Regression analysis of compositional data when both the dependent variable and independent variable are components

It is well known that regression analyses involving compositional data need special attention because the data are not of full rank. For a regression analysis where both the dependent and independent variable are components we propose a transformation of the components emphasizing their role as dependent and independent variables. A simple linear regression can be performed on the transformed components. The regression line can be depicted in a ternary diagram facilitating the interpretation of the analysis in terms of components. An exemple with time-budgets illustrates the method and the graphical features

Use of multilevel logistic regression to identify the causes of differential item functioning

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Sample size requirements for interval estimation of the strengthof association effect sizes in multiple regression analysis

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A comparison of discriminant logistic regression and Item Response Theory Likelihood-Ratio Tests for Differential Item Functioning (IRTLRDIF) in polytomous short tests

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Including a time-of-year effect in the analysis of a matched case-control study

Motivated by a matched case-control study to investigate potential risk factors for meningococcal disease amongst adolescents, we consider the analysis of matched case-control studies where disease incidence, and possibly other risk factors, vary with time of year. For the cases, the time of infection may be recorded. For controls, however, the recorded time is simply the time of data collection, which is shortly after the time of infection for the matched case, and so depends on the latter. We show that the effect of risk factors and interactions may be adjusted for the time of year effect in a standard conditional logistic regression analysis without introducing any bias. We also show that, if the time delay between data collection for cases and controls is constant, provided this delay is not very short, estimates of the time of year effect are approximately unbiased. In the case that the length of the delay varies over time, the estimate of the time of year effect is biased. We obtain an approximate expression for the degree of bias in this case. Copyright © 2004 John Wiley & Sons, Ltd.

A study of the effect of heat source location in a ventilated room using multiple regression analysis

Multiple regression analysis is a statistical technique which allows to predict a dependent variable from m ore than one independent variable and also to determine influential independent variables. Using experimental data, in this study the multiple regression analysis is applied to predict the room mean velocity and determine the most influencing parameters on the velocity. More than 120 experiments for four different heat source locations were carried out in a test chamber with a high level wall mounted air supply terminal at air change rates 3-6 ach. The influence of the environmental parameters such as supply air momentum, room heat load, Archimedes number and local temperature ratio, were examined by two methods: a simple regression analysis incorporated into scatter matrix plots and multiple stepwise regression analysis. It is concluded that, when a heat source is located along the jet centre line, the supply momentum mainly influences the room mean velocity regardless of the plume strength. However, when the heat source is located outside the jet region, the local temperature ratio (the inverse of the local heat removal effectiveness) is a major influencing parameter.

Prediction in Multilevel Logistic Regression

The purpose of this article is to present a new method to predict the response variable of an observation in a new cluster for a multilevel logistic regression. The central idea is based on the empirical best estimator for the random effect. Two estimation methods for multilevel model are compared: penalized quasi-likelihood and Gauss-Hermite quadrature. The performance measures for the prediction of the probability for a new cluster observation of the multilevel logistic model in comparison with the usual logistic model are examined through simulations and an application.

Regression analysis of mean quality-adjusted survival time based on pseudo-observations

Regression models for the mean quality-adjusted survival time are specified from hazard functions of transitions between two states and the mean quality-adjusted survival time may be a complex function of covariates. We discuss a regression model for the mean quality-adjusted survival (QAS) time based on pseudo-observations, which has the advantage of directly modeling the effect of covariates in the QAS time. Both Monte Carlo Simulations and a real data set are studied. Copyright (C) 2009 John Wiley & Sons, Ltd.

Authorship, Collaboration, and Funding Trends in Implantology Literature: Analysis of Five Journals From 2005 to 2009

Purpose: To identify the trend of authorship in dental implant by exploring the prevalence of coauthored articles and to investigate the collaboration efforts, trends in funding involved in original articles, and their relationships. Materials: Articles published in the Clinical Oral Implants Research, International Journal of Oral & Maxillofacial Implants, Clinical Implant Dentistry and Related Research, Implant Dentistry, and Journal of Oral Implantology from 2005 to 2009 were reviewed. Nonoriginal articles were excluded. For each included articles, number of authors, collaboration efforts, and extramural funding were recorded. Descriptive and analytical statistics (alpha = 0.05), including logistic regression analysis and chi(2) test, were used. Results: From a total of 2085 articles, 1503 met the inclusion criteria. Publications with 5 or more authors increased over time (P = 0.813). The amount of collaboration among different disciplines, institutions, and countries all increased. The greatest increase of collaboration was seen among institutions (P = 0.09). Non-funding studies decreased over time (P = 0.031). There was a strong association between collaboration and funding for the manuscripts during the years studied (OR, 1.5). Conclusion: The number of authors per articles and collaborative studies increased over time in implant-related journals. Collaborative studies were more likely to be funded. (Implant Dent 2011;20:68-75)

Some practical advice on polynomial regression analysis from blocked response surface designs

It is often necessary to run response surface designs in blocks. In this paper the analysis of data from such experiments, using polynomial regression models, is discussed. The definition and estimation of pure error in blocked designs are considered. It is recommended that pure error is estimated by assuming additive block and treatment effects, as this is more consistent with designs without blocking. The recovery of inter-block information using REML analysis is discussed, although it is shown that it has very little impact if thc design is nearly orthogonally blocked. Finally prediction from blocked designs is considered and it is shown that prediction of many quantities of interest is much simpler than prediction of the response itself.

