Assessment of variance components in nonlinear mixed-effects elliptical models

The issue of assessing variance components is essential in deciding on the inclusion of random effects in the context of mixed models. In this work we discuss this problem by supposing nonlinear elliptical models for correlated data by using the score-type test proposed in Silvapulle and Silvapulle (1995). Being asymptotically equivalent to the likelihood ratio test and only requiring the estimation under the null hypothesis, this test provides a fairly easy computable alternative for assessing one-sided hypotheses in the context of the marginal model. Taking into account the possible non-normal distribution, we assume that the joint distribution of the response variable and the random effects lies in the elliptical class, which includes light-tailed and heavy-tailed distributions such as Student-t, power exponential, logistic, generalized Student-t, generalized logistic, contaminated normal, and the normal itself, among others. We compare the sensitivity of the score-type test under normal, Student-t and power exponential models for the kinetics data set discussed in Vonesh and Carter (1992) and fitted using the model presented in Russo et al. (2009). Also, a simulation study is performed to analyze the consequences of the kurtosis misspecification.

Influence diagnostics for elliptical semiparametric mixed models

In this paper we extend semiparametric mixed linear models with normal errors to elliptical errors in order to permit distributions with heavier and lighter tails than the normal ones. Penalized likelihood equations are applied to derive the maximum penalized likelihood estimates (MPLEs) which appear to be robust against outlying observations in the sense of the Mahalanobis distance. A reweighed iterative process based on the back-fitting method is proposed for the parameter estimation and the local influence curvatures are derived under some usual perturbation schemes to study the sensitivity of the MPLEs. Two motivating examples preliminarily analyzed under normal errors are reanalyzed considering some appropriate elliptical errors. The local influence approach is used to compare the sensitivity of the model estimates.

The presence of anti-citrullinated protein antibodies (ACPA) and rheumatoid factor on patients with rheumatoid arthritis (RA) does not interfere with the chance of clinical remission in a follow-up of 3 years

Autoantibodies in early rheumatoid arthritis (RA) have important diagnostic value. The association between the presence of autoantibodies against cyclic citrullinated peptide and the response to treatment is controversial. To prospectively evaluate a cohort of patients with early rheumatoid arthritis (< 12 months of symptoms) in order to determine the association between serological markers (rheumatoid factor (RF), anti-citrullinated protein antibodies) such as anti-cyclic citrullinated peptide antibodies (anti-CCP) and citrullinated anti-vimentin (anti-Sa) with the occurrence of clinical remission, forty patients diagnosed with early RA at the time of diagnosis were evaluated and followed for 3 years, in use of standardized therapeutic treatment. Demographic and clinical data were recorded, disease activity score 28 (DAS 28), as well as serology tests (ELISA) for RF (IgM, IgG, and IgA), anti-CCP (CCP2, CCP3, and CCP3.1) and anti-Sa in the initial evaluation and at 3, 6, 12, 18, 24, and 36 months of follow-up. The outcome evaluated was the percentage of patients with clinical remission, which was defined by DAS 28 lower than 2.6. Comparisons were made through the Student t test, mixed-effects regression analysis, and analysis of variance (significance level of 5%). The mean age was 45 years, and a female predominance was observed (90%). At the time of diagnosis, RF was observed in 50% of cases (RF IgA-42%, RF IgG-30%, and RF IgM-50%), anti-CCP in 50% (no difference between CCP2, CCP3, and CCP3.1) and anti-Sa in 10%. After 3 years, no change in the RF prevalence and anti-CCP was observed, but the anti-Sa increased to 17.5% (P = 0.001). The percentage of patients in remission, low, moderate, and intense disease activity, according to the DAS 28, was of 0, 0, 7.5, and 92.5% (initial evaluation) and 22.5, 7.5, 32.5, and 37.5% (after 3 years). There were no associations of the presence of autoantibodies in baseline evaluation and in serial analysis with the percentage of clinical remission during follow-up of 3 years The presence of autoantibodies in early RA has no predictive value for clinical remission in early RA.

