Random Effects (random + effects)

Distribution by Scientific Domains
Distribution within Mathematics and Statistics

Terms modified by Random Effects

  • random effects distribution
  • random effects meta-analysi
  • random effects model
  • random effects models

  • Selected Abstracts

    Multilevel Mixture Cure Models with Random Effects

    Xin Lai
    Abstract This paper extends the multilevel survival model by allowing the existence of cured fraction in the model. Random effects induced by the multilevel clustering structure are specified in the linear predictors in both hazard function and cured probability parts. Adopting the generalized linear mixed model (GLMM) approach to formulate the problem, parameter estimation is achieved by maximizing a best linear unbiased prediction (BLUP) type log-likelihood at the initial step of estimation, and is then extended to obtain residual maximum likelihood (REML) estimators of the variance component. The proposed multilevel mixture cure model is applied to analyze the (i) child survival study data with multilevel clustering and (ii) chronic granulomatous disease (CGD) data on recurrent infections as illustrations. A simulation study is carried out to evaluate the performance of the REML estimators and assess the accuracy of the standard error estimates. [source]

    A Version of the EM Algorithm for Proportional Hazard Model with Random Effects

    José Cortiñas Abrahantes
    Abstract Proportional hazard models with multivariate random effects (frailties) acting multiplicatively on the baseline hazard have recently become a topic of an intensive research. One of the main practical problems related to the models is the estimation of parameters. To this aim, several approaches based on the EM algorithm have been proposed. The major difference between these approaches is the method of the computation of conditional expectations required at the E-step. In this paper an alternative implementation of the EM algorithm is proposed, in which the expected values are computed with the use of the Laplace approximation. The method is computationally less demanding than the approaches developed previously. Its performance is assessed based on a simulation study and compared to a non-EM based estimation approach proposed by Ripatti and Palmgren (2000). (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source]

    Semiparametric Transformation Models with Random Effects for Joint Analysis of Recurrent and Terminal Events

    BIOMETRICS, Issue 3 2009
    Donglin Zeng
    Summary We propose a broad class of semiparametric transformation models with random effects for the joint analysis of recurrent events and a terminal event. The transformation models include proportional hazards/intensity and proportional odds models. We estimate the model parameters by the nonparametric maximum likelihood approach. The estimators are shown to be consistent, asymptotically normal, and asymptotically efficient. Simple and stable numerical algorithms are provided to calculate the parameter estimators and to estimate their variances. Extensive simulation studies demonstrate that the proposed inference procedures perform well in realistic settings. Applications to two HIV/AIDS studies are presented. [source]

    Testing Random Effects in the Linear Mixed Model Using Approximate Bayes Factors

    BIOMETRICS, Issue 2 2009
    Benjamin R. Saville
    Summary Deciding which predictor effects may vary across subjects is a difficult issue. Standard model selection criteria and test procedures are often inappropriate for comparing models with different numbers of random effects due to constraints on the parameter space of the variance components. Testing on the boundary of the parameter space changes the asymptotic distribution of some classical test statistics and causes problems in approximating Bayes factors. We propose a simple approach for testing random effects in the linear mixed model using Bayes factors. We scale each random effect to the residual variance and introduce a parameter that controls the relative contribution of each random effect free of the scale of the data. We integrate out the random effects and the variance components using closed-form solutions. The resulting integrals needed to calculate the Bayes factor are low-dimensional integrals lacking variance components and can be efficiently approximated with Laplace's method. We propose a default prior distribution on the parameter controlling the contribution of each random effect and conduct simulations to show that our method has good properties for model selection problems. Finally, we illustrate our methods on data from a clinical trial of patients with bipolar disorder and on data from an environmental study of water disinfection by-products and male reproductive outcomes. [source]

    Standard Errors for EM Estimates in Generalized Linear Models with Random Effects

    BIOMETRICS, Issue 3 2000
    Herwig Friedl
    Summary. A procedure is derived for computing standard errors of EM estimates in generalized linear models with random effects. Quadrature formulas are used to approximate the integrals in the EM algorithm, where two different approaches are pursued, i.e., Gauss-Hermite quadrature in the case of Gaussian random effects and nonparametric maximum likelihood estimation for an unspecified random effect distribution. An approximation of the expected Fisher information matrix is derived from an expansion of the EM estimating equations. This allows for inferential arguments based on EM estimates, as demonstrated by an example and simulations. [source]

