Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

International openness in transition countries: further evidence on foreign direct investment

The thesis focuses on the process of international openness of Transition Countries. This study provides a theoretical analysis based on reference literature, and an empirical analysis which is aimed at estimating some main effects of Foreign Direct Investment. Transition has represented a highly complex phenomenon, characterized by several aspects, whose interaction has shaped the developmental path of each country involved. Although the thesis focuses on economic issues it is outstanding to underline that Transition implies political, institutional, and even social deep changes, which must be taken into consideration in the general overview of the contex. The empirical part has been developed along two different ways: a country analysis and a firm analysis, thus allowing to widen the study and delve deeper into the use of econometric instruments. More specifically, in the first empirical stage both static (Fixed Effects) and dynamic (LSDV Corrected) methodologies have been implemented, whereas in the second stage the Cox Proportional Function has been chosen in order to handle with censored data.

An interdisciplinary analysis of obesity: theory and empirical evidence

The dissertation is structured in three parts. The first part compares US and EU agricultural policies since the end of WWII. There is not enough evidence for claiming that agricultural support has a negative impact on obesity trends. I discuss the possibility of an exchange in best practices to fight obesity. There are relevant economic, societal and legal differences between the US and the EU. However, partnerships against obesity are welcomed. The second part presents a socio-ecological model of the determinants of obesity. I employ an interdisciplinary model because it captures the simultaneous influence of several variables. Obesity is an interaction of pre-birth, primary and secondary socialization factors. To test the significance of each factor, I use data from the National Longitudinal Survey of Adolescent Health. I compare the average body mass index across different populations. Differences in means are statistically significant. In the last part I use the National Survey of Children Health. I analyze the effect that family characteristics, built environment, cultural norms and individual factors have on the body mass index (BMI). I use Ordered Probit models and I calculate the marginal effects. I use State and ethnicity fixed effects to control for unobserved heterogeneity. I find that southern US States tend have on average a higher probability of being obese. On the ethnicity side, White Americans have a lower BMI respect to Black Americans, Hispanics and American Indians Native Islanders; being Asian is associated with a lower probability of being obese. In neighborhoods where trust level and safety perception are higher, children are less overweight and obese. Similar results are shown for higher level of parental income and education. Breastfeeding has a negative impact. Higher values of measures of behavioral disorders have a positive and significant impact on obesity, as predicted by the theory.

Modelli Gravitazionali per l'analisi del Commercio Internazionale

Il modello gravitazionale e' ormai diventato un "cavallo da battaglia" in economia internazionle ed e' comunemente utilizzato nella determinazione dei flussi commerciali. Recentemente, molti studi hanno mostrato l'importanza della dipendenza spaziale, che va' a considerare quegli effetti dovuti al cosiddetto "third country". Intervengono a questo scopo la modellistica e le tecniche di stima di Econometria Spaziale. Verra' fatto uso di tali tecniche allo scopo di stimare con un modello gravitazionale spaziale il commercio internazionale tra paesi dell'OCSE per un panel di 22 anni. L'obiettivo e' quindi duplice: da un lato, si andra' ad applicare le piu' moderne tecniche di Econometria Spaziale, in un campo in cui tali contributi scarseggiano. Dall'altro lato,verra' fornita una interpretazione del comportamento del commercio internazionale tra paesi dell'OCSE, approfondendo gli aspetti relativi all'effetto del"third country" e del fenomeno migratorio. Inoltre , viene proposta un'analisi che ha lo scopo di validare l'ipotesi di omissione della distanza dal modello gravitazione strutturale.

Modeling the spatial dynamics of economic models

The advances that have been characterizing spatial econometrics in recent years are mostly theoretical and have not found an extensive empirical application yet. In this work we aim at supplying a review of the main tools of spatial econometrics and to show an empirical application for one of the most recently introduced estimators. Despite the numerous alternatives that the econometric theory provides for the treatment of spatial (and spatiotemporal) data, empirical analyses are still limited by the lack of availability of the correspondent routines in statistical and econometric software. Spatiotemporal modeling represents one of the most recent developments in spatial econometric theory and the finite sample properties of the estimators that have been proposed are currently being tested in the literature. We provide a comparison between some estimators (a quasi-maximum likelihood, QML, estimator and some GMM-type estimators) for a fixed effects dynamic panel data model under certain conditions, by means of a Monte Carlo simulation analysis. We focus on different settings, which are characterized either by fully stable or quasi-unit root series. We also investigate the extent of the bias that is caused by a non-spatial estimation of a model when the data are characterized by different degrees of spatial dependence. Finally, we provide an empirical application of a QML estimator for a time-space dynamic model which includes a temporal, a spatial and a spatiotemporal lag of the dependent variable. This is done by choosing a relevant and prolific field of analysis, in which spatial econometrics has only found limited space so far, in order to explore the value-added of considering the spatial dimension of the data. In particular, we study the determinants of cropland value in Midwestern U.S.A. in the years 1971-2009, by taking the present value model (PVM) as the theoretical framework of analysis.