Genetic analyses of smoking initiation, persistence, quantity, and age-at-onset of regular cigarette use in Brazilian families: the Baependi Heart Study

Background: The purpose of this study was to estimate the genetic influences on the initiation of cigarette smoking, the persistence, quantity and age-at-onset of regular cigarette use in Brazilian families. Methods: The data set consisted of 1,694 individuals enrolled in the Baependi Heart Study. The heritability and the heterogeneity in genetic and environmental variance components by gender were estimated from variance components approaches, using the SOLAR (Sequential Oligogenic Linkage Analysis Routines) computer package. The mixed-effects Cox model was used for the genetic analysis of the age-at onset of regular cigarette use. Results: The heritability estimates were high (> 50%) for smoking initiation and were intermediate, ranging from 23.4 to 31.9%, for smoking persistence and quantity. Significant evidence for heterogeneity in variance components by gender was observed for smoking initiation and age-at-onset of regular cigarette use. Genetic factors play an important role in the interindividual variation of these phenotypes in females, while in males there is a predominant environmental component, which could be explained by greater social influences in the initiation of tobacco use. Conclusions: Significant heritabilities were observed in smoking phenotypes for both males and females from the Brazilian population. These data add to the literature and are concordant with the notion of significant biological determination in smoking behavior. Samples from the Baependi Heart Study may be valuable for the mapping of genetic loci that modulate this complex biological trait.

Quantitative MRI of Vastus Medialis, Vastus Lateralis and Gluteus Medius Muscle Workload after Squat Exercise: Comparison Between Squatting with Hip Adduction and Hip Abduction

The aim of the present study was to evaluate the use MRI to quantify the workload of gluteus medius (GM), vastus medialis (VM) and vastus lateralis (VL) muscles in different types of squat exercises. Fourteen female volunteers were evaluated, average age of 22 +/- 2 years, sedentary, without clinical symptoms, and without history of previous lower limb injuries. Quantitative MRI was used to analyze VM, VL and GM muscles before and after squat exercise, squat associated with isometric hip adduction and squat associated with isometric hip abduction. Multi echo images were acquired to calculate the transversal relaxation times (T2) before and after exercise. Mixed Effects Model statistical analysis was used to compare images before and after the exercise (Delta T2) to normalize the variability between subjects. Imaging post processing was performed in Matlab software. GM muscle was the least active during the squat associated with isometric hip adduction and VM the least active during the squat associated with isometric hip abduction, while VL was the most active during squat associated with isometric hip adduction. Our data suggests that isometric hip adduction during the squat does not increase the workload of VM, but decreases the GM muscle workload. Squat associated with isometric hip abduction does not increase VL workload.

Efficacy of brief alcohol screening intervention for college students (BASICS): a meta-analysis of randomized controlled trials

Background: Many studies reported that brief interventions are effective in reducing excessive drinking. This study aimed to assess the efficacy of a protocol of brief intervention for college students (BASICS), delivered face-to-face, to reduce risky alcohol consumption and negative consequences. Methods: A systematic review with meta-analysis was performed by searching for randomized controlled trials (RCTs) in Medline, PsycInfo, Web of Science and Cochrane Library databases. A quality assessment of RCTs was made by using a validated scale. Combined mean effect sizes, using meta-analysis random-effects models, were calculated. Results: 18 studies were included in the review. The sample sizes ranged from 54 to 1275 (median = 212). All studies presented a good evaluation of methodological quality and four were found to have excellent quality. After approximately 12 months of follow-up, students receiving BASICS showed a significant reduction in alcohol consumption (difference between means = -1.50 drinks per week, 95% CI: -3.24 to -0.29) and alcohol-related problems (difference between means = -0.87, 95% CI: -1.58 to -0.20) compared to controls. Conclusions: Overall, BASICS lowered both alcohol consumption and negative consequences in college students. Gender and peer factors seem to play an important role as moderators of behavior change in college drinking. Characteristics of BASICS procedure have been evaluated as more favorable and acceptable by students in comparison with others interventions or control conditions. Considerations for future researches were discussed.

Trends of the genetic connectedness measures among Nelore beef cattle herds

Validity of comparisons between expected breeding values obtained from best linear unbiased prediction procedures in genetic evaluations is dependent on genetic connectedness among herds. Different cattle breeding programmes have their own particular features that distinguish their database structure and can affect connectedness. Thus, the evolution of these programmes can also alter the connectedness measures. This study analysed the evolution of the genetic connectedness measures among Brazilian Nelore cattle herds from 1999 to 2008, using the French Criterion of Admission to the group of Connected Herds (CACO) method, based on coefficients of determination (CD) of contrasts. Genetic connectedness levels were analysed by using simple and multiple regression analyses on herd descriptors to understand their relationship and their temporal trends from the 19992003 to the 20042008 period. The results showed a high level of genetic connectedness, with CACO estimates higher than 0.4 for the majority of them. Evaluation of the last 5-year period showed only a small increase in average CACO measures compared with the first 5 years, from 0.77 to 0.80. The percentage of herds with CACO estimates lower than 0.7 decreased from 27.5% in the first period to 16.2% in the last one. The connectedness measures were correlated with percentage of progeny from connecting sires, and the artificial insemination spread among Brazilian herds in recent years. But changes in connectedness levels were shown to be more complex, and their complete explanation cannot consider only herd descriptors. They involve more comprehensive changes in the relationship matrix, which can be only fully expressed by the CD of contrasts.