    Interpreting Parameters in the Logistic Regression Model with Random Effects

    BIOMETRICS, Issue 3 2000
    Klaus Larsen
    Summary. Logistic regression with random effects is used to study the relationship between explanatory variables and a binary outcome in cases with nonindependent outcomes. In this paper, we examine in detail the interpretation of both fixed effects and random effects parameters. As heterogeneity measures, the random effects parameters included in the model are not easily interpreted. We discuss different alternative measures of heterogeneity and suggest using a median odds ratio measure that is a function of the original random effects parameters. The measure allows a simple interpretation, in terms of well-known odds ratios, that greatly facilitates communication between the data analyst and the subject-matter researcher. Three examples from different subject areas, mainly taken from our own experience, serve to motivate and illustrate different aspects of parameter interpretation in these models. [source]

    Estimates of direct and maternal genetic effects for weights from birth to 600 days of age in Nelore cattle

    Galvão de Albuquerque
    Estimates of direct and maternal variance and heritability for weights at each week (up to 280 days of age) and month of age (up to 600 days of age) in Zebu cattle are presented. More than one million records on 200 000 animals, weighed every 90 days from birth to 2 years of age, were available. Data were split according to week (data sets 1) or month (data sets 2) of age at recording, creating 54 and 21 data sets, respectively. The model of analysis included contemporary groups as fixed effects, and age of dam (linear and quadratic) and age of calf (linear) effects as covariables. Random effects fitted were additive direct and maternal genetic effects, and maternal permanent environmental effect. Direct heritability estimates decreased from 0.28 at birth, to 0.12,0.13 at about 150 days of age, stayed more or less constant at 0.14,0.16 until 270 days of age and increased with age after that, up to 0.25,0.26. Maternal heritability estimates increased from birth (0.01) to a peak of 0.14 for data sets 1 and 0.07,0.08 for data sets 2 at about 180,210 days of age, before decreasing slowly to 0.07 and 0.05, respectively, at 300 days, and then rapidly diminished after 300 days of age. Permanent environmental effects were 1.5 to four times higher than genetic maternal effects and showed a similar trend. Schätzung von direkten und maternal genetischen Effekten für Gewichte von der Geburt bis zum 600. Lebenstag beim Nelore-Rind Es werden Schätzwerte für die direkte und maternale Varianz sowie für Heritabilitäten der Gewichte in jeder Woche (bis zum 280. Lebenstag) und für jeden Monat (bis zum 600. Lebenstag) beim Zebu Rind gezeigt. Mehr als eine Million Datensätze vom 200.000 Tieren standen zur Verfügung, die alle 90 Tage bis zum zweiten Lebensjahr gewogen wurden. Die Daten wurden entsprechend dem Alter in Wochen (Datenset 1) oder Monaten (Datenset 2) aufgeteilt, woraus 54 bzw. 21 Datensets entstanden. Die Modelle beinhalteten Tiergruppen, die zur gleichen Zeit gelebt haben, als fixen Effekt, das Alter der Mutter (linear und quadratisch) und das Alter des Kalbes (linear) als Kovariablen. Als zufällige Effekte wurden der additive direkte, maternal genetische Effekt und maternal permanente Umwelteffekt berücksichtigt. Direkte Heritabilitätsschätzungen nahmen von 0,28 von Geburt auf 0,12,0,13 bei ca. 150 Lebenstagen ab, blieben mehr oder weniger konstant bei 0,14,0,16 bis zum 270. Lebenstag und nahmen ab dem 270. Lebenstag auf 0,25,0,26 zu. Maternale Heritabilitätsschätzungen nahmen von Geburt (0,01) zu einem Peak von 0, 14 beim Datenset 1 und 0,07,0,8 beim Datenset 2 bis ca. 180,210 Lebenstagen zu, bevor sie langsam wieder auf 0,07 bzw. 0,05 bei einem Alter von 300 Tagen sanken. Nach 300 Lebenstagen sanken sie rapide ab. Permanente Umwelteffekte waren 1,5 bis vierfach höher als genetisch maternale Effekte und zeigten einen ähnlichen Trend. [source]

    Semiparametric inference on a class of Wiener processes

    Xiao Wang
    Abstract., This article studies the estimation of a nonhomogeneous Wiener process model for degradation data. A pseudo-likelihood method is proposed to estimate the unknown parameters. An attractive algorithm is established to compute the estimator under this pseudo-likelihood formulation. We establish the asymptotic properties of the estimator, including consistency, convergence rate and asymptotic distribution. Random effects can be incorporated into the model to represent the heterogeneity of degradation paths by letting the mean function be random. The Wiener process model is extended naturally to a normal inverse Gaussian process model and similar pseudo-likelihood inference is developed. A score test is used to test the presence of the random effects. Simulation studies are conducted to validate the method and we apply our method to a real data set in the area of health structure monitoring. [source]