Efficacy of experimental treatments compared with standard treatments in non-inferiority trials: a meta-analysis of randomized controlled trials

Background There is concern that non-inferiority trials might be deliberately designed to conceal that a new treatment is less effective than a standard treatment. In order to test this hypothesis we performed a meta-analysis of non-inferiority trials to assess the average effect of experimental treatments compared with standard treatments. Methods One hundred and seventy non-inferiority treatment trials published in 121 core clinical journals were included. The trials were identified through a search of PubMed (1991 to 20 February 2009). Combined relative risk (RR) from meta-analysis comparing experimental with standard treatments was the main outcome measure. Results The 170 trials contributed a total of 175 independent comparisons of experimental with standard treatments. The combined RR for all 175 comparisons was 0.994 [95% confidence interval (CI) 0.978–1.010] using a random-effects model and 1.002 (95% CI 0.996–1.008) using a fixed-effects model. Of the 175 comparisons, experimental treatment was considered to be non-inferior in 130 (74%). The combined RR for these 130 comparisons was 0.995 (95% CI 0.983–1.006) and the point estimate favoured the experimental treatment in 58% (n = 76) and standard treatment in 42% (n = 54). The median non-inferiority margin (RR) pre-specified by trialists was 1.31 [inter-quartile range (IQR) 1.18–1.59]. Conclusion In this meta-analysis of non-inferiority trials the average RR comparing experimental with standard treatments was close to 1. The experimental treatments that gain a verdict of non-inferiority in published trials do not appear to be systematically less effective than the standard treatments. Importantly, publication bias and bias in the design and reporting of the studies cannot be ruled out and may have skewed the study results in favour of the experimental treatments. Further studies are required to examine the importance of such bias.

Does land-based exercise reduce pain and disability associated with hip osteoarthritis? A meta-analysis of randomized controlled trials

Objective To determine if clinical guidelines recommending therapeutic exercise for people with hip osteoarthritis (OA) are supported by rigorous scientific evidence. Methods A meta-analysis of randomized controlled trials (RCTs) recruiting people with hip OA and comparing some form of land-based exercise program (as opposed to exercises conducted in the water) with a non-exercise group in terms of hip pain and/or self-reported physical function. Results Thirty-two RCTs were identified, but only five met the inclusion criteria. Only one of the five included RCTs restricted recruitment to people with hip OA, the other four RCTs also recruiting participants with knee OA. The five included studies provided data on 204 and 187 hip OA participants for pain and physical function, respectively. Combining the results of the five included RCTs using a fixed-effects model demonstrated a small treatment effect for pain (standardized mean difference (SMD) −0.38; 95% confidence interval (CI) −0.67 to −0.09). No significant benefit in terms of improved self-reported physical function was detected (SMD −0.02; 95% CI −0.31 to 0.28). Conclusion Currently there is only silver level evidence (one small RCT) supporting the benefit of land-based therapeutic exercise for people with symptomatic hip OA in terms of reduced pain and improved physical function. The limited number and small sample size of the included RCTs restricts the confidence that can be attributed to these results.

The Incumbent Spending Puzzle

Objective This article seeks to explain the puzzle of why incumbents spend so much on campaigns despite most research finding that their spending has almost no effect on voters. Methods The article uses ordinary least squares, instrumental variables, and fixed-effects regression to estimate the impact of incumbent spending on election outcomes. The estimation includes an interaction term between incumbent and challenger spending to allow the effect of incumbent spending to depend on the level of challenger spending. Results The estimation provides strong evidence that spending by the incumbent has a larger positive impact on votes received the more money the challenger spends. Conclusion Campaign spending by incumbents is most valuable in the races where the incumbent faces a serious challenge. Raising large sums of money to be used in close races is thus a rational choice by incumbents.

Mobile goes global: The effect of cell phones on economic growth and development

This study investigates the effect of cell phones on economic development and growth by performing an econometric analysis using data from the International Telecommunications Union and the Penn World Table. It discusses the various ways cell phones can make markets more efficient and how the diffusion of information andknowledge plays into development. Several approaches (OLS, Fixed Effects, 2SLS) were used to test over 20 econometric models. Overall, the mobile cellular subscriptions rate was found to have a positive and significant impact on countries’ level of real per capitaGDP and GDP growth rate. Furthermore, the study provides policy implications for the use of technology to promote global growth.

The Returns to Migration: The Influence of Education and Migration Type

We show the impact of migration type on real wages over time. We create a migration and earnings history from the National Longitudinal Survey of Youth over the period 1979-2002. We estimate the effects of primary, onward, and two types of return migration on real wages using a panel data model with individual, location, and time fixed effects. Panel data are well suited for the study of the returns to U.S. internal migration because the influence of migration on wages has been found to occur years after the event. We differentiate return migration into two types: return to a location with ties that form a geographical anchor (home) and return to a prior place of work. We find that real wage growth varies by migration type. Education attainment is a significant factor in real wage growth. Our results show that onward migration is an important channel by which the monetary rewards to a college education are manifested.