Transmission of Human Herpesvirus Type 8 Infection Within Families in American Indigenous Populations From the Brazilian Amazon

Background. The intrafamilial dynamics of endemic infection with human herpesvirus type 8 (HHV-8) in Amerindian populations is unknown. Methods. Serum samples were obtained from 517 Amerindians and tested for HHV-8 anti-latent nuclear antigen (anti-LANA) and antilytic antibodies by immunofluorescence assays. Logistic regression and mixed logistic models were used to estimate the odds of being HHV-8 seropositive among intrafamilial pairs. Results. HHV-8 seroprevalence by either assay was 75.4% (95% confidence interval [CI]: 71.5%-79.1%), and it was age-dependent (P-trend<.001). Familial dependence in HHV-8 seroprevalence by either assay was found between mother-offspring (odds ratio [OR], 5.44; 95% CI: 1.62-18.28) and siblings aged >= 10 years (OR 4.42, 95% CI: 1.70-11.45) or siblings in close age range (<5 years difference) (OR 3.37, 95% CI: 1.21-9.40), or in families with large (>4) number of siblings (OR, 3.20, 95% CI: 1.33-7.67). In separate analyses by serological assay, there was strong dependence in mother-offspring (OR 8.94, 95% CI: 2.94-27.23) and sibling pairs aged >= 10 years (OR, 11.91, 95% CI: 2.23-63.64) measured by LANA but not lytic antibodies. Conclusions. This pattern of familial dependence suggests that, in this endemic population, HHV-8 transmission mainly occurs from mother to offspring and between close siblings during early childhood, probably via saliva. The mother to offspring dependence was derived chiefly from anti-LANA antibodies.

Cough and dyspnea during bronchoconstriction: comparison of different stimuli

Abstract Background Bronchial challenge tests are used to evaluate bronchial responsiveness in diagnosis and follow-up of asthmatic patients. Challenge induced cough has increasingly been recognized as a valuable diagnostic tool. Various stimuli and protocols have been employed. The aim of this study was to compare cough and dyspnea intensity induced by different stimuli. Methods Twenty asthmatic patients underwent challenge tests with methacholine, bradykinin and exercise. Cough was counted during challenge tests. Dyspnea was assessed by modified Borg scale and visual analogue scale. Statistical comparisons were performed by linear mixed-effects model. Results For cough evaluation, bradykinin was the most potent trigger (p < 0.01). In terms of dyspnea measured by Borg scale, there were no differences among stimuli (p > 0.05). By visual analogue scale, bradykinin induced more dyspnea than other stimuli (p ≤ 0.04). Conclusion Bradykinin seems to be the most suitable stimulus for bronchial challenge tests intended for measuring cough in association with bronchoconstriction.

Influence diagnostics in heteroscedastic and/or autoregressive nonlinear elliptical models for correlated data

In this paper, we propose nonlinear elliptical models for correlated data with heteroscedastic and/or autoregressive structures. Our aim is to extend the models proposed by Russo et al. [22] by considering a more sophisticated scale structure to deal with variations in data dispersion and/or a possible autocorrelation among measurements taken throughout the same experimental unit. Moreover, to avoid the possible influence of outlying observations or to take into account the non-normal symmetric tails of the data, we assume elliptical contours for the joint distribution of random effects and errors, which allows us to attribute different weights to the observations. We propose an iterative algorithm to obtain the maximum-likelihood estimates for the parameters and derive the local influence curvatures for some specific perturbation schemes. The motivation for this work comes from a pharmacokinetic indomethacin data set, which was analysed previously by Bocheng and Xuping [1] under normality.

A mixed model QTL analysis for sugarcane multiple-harvest-location trial data

Sugarcane-breeding programs take at least 12 years to develop new commercial cultivars. Molecular markers offer a possibility to study the genetic architecture of quantitative traits in sugarcane, and they may be used in marker-assisted selection to speed up artificial selection. Although the performance of sugarcane progenies in breeding programs are commonly evaluated across a range of locations and harvest years, many of the QTL detection methods ignore two- and three-way interactions between QTL, harvest, and location. In this work, a strategy for QTL detection in multi-harvest-location trial data, based on interval mapping and mixed models, is proposed and applied to map QTL effects on a segregating progeny from a biparental cross of pre-commercial Brazilian cultivars, evaluated at two locations and three consecutive harvest years for cane yield (tonnes per hectare), sugar yield (tonnes per hectare), fiber percent, and sucrose content. In the mixed model, we have included appropriate (co)variance structures for modeling heterogeneity and correlation of genetic effects and non-genetic residual effects. Forty-six QTLs were found: 13 QTLs for cane yield, 14 for sugar yield, 11 for fiber percent, and 8 for sucrose content. In addition, QTL by harvest, QTL by location, and QTL by harvest by location interaction effects were significant for all evaluated traits (30 QTLs showed some interaction, and 16 none). Our results contribute to a better understanding of the genetic architecture of complex traits related to biomass production and sucrose content in sugarcane.