    Variability in measurements of micro lengths with a white light interferometer

    Carlo Ferri
    Abstract The effect of the discretionary set-up parameters scan length and initial scanner position on the measurements of length performed with a white light interferometer microscope was investigated. In both analyses, two reference materials of nominal lengths 40 and 200,µm were considered. Random effects and mixed effects models were fitted to the data from two separate experiments. Punctual and interval estimates of variance components were provided. Copyright © 2008 John Wiley & Sons, Ltd. [source]

    Multilevel Mixture Cure Models with Random Effects

    Xin Lai
    Abstract This paper extends the multilevel survival model by allowing the existence of cured fraction in the model. Random effects induced by the multilevel clustering structure are specified in the linear predictors in both hazard function and cured probability parts. Adopting the generalized linear mixed model (GLMM) approach to formulate the problem, parameter estimation is achieved by maximizing a best linear unbiased prediction (BLUP) type log-likelihood at the initial step of estimation, and is then extended to obtain residual maximum likelihood (REML) estimators of the variance component. The proposed multilevel mixture cure model is applied to analyze the (i) child survival study data with multilevel clustering and (ii) chronic granulomatous disease (CGD) data on recurrent infections as illustrations. A simulation study is carried out to evaluate the performance of the REML estimators and assess the accuracy of the standard error estimates. [source]

    Cross-state variation in Medicaid programs and female labor supply

    ECONOMIC INQUIRY, Issue 3 2000
    E Montgomery
    Using a pooled cross-section data set from the 1980 through 1993 Current Population Survey March Supplements, we test if different Medicaid benefit levels across states impact the labor supply behavior of female heads of households. The ordinary least square (OLS) results support the prediction that Medicaid expenditures reduce labor supply. Controlling for state fixed or random effects alters the effect of both AFDC and Medicaid on the decision to participate as well as the number of hours worked. We also find that while the effects of program generosity are sensitive to the inclusion of state effects those of variation in eligibility thresholds are not. [source]

    Modeling mood variation associated with smoking: an application of a heterogeneous mixed-effects model for analysis of ecological momentary assessment (EMA) data

    ADDICTION, Issue 2 2009
    Donald Hedeker
    ABSTRACT Aims Mixed models are used increasingly for analysis of ecological momentary assessment (EMA) data. The variance parameters of the random effects, which indicate the degree of heterogeneity in the population of subjects, are considered usually to be homogeneous across subjects. Modeling these variances can shed light on interesting hypotheses in substance abuse research. Design We describe how these variances can be modeled in terms of covariates to examine the covariate effects on between-subjects variation, focusing on positive and negative mood and the degree to which these moods change as a function of smoking. Setting The data are drawn from an EMA study of adolescent smoking. Participants Participants were 234 adolescents, either in 9th or 10th grades, who provided EMA mood reports from both random prompts and following smoking events. Measurements We focused on two mood outcomes: measures of the subject's negative and positive affect and several covariates: gender, grade, negative mood regulation and smoking level. Findings and conclusions Following smoking, adolescents experienced higher positive affect and lower negative affect than they did at random, non-smoking times. Our analyses also indicated an increased consistency of subjective mood responses as smoking experience increased and a diminishing of mood change. [source]

    Evaluation of reduced rank semiparametric models to assess excess of risk in cluster analysis

    ENVIRONMETRICS, Issue 4 2009
    Marco Geraci
    Abstract The existence of multiple environmental hazards is obviously a threat to human health and, from a statistical point of view, the modeling and the detection of disease clusters potentially related to those hazards offer challenging tasks. In this paper, we consider low rank thin plate spline (TPS) models within a semiparametric approach to focused clustering for small area health data. Both the distance from a putative source and a general, unspecified clustering process are modeled in the same fashion and they are entered log-additively in mixed Poisson-Normal models. Some issues related to the identification of the random effects arising from this approach are investigated. Under different simulated scenarios, we evaluate the proposed models using conditional Akaike's weights and tests for variance components, providing a comprehensive model selection methodology easy to implement. We examine observations of lung cancer deaths taken in Ohio between 1987 and 1988. These data were analyzed on several occasions to investigate the risk associated with a putative source in Hamilton county. In our analysis, we found a strong south-eastward spatial trend which is confounded with a significant radial distance effect decreasing between 0 and 150 km from the point source. Copyright © 2008 John Wiley & Sons, Ltd. [source]