Analysis of criteria for metabolic syndrome in a population-based study of Japanese-Brazilians

Objective: Criteria for metabolic syndrome (MS) differ particularly regarding the definition of central obesity and consequently, there could be differences in the assessment of cardiovascular risk. We estimated the prevalence of metabolic syndrome, compared the agreement of the World Health Organization (WHO) criteria with the standard and a modified National Cholesterol Education Program (NCEP) criterion and investigated whether additional factors were associated with the diagnosis of the syndrome in a Japanese descendant population.Methods: In this cross-sectional, population-based survey, 1166 Japanese-Brazilians (533 men, 633 women) aged 57.4 +/- 12.4 years with mean body mass index (BMI) and waist of 25.2 +/- 4.0 kg/m(2) and 84.5 +/- 10.6 cm, respectively, were included. McNemar and kappa statistics were used to assess the concordance between WHO criteria with the standard and a modified NCEP criteria (waist of 90 and 80 cm, for men and women, respectively). in logistic regression analysis, a number of metabolic variables and albumin-to-creatinine ratio were included to test independent associations with metabolic syndrome defined by the modified NCEP criteria.Results: According to WHO, 55.4% (95% Cl 52.5-58.2%) of the subjects had MS and to NCEP 47.4% (95% Cl 44.6-50.0%). WHO criterion detected 48.3% of central obese subjects while NCEP only 14.0%. Kappa statistics showed a good strength of agreement (k = 0.67, p < 0.01) between WHO and NCEP standard definitions of MS. Using the modified NCEP criterion for Asians, more subjects with metabolic syndrome were identified (58%) and agreement with WHO was improved (k = 0.72, p < 0.001). However, similar Framingham risk scores were attributed to the subsets of subjects classified by any of the three criteria. Areas under the receiver operating characteristic curves, obtained for the modified waist values to diagnose metabolic syndrome according to WHO, were > 0.80 and corresponded, respectively, to sensitivity and specificity of 63 and 83% for men and 77 and 72% for women. In final logistic regression model, age, male sex, BMI and homeostasis model assessment-insulin resistance but not with albumin-to-creatinine ratio (ACR) were independently associated with the syndrome.Conclusions: High prevalence of MS, independent of the criterion considered, was found in this Japanese-Brazilian population. The replacement of waist cutoff by those proposed by WHO for Asians lead to this diagnosis in a higher number of subjects with elevated cardiovascular risk. Our data did not support that ACR should be included in the classical definition of MS in Japanese descendants as previously suggested by WHO.

Prevalence of Treponema Species Detected in Endodontic Infections: Systematic Review and Meta-regression Analysis

Introduction: This systematic review and meta-regression analysis aimed to calculate a combined prevalence estimate and evaluate the prevalence of different Treponema species in primary and secondary endodontic infections, including symptomatic and asymptomatic eases. Methods: The MEDLINE/PubMed, Embase, Scielo, Web of Knowledge, and Scopus data-bases were searched without starting date restriction up to and including March 2014. Only reports in English were included. The selected literature was reviewed by 2 authors and classified as suitable or not to be included in this review. Lists were compared, and, in case of disagreements, decisions were made after a discussion based on inclusion and exclusion criteria. A pooled prevalence of Treponema species in endodontic infections was estimated. Additionally, a meta-regression analysis was performed. Results: Among the 265 articles identified in the initial search, only 51 were included in the final analysis. The studies were classified into 2 different groups according to the type of endodontic infection and whether it was an exclusively primary/secondary study (n = 36) or a primary/secondary comparison (n = 15). The pooled prevalence of Treponema species was 41.5% (95% confidence interval, 35.9-47.0). In the multivariate model of meta-regression analysis, primary endodontic infections (P < .001), acute apical abscess, symptomatic apical periodontitis (P < .001), and concomitant presence of 2 or more species (P = .028) explained the heterogeneity regarding the prevalence rates of Treponema species. Conclusions: Our findings suggest that Treponema species are important pathogens involved in endodontic infections, particularly in cases of primary and acute infections.