Coupled Boltzmann calculation of mixed axion/neutralino cold dark matter production in the early universe

We calculate the relic abundance of mixed axion/neutralino cold dark matter which arises in R-parity conserving supersymmetric (SUSY) models wherein the strong CP problem is solved by the Peccei-Quinn (PQ) mechanism with a concommitant axion/saxion/axino supermultiplet. By numerically solving the coupled Boltzmann equations, we include the combined effects of 1. thermal axino production with cascade decays to a neutralino LSP, 2. thermal saxion production and production via coherent oscillations along with cascade decays and entropy injection, 3. thermal neutralino production and re-annihilation after both axino and saxion decays, 4. gravitino production and decay and 5. axion production both thermally and via oscillations. For SUSY models with too high a standard neutralino thermal abundance, we find the combined effect of SUSY PQ particles is not enough to lower the neutralino abundance down to its measured value, while at the same time respecting bounds on late-decaying neutral particles from BBN. However, models with a standard neutralino underabundance can now be allowed with either neutralino or axion domination of dark matter, and furthermore, these models can allow the PQ breaking scale f(a) to be pushed up into the 10(14) - 10(15) GeV range, which is where it is typically expected to be in string theory models.

Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions

An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.

Cation Distribution and Local Order in Mixed Sodium Metaphosphate Glasses

Two structural properties in mixed alkali metal phosphate glasses that seem to be crucial to the development of the mixed ion effect in dc conductivity were systematically analyzed in Na mixed metaphosphates: the local order around the mobile species, and their distribution and mixing in the glass network. The set of glasses considered here, Na1-xMxPO3 with M = Li, Ag, K, Rb, and Cs and 0 <= x <= 1, encompass a broad degree of size mismatch between the mixed cation species. A comprehensive solid-state nuclear magnetic resonance study was carried out using P-31 MAS, Na-23 triple quantum MAS, Rb-87 QCPMG, P-31-Na-23 REDOR, Na-23-Li-7 and Li-7-Li-6 SEDOR, and Na-23 spin echo decay. It was observed that the arrangement of P atoms around Na in the mixed glasses was indistinguishable from that observed in the NaPO3 glass. However, systematic distortions in the local structure of the 0 environments around Na were observed, related to the presence of the second cation. The average Na-O distances show an expansion/compression When Na+ ions are replaced by cations with respectively smaller/bigger radii. The behavior of the nuclear electric quadrupole coupling. constants indicates that this expansion reduces the local symmetry, while the compression produces the opposite effect These effects become marginally small when the site mismatch between the cations is small, as in Na-Ag mixed glasses. The present study confirms the intimate mixing of cation species at the atomic scale, but clear deviations from random mixing were detected in systems with larger alkali metal ions (Cs-Na, K-Na, Rb-Na). In contrast, no deviations from the statistical ion mixture were found in the systems Ag-Na and Li-Na, where mixed cations are either of radii comparable to (Ag+) or smaller than (Li+) Na+. The set of results supports two fundamental structural features of the models proposed to explain the mixed ion effect: the. structural specificity of the sites occupied by each cation species and their mixing at the atomic scale.

Bartlett corrections in Birnbaum-Saunders nonlinear regression models

Lemonte and Cordeiro [Birnbaum-Saunders nonlinear regression models, Comput. Stat. Data Anal. 53 (2009), pp. 4441-4452] introduced a class of Birnbaum-Saunders (BS) nonlinear regression models potentially useful in lifetime data analysis. We give a general matrix Bartlett correction formula to improve the likelihood ratio (LR) tests in these models. The formula is simple enough to be used analytically to obtain several closed-form expressions in special cases. Our results generalize those in Lemonte et al. [Improved likelihood inference in Birnbaum-Saunders regressions, Comput. Stat. DataAnal. 54 (2010), pp. 1307-1316], which hold only for the BS linear regression models. We consider Monte Carlo simulations to show that the corrected tests work better than the usual LR tests.