    Space,time zero-inflated count models of Harbor seals,

    ENVIRONMETRICS, Issue 7 2007
    Jay M. Ver Hoef
    Abstract Environmental data are spatial, temporal, and often come with many zeros. In this paper, we included space-time random effects in zero-inflated Poisson (ZIP) and ,hurdle' models to investigate haulout patterns of harbor seals on glacial ice. The data consisted of counts, for 18 dates on a lattice grid of samples, of harbor seals hauled out on glacial ice in Disenchantment Bay, near Yakutat, Alaska. A hurdle model is similar to a ZIP model except it does not mix zeros from the binary and count processes. Both models can be used for zero-inflated data, and we compared space-time ZIP and hurdle models in a Bayesian hierarchical model. Space-time ZIP and hurdle models were constructed by using spatial conditional autoregressive (CAR) models and temporal first-order autoregressive (AR(1)) models as random effects in ZIP and hurdle regression models. We created maps of smoothed predictions for harbor seal counts based on ice density, other covariates, and spatio-temporal random effects. For both models predictions around the edges appeared to be positively biased. The linex loss function is an asymmetric loss function that penalizes overprediction more than underprediction, and we used it to correct for prediction bias to get the best map for space-time ZIP and hurdle models. Published in 2007 by John Wiley & Sons, Ltd. [source]

    Bayesian hierarchical models in ecological studies of health,environment effects

    ENVIRONMETRICS, Issue 2 2003
    Sylvia Richardson
    Abstract We describe Bayesian hierarchical models and illustrate their use in epidemiological studies of the effects of environment on health. The framework of Bayesian hierarchical models refers to a generic model building strategy in which unobserved quantities (e.g. statistical parameters, missing or mismeasured data, random effects, etc.) are organized into a small number of discrete levels with logically distinct and scientifically interpretable functions, and probabilistic relationships between them that capture inherent features of the data. It has proved to be successful for analysing many types of complex epidemiological and biomedical data. The general applicability of Bayesian hierarchical models has been enhanced by advances in computational algorithms, notably those belonging to the family of stochastic algorithms based on Markov chain Monte Carlo techniques. In this article, we review different types of design commonly used in studies of environment and health, give details on how to incorporate the hierarchical structure into the different components of the model (baseline risk, exposure) and discuss the model specification at the different levels of the hierarchy with particular attention to the problem of aggregation (ecological) bias. Copyright © 2003 John Wiley & Sons, Ltd. [source]

    An echocardiographic and auscultation study of right heart responses to training in young National Hunt Thoroughbred horses

    Summary Reasons for performing study: There are few data available to determine the effect of training on cardiac valve function. Objectives: To investigate the effect of commercial race training on right ventricular (RV) and tricuspid valve function in an untrained group of National Hunt Thoroughbreds (TB). Material and methods: Cardiac auscultation, guided M-mode echocardiography of the RV, and colour flow Doppler (CFD) tricuspid valve and right atrium were performed in 90 TB horses (age 2,7 years) 1998,2003. Forty horses were examined at least once and 48 horses were examined on at least 2 occasions. Examinations were then classified as: i) before commencement of race training, ii) after cantering exercise had been sustained for a period of 8,12 weeks and iii) at full race fitness. Tricuspid valve regurgitation (TR) murmurs were graded on a 1,6 scale and CFD echocardiography TR signals were graded on a 1,9 scale. Right ventricular internal diameter (RVID) in diastole and systole (RVIDd and RVIDs) was measured by guided M-mode. Associations between continuous RVID and TR measures and explanatory covariates of weight, age, heart rate, yard and stage of training were examined using general linear mixed models with horse-level random effects. Results: On average, RVIDd and RVIDs increased by 0.08 and 0.1 cm, respectively, per year increase in age (P=0.1 and 0.02) and by 0.3 and 0.4 cm, respectively between pre-training and race fitness (P = 0.07 and 0.005). Tricuspid regurgitation score by colour flow Doppler increased by 0.6/year with age (P<0.0001) and by 1.8 between pre-training and race fitness (P< 0.0001). No significant associations were found between any outcomes and weight, heart rate and training yard. Due to the high level of co-linearity between age and training, multivariable models including both terms were not interpretable. Conclusions and clinical relevance: Athletic training of horses exerts independent effects on both severity and prevalence of tricuspid valve incompetence. This effect should therefore be taken into account when examinations are performed. Dimensions of RV increase with age and training in TB horses in a manner that appears to be similar to that of the LV. [source]

    How Did the Elimination of the US Earnings Test above the Normal Retirement Age Affect Labour Supply Expectations?,

    FISCAL STUDIES, Issue 2 2008
    Pierre-Carl Michaud
    H55; J22 Abstract We look at the effect of the 2000 repeal of the earnings test above the normal retirement age (NRA) on the self-reported probabilities of working full-time after ages 65 and 62 of male workers in the US Health and Retirement Study (HRS). Using administrative records on social security benefit entitlements linked to the HRS survey data, we can distinguish groups of respondents according to the predicted effect of the earnings test before its repeal on their marginal wage rate after the NRA. We use panel data models with fixed and random effects to investigate the effect of the repeal. We find that male workers whose predicted marginal wage rate increased because the earnings test was repealed had the largest increase in the subjective probability of working full-time after age 65. We find no significant effects of the repeal on the subjective probability of working full-time past age 62. [source]