Are mutans streptococci detected in preschool children a reliable predictive factor for dental caries risk? A systematic review

Research suggests that mutans streptococci play an important role in cariogenesis in children but the usefulness of bacterial testing in risk assessment is unknown. Our objective was to summarize the literature assessing the association of mutans streptococci and dental caries in preschool children, (Pre)Medline (1966-2003), Embase (1980-2003), the Cochrane Register of Controlled Trials (2003, issue 3), and reference lists of included studies were searched. All abstracts found by the electronic searches (n = 981) were independently scrutinized by 2 reviewers. Minimal requirements for inclusion were assessment of preschool children without caries at baseline, reporting of mutans streptococci present in saliva or plaque at baseline and assessment of caries presence after a minimum of 6 months of follow-up. Participants' details, test methods, methodological characteristics and findings were extracted by one reviewer and cross-checked by another. Homogeneity was tested using chi2 tests. Results of plaque and saliva testing were pooled separately using a fixed effects model. Methodological quality of reports was low. Out of 9 studies included, data from 3 reports on plaque test assessment alone (n = 300) and from 4 reports on saliva test assessment alone (n = 451) were available for pooled analysis. The pooled risk ratio (95% CI) was 3.85 (2.48-5.96) in studies using plaque tests and 2.11 (1.47-3.02) in those using saliva testing. Presence of mutans streptococci, both in plaque or saliva of young caries-free children, appears to be associated with a considerable increase in caries risk. Lack of adjustment for potential confounders in the original studies, however, limits the extent to which interpretations for practice can be made.

A Diagnostic Test for the Mixing Distribution in a Generalised Linear Mixed Model

We introduce a diagnostic test for the mixing distribution in a generalised linear mixed model. The test is based on the difference between the marginal maximum likelihood and conditional maximum likelihood estimates of a subset of the fixed effects in the model. We derive the asymptotic variance of this difference, and propose a test statistic that has a limiting chi-square distribution under the null hypothesis that the mixing distribution is correctly specified. For the important special case of the logistic regression model with random intercepts, we evaluate via simulation the power of the test in finite samples under several alternative distributional forms for the mixing distribution. We illustrate the method by applying it to data from a clinical trial investigating the effects of hormonal contraceptives in women.

A unified approach to modeling multivariate binary data using copulas over partitions

Many seemingly disparate approaches for marginal modeling have been developed in recent years. We demonstrate that many current approaches for marginal modeling of correlated binary outcomes produce likelihoods that are equivalent to the proposed copula-based models herein. These general copula models of underlying latent threshold random variables yield likelihood based models for marginal fixed effects estimation and interpretation in the analysis of correlated binary data. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalized models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate concepts.

Erythropoietin or Darbepoetin for patients with cancer--meta-analysis based on individual patient data

BACKGROUND: Erythropoiesis-stimulating agents (ESAs) reduce anemia in cancer patients and may improve quality of life, but there are concerns that ESAs might increase mortality. OBJECTIVES: Our objectives were to examine the effect of ESAs and identify factors that modify the effects of ESAs on overall survival, progression free survival, thromboembolic and cardiovascular events as well as need for transfusions and other important safety and efficacy outcomes in cancer patients. SEARCH STRATEGY: We searched the Cochrane Library, Medline, Embase and conference proceedings for eligible trials. Manufacturers of ESAs were contacted to identify additional trials. SELECTION CRITERIA: We included randomized controlled trials comparing epoetin or darbepoetin plus red blood cell transfusions (as necessary) versus red blood cell transfusions (as necessary) alone, to prevent or treat anemia in adult or pediatric cancer patients with or without concurrent antineoplastic therapy. DATA COLLECTION AND ANALYSIS: We performed a meta-analysis of randomized controlled trials comparing epoetin alpha, epoetin beta or darbepoetin alpha plus red blood cell transfusions versus transfusion alone, for prophylaxis or therapy of anemia while or after receiving anti-cancer treatment. Patient-level data were obtained and analyzed by independent statisticians at two academic departments, using fixed-effects and random-effects meta-analysis. Analyses were according to the intention-to-treat principle. Primary endpoints were on study mortality and overall survival during the longest available follow-up, regardless of anticancer treatment, and in patients receiving chemotherapy. Tests for interactions were used to identify differences in effects of ESAs on mortality across pre-specified subgroups. The present review reports only the results for the primary endpoint. MAIN RESULTS: A total of 13933 cancer patients from 53 trials were analyzed, 1530 patients died on-study and 4993 overall. ESAs increased on study mortality (combined hazard ratio [cHR] 1.17; 95% CI 1.06-1.30) and worsened overall survival (cHR 1.06; 95% CI 1.00-1.12), with little heterogeneity between trials (I(2) 0%, p=0.87 and I(2) 7.1%, p=0.33, respectively). Thirty-eight trials enrolled 10441 patients receiving chemotherapy. The cHR for on study mortality was 1.10 (95% CI 0.98-1.24) and 1.04; 95% CI 0.97-1.11) for overall survival. There was little evidence for a difference between trials of patients receiving different cancer treatments (P for interaction=0.42). AUTHORS' CONCLUSIONS: ESA treatment in cancer patients increased on study mortality and worsened overall survival. For patients undergoing chemotherapy the increase was less pronounced, but an adverse effect could not be excluded.