operations requires forecasts of seasonal inflow and a good understanding of the associated uncertainties. When forecasting seasonal runoff volume to a reservoir using a linear regression model, hydrologic forecasters typically use the standard error of residuals as the standard error of forecast to give water managers a sense of uncertainties in the forecast. However, this practice accounts for only the random error and ignores the modeling error in the volume forecast, resulting in underestimation of the standard error of the forecast. The underestimation can become significant in extreme runoff years for which reservoir operations tend to be most critical. This paper presents the algorithm for calculating the standard error of forecast, which takes into consideration both random and modeling errors. A simple way of calculating the standard error of forecast using built-in functions in Microsoft Excel is described. An example is used to demonstrate the potentially significant underestimation of the true error of a forecast if modeling error is ignored.Key words: standard error of forecast, residuals, runoff volume forecast, regression analysis.

scholarly journals Magnitudes of New Zealand earthquakes, 1901-1993

1998 ◽  
Vol 31 (4) ◽  
pp. 260-280 ◽  
Author(s):  
D. J. Dowrick ◽  
D. A. Rhoades
Keyword(s):  
New Zealand ◽  
Surface Wave ◽  
Standard Error ◽  
Regression Models ◽  
Local Magnitude ◽  
Surface Wave Magnitude ◽  
Upper Limit ◽  
Seismological Observatory ◽  
Consistent Basis

Determinations of surface-wave magnitude (Ms) are made on a consistent basis for 202 selected New Zealand earthquakes over the period 1901-1993, including most post-1942 events with local magnitude not less than 6.0 and centroid depth less than 45 km. These determinations have led to a reassessment of magnitudes and locations of some earlier events in the New Zealand Seismological Observatory Catalogue of local magnitudes (ML), in some cases with substantial revisions. The surface-wave magnitudes are compared with local magnitudes and moment magnitudes (Mw), where available, and the relations between these three variables and centroid depth are examined through regression models. The absence of surface-wave observations for some earthquakes allows an upper limit to be placed on their likely moment magnitudes. The analysis shows that estimates of Mw derived from Ms will have a standard error of about 0.15 and Mw derived from ML a standard error of about 0.3.

scholarly journals Ruminal pH and N-NH3 behavior: a Bayesian approach

2016 ◽  
Vol 37 (1) ◽  
pp. 311
Author(s):  
Osvaldo Martins Souza ◽  
Elias Nunes Martins ◽  
Robson Marcelo Rossi ◽  
Carlos Antonio Lopes de Oliveira ◽  
Sílvia Cristina de Aguiar ◽  
...  
Keyword(s):  
Bayesian Approach ◽  
Regression Models ◽  
Correlated Data ◽  
Linear Functions ◽  
A Posteriori ◽  
Ruminal Ph ◽  
Estimated Parameters ◽  
A Posteriori Estimates ◽  
Least Squares Estimates ◽  
The Bayesian Approach

In this work, we present the Bayesian approach as an alternative to frequentist analysis regarding correlated data of pH and N-NH3 in the Holstein cow rumen. It was observed that for pH and N-NH3 data, a posteriori estimates of coefficients of the regression models were significant, which was not observed for least-squares estimates. Thus, the Bayesian approach allowed inferences that were directly linked to the sampling of parameters of interest and statistical comparisons of non-linear functions of the estimated parameters.

scholarly journals What Triggers Poverty of Young Nationals and Young Migrants? A Comparative Macroeconomic Approach

2020 ◽  
Vol 9 (2) ◽  
pp. 13-29
Author(s):  
Smaranda Cimpoeru
Keyword(s):  
Social Exclusion ◽  
Cross Section ◽  
Preliminary Analysis ◽  
Regression Models ◽  
Gini Index ◽  
Poverty Reduction ◽  
Social Categories ◽  
Economic Determinants ◽  
Panel Data Regression ◽  
Data Regression

AbstractIdentifying the macro-economic determinants of poverty is a key concern for developing poverty reduction policies. Since young people and young migrants in particular are more exposed to poverty, establishing the factors that trigger poverty among these social categories has even more relevance. A preliminary analysis shows that significant differences exist between at-risk-of poverty or social exclusion rate of young migrants and young nationals across European countries. For a more thorough study of the reasons behind these differences in poverty rates between young migrants and young nationals, two panel data regression models are estimated on a cross-section of 23 countries over the period 2010 – 2018 (one model for young migrants, the other for young nationals). Results confirm the main theories in the specialty literature: unemployment and inequality (measured by the Gini index) are the main triggers of poverty or social exclusion both for young nationals and young migrants. However, the income is significant for reducing poverty only for young nationals, but not for the young migrants. This result reinforces the necessity of better integration policies for young migrants in richer Member States.

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