    Summer drought: a driver for crown condition and mortality of Norway spruce in Norway

    FOREST PATHOLOGY, Issue 2 2004
    S. Solberg
    Summary Summer drought, i.e. unusually dry and warm weather, has been a significant stress factor for Norway spruce in southeast Norway during the 14 years of forest monitoring. Dry and warm summers were followed by increases in defoliation, discolouration of foliage, cone formation and mortality. The causal mechanisms are discussed. Most likely, the defoliation resulted from increased needle-fall in the autumn after dry summers. During the monitoring period 1988,2001, southeast Norway was repeatedly affected by summer drought, in particular, in the early 1990s. The dataset comprised 455 ,Forest officers' plots' with annual data on crown condition and mortality. Linear mixed models were used for estimation and hypothesis testing, including a variance,covariance structure for the handling of random effects and temporal autocorrelation. Résumé La sécheresse estivale, c'est à dire un temps exceptionnellement sec et chaud, a été un facteur significatif de stress pour l'Epicéa commun dans le sud-est de la Norvège au cours de 14 années de surveillance. Les étés secs et chauds ont été suivis d'une augmentation de la défoliation, des colorations anormales du feuillage, de la formation de cônes et de la mortalité. Les mécanismes causaux sont discutés. La défoliation peut probablement s'expliquer par une chute automnale des aiguilles après les étés secs. Pendant la période de suivi de 1988 à 2001, le sud-est de la Norvège a été affecté de façon répétée par des sécheresses estivales, en particulier au début des années 1990. La base de données comprend 455 ,parcelles d'agents forestiers' avec des données annuelles sur l'état des houppiers et la mortalité. Des modèles linéaires mixtes ont été utilisés pour tester les hypothèses et faire les estimations, en incluant une structure de variance-covariance pour prendre en compte les effets aléatoires et les auto-corrélations temporelles. Zusammenfassung Sommertrockenheit, d.h. ungewöhnlich trockenes und warmes Wetter, war ein wesentlicher Stressfaktor für die Fichte (Picea abies) in Südwestnorwegen während der 14 Jahre, in denen der Waldzustand bisher erfasst wurde. Nach trockenen und warmen Sommern nahmen der Nadelverlust, die Nadelverfärbung, die Zapfenbildung und die Mortalität zu. Die ursächlichen Mechanismen hierfür werden diskutiert. Am wahrscheinlichsten ist der Blattverlust das Ergebnis eines erhöhten Nadelfalles im Herbst nach einem trockenen Sommer. Während der Beobachtungsperiode von 1988 bis 2001 traten in Südwestnorwegen wiederholt trockene Sommer auf, insbesondere zu Beginn der 90er Jahre. Das Datenset umfasste 455 Stichprobeflächen mit jährlichen Angaben zum Kronenzustand und zur Mortalität. Für die statistische Analyse wurden lineare Modelle mit gemischten Effekten verwendet, einschliesslich einer Varianz-Kovarianzstruktur für die zeitreihenbedingten Autokorrelationen. [source]

    Testing association in the presence of linkage , a powerful score for binary traits

    Gudrun Jonasdottir
    Abstract We present a score for testing association in the presence of linkage for binary traits. The score is robust to varying degrees of linkage, and it is valid under any ascertainment scheme based on trait values as well as under population stratification. The score test is derived from a mixed effects model where population level association is modeled using a fixed effect and where correlation among related individuals is allowed for by using log-gamma random effects. The score, as presented in this paper, does not assume full information about the inheritance pattern in families or parental genotypes. We compare the score to the semi-parametric family-based association test (FBAT), which has won ground because of its flexible and simple form. We show that a random effects formulation of co-inheritance can improve the power substantially. We apply the method to data from the Collaborative Study on the Genetics of Alcoholism. We compare our findings to previously published results. Genet. Epidemiol. 2007. © 2007 Wiley-Liss, Inc. [source]

    Robustness of inference on measured covariates to misspecification of genetic random effects in family studies

    Ruth M.Pfeiffer
    Abstract Family studies to identify disease-related genes frequently collect only families with multiple cases. It is often desirable to determine if risk factors that are known to influence disease risk in the general population also play a role in the study families. If so, these factors should be incorporated into the genetic analysis to control for confounding. Pfeiffer et al. [2001 Biometrika 88: 933,948] proposed a variance components or random effects model to account for common familial effects and for different genetic correlations among family members. After adjusting for ascertainment, they found maximum likelihood estimates of the measured exposure effects. Although it is appealing that this model accounts for genetic correlations as well as for the ascertainment of families, in order to perform an analysis one needs to specify the distribution of random genetic effects. The current work investigates the robustness of the proposed model with respect to various misspecifications of genetic random effects in simulations. When the true underlying genetic mechanism is polygenic with a small dominant component, or Mendelian with low allele frequency and penetrance, the effects of misspecification on the estimation of fixed effects in the model are negligible. The model is applied to data from a family study on nasopharyngeal carcinoma in Taiwan. Genet Epidemiol 24:14,23, 2003. © 2003 Wiley-Liss, Inc. [source]

    Analyzing the Relationship Between Smoking and Coronary Heart Disease at the Small Area Level: A Bayesian Approach to Spatial Modeling

    Jane Law
    We model the relationship between coronary heart disease and smoking prevalence and deprivation at the small area level using the Poisson log-linear model with and without random effects. Extra-Poisson variability (overdispersion) is handled through the addition of spatially structured and unstructured random effects in a Bayesian framework. In addition, four different measures of smoking prevalence are assessed because the smoking data are obtained from a survey that resulted in quite large differences in the size of the sample across the census tracts. Two of the methods use Bayes adjustments of standardized smoking ratios (local and global adjustments), and one uses a nonparametric spatial averaging technique. A preferred model is identified based on the deviance information criterion. Both smoking and deprivation are found to be statistically significant risk factors, but the effect of the smoking variable is reduced once the confounding effects of deprivation are taken into account. Maps of the spatial variability in relative risk, and the importance of the underlying covariates and random effects terms, are produced. We also identify areas with excess relative risk. [source]

    Use of tree rings to study the effect of climate change on trembling aspen in Québec

    Abstract In this paper, we present a new approach, based on a mixed model procedure, to quantify the tree-ring-based growth-climate relationship of trembling aspen along a latitudinal gradient from 46 to 54 °N in eastern Canada. This approach allows breaking down the growth response into general intersite and local climatic responses, and analyzing variations of absolute ring width as well as interannual variations in tree growth. The final model also integrates nonclimatic variables such as soil characteristics and the occurrence of insect outbreaks into the growth predictions. Tree level random effects on growth were important as intercepts but were nonsignificant for the climatic variables, indicating that a single climate,growth relationship was justified in our case. The response of tree growth to climate showed, however, a strong dependence on the spatial scale at which the analysis was performed. Intersite variations in tree growth were mostly dependent on variations in the thermal heat sum, a variable that showed low interannual and high intersite variation. When variation for a single site was analyzed, other variables showed up to be important while the heat sum was unimportant. Finally, future growth under six different climate change scenarios was simulated in order to study the potential impact of climate change. Results suggest only moderate growth increases in the northern portion of the gradient and a growth decrease in the southern portion under future climatic conditions. [source]

    Country specific cost comparisons from multinational clinical trials using empirical Bayesian shrinkage estimation: the Canadian ASSENT-3 economic analysis

    HEALTH ECONOMICS, Issue 4 2005
    Andrew R. Willan
    Abstract The growing number of multinational clinical trials in which patient-level health care resource data are collected have raised the issue of which is the best approach for making inference for individual countries with respect to the between-treatment difference in mean cost. We describe and discuss the relative merits of three approaches. The first uses the random effects pooled estimate from all countries to estimate the difference for any particular country. The second approach estimates the difference using only the data from the specific country in question. Using empirical Bayes estimation a third approach estimates the country-specific difference using a variance-weighted linear sum of the estimates provided by the other two approaches. The approaches are illustrated and compared using the data from the ASSENT-3 trial. Copyright © 2005 John Wiley & Sons, Ltd. [source]

    Measuring horizontal inequity in Belgian health care using a Gaussian random effects two part count data model

    HEALTH ECONOMICS, Issue 7 2004
    Tom Van Ourti
    Abstract We estimate the determinants of utilisation of physician and hospital services in Belgium using a one- and two-part panel count data model, and a one- and two-part pooled count data model. We conclude that the two-part panel count data model is most appropriate as it controls for unobserved heterogeneity and allows for a two-part decision-making process. The estimates of the determinants of utilisation of health care are then used to calculate indices of horizontal inequity. We find that inequity for general practitioner and hospital services is stable across time and in favour of low-income individuals, in the sense that, overall, they consume more than one would expect on the basis of their need, albeit the indices for hospital care are not significant. Horizontal equity applies to specialist care in all years, but from 1999 onwards, some evidence (although not statistically significant) of pro-rich inequity is found. Copyright © 2004 John Wiley & Sons, Ltd. [source]

    Real-time atomic force microscopy of root dentine during demineralization when subjected to chelating agents

    G. De-Deus
    Abstract Aim, To explore the potential of atomic force microscopy (AFM) for the examination of changes to dentine surfaces during demineralization and evaluate qualitatively the effect of EDTA, EDTAC and citric acid. Methodology, Nine canine teeth were sectioned transversely at the cemento-enamel junction, and the crowns discarded. Subsequently, each root was embedded in an epoxy cylinder and discs approximately 5 mm thick were cut. A standard metallographic procedure was then used to prepare the surfaces for observation. From the central portion of these samples, two specimens were symmetrically prepared per tooth so that a total number of 18 samples was produced. To allow the use of a liquid cell during AFM, the samples were embedded in silicone rubber and were then randomly divided into three groups, as follows: group 1: 17% EDTA (pH 7.7), group 2: 17% EDTAC (pH 7.7) and group 3: 10% citric acid (pH 1.4). Topographical images were acquired during the demineralization process, allowing real-time observation of the dentine surface. Two operators assigned scores to the AFM images using a double-blind method. anova analysis with random effects (P < 0.05) was used to compare the results. Results, The average scores were 6.13 ± 0.35 for EDTAC, 7.36 ± 0.23 for EDTA and 14.55 ± 1.21 for citric acid. Citric acid was statistically different from EDTA and EDTAC while EDTA and EDTAC were not statistically different. Conclusions, The most effective demineralizing substance was citric acid. The methodology developed for real-time observation of dentine surfaces is a valuable method to evaluate demineralization. [source]

    Multilevel investigation of variation in HoNOS ratings by mental health professionals: a naturalistic study of consecutive referrals

    R. Ecob
    Episodes of mental healthcare in specialist psychiatric services often begin with the assessment of clinical and psychosocial needs of patients by healthcare professionals. Particularly for patients with complex needs or severe problems, ratings of clinical and social functioning at the start of each episode of care may serve as a baseline against which subsequent measures can be compared. Currently, little is known about service variations in such assessments on referrals from primary care. We set out to quantify variability in initial assessments performed by healthcare professionals in three CMHTs in Bristol (UK) using the Health of the Nation Outcome Scales (HoNOS). We tested the hypothesis that variations in HoNOS total and sub-scale scores are related to referral source (general practices), healthcare assessor (in CMHTs) and the assessor's professional group. Statistical analysis was performed using multilevel variance components models with cross-classified random effects. We found that variation due to assessor substantially exceeded that due to referral source (general practices). Furthermore, patient variance differed by assessor profession for the HoNOS , Impairment scores. Assessor variance differed by assessor profession for the HoNOS , Social scores. As HoNOS total and subscale scores show much larger variation by assessor than by referral source, investigations of HoNOS scores must take assessors into account. Services should implement and evaluate interdisciplinary training to improve consistency in use of rating thresholds; such initiatives could be evaluated using these extensions of multilevel models. Future research should aim to integrate routine diagnostic data with continuous outcomes to address selection effects (of patients to assessors) better. Copyright © 2004 Whurr Publishers Ltd. [source]

    Do perineal exercises during pregnancy prevent the development of urinary incontinence?

    A systematic review
    Objectives: The aim of the current article was to conduct a systematic review of the performance of perineal exercises during pregnancy and their utility in the prevention of urinary incontinence. Methods: Randomized controlled studies (RCT) of a low-risk obstetric population (primiparas or nulliparas) who had done perineal exercises only during pregnancy met the inclusion criteria. Articles published between 1966 and 2007 from periodicals indexed in the LILACS, SCIELO, PubMed/MEDLINE, SCIRUS and Cochrane Library databases were selected, using the following keywords: ,urinary incontinence', ,pregnancy', ,pelvic floor' and ,exercise'. The Jadad scale was applied to assess the internal validity of the RCT and two meta-analysis: one of fixed effects and the other of random effects were carried out with data extracted from the RCT, using the Stata 9.2 statistical software and adopting a significance level of 0.05. Results: Four RCTs with high methodological quality, involving a total of 675 women were included. They indicated that perineal muscle exercise significantly reduced the development of urinary incontinence from 6 weeks to 3 months after delivery (odds ratio = 0.45; confidence interval: 0.3 to 0.66). However, when evaluating this effect during the 34th and 35th gestational week, a meta-analysis showed that the results were not significant (odds ratio = 0.13; confidence interval: 0.00 to 3.77). Conclusion: Pelvic floor muscle exercises may be effective at reducing the development of postpartum urinary incontinence, despite clinical heterogeneity among the RCT. [source]

    Estimates of genetic parameters for conformation measures and scores in Finnhorse and Standardbred foals

    E. Schroderus
    Summary The aim of this study was to estimate genetic parameters for conformation measures and scores in the Finnhorse and the Standardbred foals presented in foal shows. Studied traits included height at withers and at croup, six subjectively evaluated conformation traits and overall grade. Data were from 10-year period (1995,2004) and consisted of 5821 Finnhorse foals (1,3 years old) with 7644 records and 2570 Standardbred foals (1,2 years old) with 2864 records. Variance components were estimated with REML , animal model using VCE4 program. The model included age class, year of judging, sex and region as fixed effects, and additive genetic, permanent environmental and residual as random effects. Estimates of heritability for measured traits were very high in both breeds (0.88,0.90). Estimates of heritability for conformation traits varied from 0.13 to 0.32 in the Finnhorse and from 0.06 to 0.47 in the Standardbred. In both breeds, estimates of heritability were lowest for hooves and movements at walk, and highest for type and body conformation among scored traits. Estimate of heritability for overall grade was in the Finnhorse 0.32 and in the Standardbred 0.34. Genetic correlations between overall grade and different conformation traits were 0.35,0.84 in the Finnhorse and 0.31,0.88 in the Standardbred. Thus, selection based on the overall grade would improve all studied characteristics. [source]

    Effects of breed, sex and halothane genotype on fatty acid composition of triacylglycerols and phospholipids in pork longissimus muscle

    S. Zhang
    Summary The objective of this study was to estimate the effects of breed, sex, and halothane (HAL-1843TM) genotype on fatty acid composition of triacylglycerols (TAG) and phospholipids (PL) extracted from porcine longissimus muscle (LM). Purebred Yorkshire (n = 131), Duroc (n = 136), Hampshire (n = 49), Spotted (n = 35), Chester White (n = 74), Poland China (n = 51), Berkshire (n = 169) and Landrace (n = 82) pigs (n = 727; 427 barrows and 300 gilts) from the 1994 and 2001 National Barrow Show Sire Progeny Tests were used. For statistical analyses, a mixed model was used that included fixed effects of breed, sex, HAL-1843TM genotype, year, slaughter date within each year, interaction of breed × sex and random effects of sire and dam within breed. Breeds and sex were significantly associated with the percentages of the majority fatty acids in TAG. Duroc pigs had greater total saturated fatty acids (SFA) and lower total monounsaturated fatty acids (MUFA) (p < 0.05) contents than did pigs of all other breeds except Berkshire (p > 0.05). The concentration of total polyunsaturated fatty acids (PUFA) was the greatest in Hampshire pigs (p < 0.05). The content of total SFA was greater (p < 0.01), whereas the concentrations of total MUFA and PUFA were lower (p < 0.01) in barrows than those in gilts. The contents of major SFA in PL did not differ significantly among pigs from different breeds and sex groups. However, breed and sex significantly affected the concentrations of major MUFA and PUFA in PL and strong negative correlation between the total contents of MUFA and PUFA in PL was observed in the current study. Chester White pigs had greater total MUFA and lower total PUFA contents (p < 0.05) in PL than did pigs of all other breeds except Spotted (p > 0.05). In contrast to breed and sex effects, the concentrations of fatty acids in PL were more affected by HAL-1843TM genotype than those in TAG. The content of C16:0, a major SFA in PL, differed significantly in pigs with different HAL-1843TM genotypes. In conclusion, these results suggest that breed and sex are important sources of the variations for fatty acid composition of TAG and PL in LM. [source]

    Identifiability of parameters and behaviour of MCMC chains: a case study using the reaction norm model

    M.M. Shariati
    Summary Markov chain Monte Carlo (MCMC) enables fitting complex hierarchical models that may adequately reflect the process of data generation. Some of these models may contain more parameters than can be uniquely inferred from the distribution of the data, causing non-identifiability. The reaction norm model with unknown covariates (RNUC) is a model in which unknown environmental effects can be inferred jointly with the remaining parameters. The problem of identifiability of parameters at the level of the likelihood and the associated behaviour of MCMC chains were discussed using the RNUC as an example. It was shown theoretically that when environmental effects (covariates) are considered as random effects, estimable functions of the fixed effects, (co)variance components and genetic effects are identifiable as well as the environmental effects. When the environmental effects are treated as fixed and there are other fixed factors in the model, the contrasts involving environmental effects, the variance of environmental sensitivities (genetic slopes) and the residual variance are the only identifiable parameters. These different identifiability scenarios were generated by changing the formulation of the model and the structure of the data and the models were then implemented via MCMC. The output of MCMC sampling schemes was interpreted in the light of the theoretical findings. The erratic behaviour of the MCMC chains was shown to be associated with identifiability problems in the likelihood, despite propriety of posterior distributions, achieved by arbitrarily chosen uniform (bounded) priors. In some cases, very long chains were needed before the pattern of behaviour of the chain may signal the existence of problems. The paper serves as a warning concerning the implementation of complex models where identifiability problems can be difficult to detect a priori. We conclude that it would be good practice to experiment with a proposed model and to understand its features before embarking on a full MCMC implementation. [source]