Publication bias (PB) makes the resources for meta-analysis (M-A) unreliable in the sense of completion and accuracy, so to investigate, identify and correct PB is a very important issue in M-A. The current study proposed an empirical comparison in both detection and correcting PB, using a Monte Carlo study. Conditions to be manipulated include the number of primary studies, number of missing studies and true effect size. RANNOR in SAS will be used to generate normally distributed random variables and, for each condition, 10,000 M-As will be simulated. Type I error rates are to be calculated for the conditions with no PB and powers were estimated for the conditions with PB and adequate type I error control. Finally, a demonstration of how M-A can and should be used as a part of program evaluations was given. / text

Background: Multiple sclerosis (MS) is the most common cause of disability in young people and yet there are no interventions available which reliably alter disease progression. This is despite several decades of research using the most common animal model of multiple sclerosis, experimental autoimmune encephalomyelitis (EAE). There is now emerging evidence across the neurosciences to suggest that limited internal validity (measures to reduce bias) and external validity (e.g. using a clinically relevant animal model) may influence the translational success. Aim and objectives: To provide an unbiased summary of the scope of the literature on candidate drugs for MS tested in EAE to identify potential reasons for the failures to translate efficacy to clinical trials. My objectives were, across all of the identified publications, to: (1) describe the reporting of measures to reduce bias and to assess their impact on measures of drug efficacy; (2) assess the relationship between treatment related effects measured using different outcome measures; (3) assess the prevalence and impact of any publication bias; (4) compare findings from the above with another disease with limited translational success (Parkinson’s disease; PD). Methods: I used systematic searches of three online databases to identify relevant publications. Estimates of efficacy were extracted for neurobehavioural scores, inflammation, demyelination and axon loss. For PD experiments, we searched for dopamine agonists tested in animal models of PD with outcome assessed as change in neurobehavioural scores. I calculated normalised mean difference or standardised mean difference effect sizes and combined these in a meta-analysis using a random effects model. I used stratified meta-analysis or meta-regression to assess the extent to which different study design characteristics explained differences in reported efficacies. These characteristics included: measures to reduce bias (random allocation to group and blinded assessment of outcome), the animal species, sex, time of drug administration, route of drug administration and the number of animals per group. Publication bias was assessed using funnel plotting, Egger regression and “trim and fill”. Results: I identified 1464 publications reporting drugs tested in EAE. Reported study quality was poor: 11% reported random allocation to group, 17% reported blinded assessment of neurobehavioural outcomes, 28% reported blinded assessment of histological outcomes, and < 1% reported a sample size calculation. Estimates of efficacy measured as the reduction in inflammation were substantially higher in unblinded studies (47.1% reduction (95% CI 41.8-52.4)) versus blinded studies (33.1% (25.8-40.4). Moreover, the same finding was identified for 121 publications on dopamine agonists tested in experimental PD models where efficacy was measured as change in neurobehavioural outcomes. For EAE studies we were unable to include data from 631 publications describing original research. Usually this was because the publication did not include basic details such as the number of animals in each group (115 publications), the observed variance (592) or suitable control data (49). For each category of outcome I found evidence of a substantial publication bias. Interventions were most commonly administered on or before the induction of EAE with shorter times to treatment associated with higher estimates of efficacy for the reduction in mean severity scores (a neurobehavioural outcome). Treatment related effects were found to vary across different outcome measures with the largest effect being for the reduction in axon loss. Where neurobehavioural scores and axon loss were measured in the same cohort of animals, the concordance between efficacies in these increased with later times to treatment. Conclusions: In this, the largest systematic review and meta-analysis of animal studies in any domain, I have found that a large number of publications present incomplete data. In addition, measures to reduce bias are seldom reported, the lack of which is associated with overstatements of efficacy for both a measure of drug efficacy in EAE and experimental PD studies. Translational success may have also been affected by the majority of studies administering drugs on or before EAE induction which is of limited relevance in the clinical setting where patients do not present at that stage of disease. Moreover, my analysis of the relationship between outcome measures provides empirical evidence from systematically identified studies to suggest that targeting axon loss as later time points is most strongly associated with improvements in neurobehavioural scores. Therefore drugs which are successfully able to target axon loss at these time points may offer substantial hope for clinical success. Overall, improvements in the conduct and reporting of preclinical studies are likely to improve their utility, and the prospects for translational success. While my findings relate predominately to the animal modelling of MS and PD it is likely that they also hold for other animal research.

Background: In September 2005, scientific journals began requiring trial protocol registration to increase transparency and accountability. Objective: My primary objectives were: develop a database of linked protocols and publications for surgical randomized control trials (RCTs); estimate the proportion published; and determine the proportion exhibiting selective outcome reporting. Methods: A systematic search of the clinicaltrials.gov database was conducted identifying surgical RCTs, completed between 2006 and 2012. Protocols were linked with publications. Primary outcomes were compared. Results: We identified a cohort of 743 surgical RCT protocols. The proportion of registered trials which published their primary results was 0.49 (n=364). The proportion of selective outcome reporting was estimated to be 0.244, significantly lower than the previous estimate (p<0.001). Conclusion: More than half of the completed surgical RCTs were unpublished, and one quarter of those published selectively reported their primary outcome. This supports the notion that significant bias is present in the surgical literature.

The association between economic freedom and economic growth has been largely explored by researchers and the overall ndings indicate a signi cant and positive relationship. The empirical literature, however, is subject to suer from bias. In this paper we collect 16,070 estimates from 69 studies and using recently developed meta-analytic techniques investigate the eect of publication and speci cation biases on the reported results. While our baseline analysis re- ports some evidence for publication bias, but not very strong and robust, and con rms the speci cation bias reported by previous reviews, we also nd that these results are aected by the inclusion of three in uential outliers in the data set. Once we trim these studies, there is no evidence of speci cation bias anymore and we nd evidence of a robust and strong publication bias. Further, after controlling for the bias, we nd that the true eect of economic freedom on growth is substantially smaller than the eect reported by the empirical literature. JEL Classi cation O43; P10; P12; C52 Keywords 'economic freedom', 'economic growth', 'publi- cation bias', 'speci cation bias', 'meta-analysis' Title Economic freedom and economic growth: A Meta-Analysis

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Conclusions. The sensitivity and positive predictive value are generally more concerned than the specificity and negative predictive value in assessing and adjusting publication bias in meta-analyses. In this sense, Egger's regression can be recommended for its high sensitivity, while any positive result from Tang's method would suggest a probability of bias that should be taken seriously. Given the different patterns of the accuracy with the OR and the P1-P2 combination, a combination of Egger's regression and Tang's regression would be advisable. Further studies are needed to study the accuracy of methods used in combination. / Due to sampling error and true heterogeneity, a single study cannot provide a comprehensive picture and a precise estimate of, say the effectiveness of a treatment. Systematic reviews that identify and integrate relevant studies have become the most important scientific, quantitative method to summarize scientific research. Meta-analysis is the statistical method used in systematic reviews to combine results from individual studies. / However, due to selective submission and publication, not all relevant studies conducted, especially those unpublished studies with an insignificant negative result, are easily accessible to those who conduct reviews. As a result, the truth, say, the effect of a treatment, would be overestimated. This phenomenon is known as publication bias. A few methods for detecting the bias have been developed and used in meta-analyses. Although their accuracy has been studied, some important issues remain to be answered, such as when would a method be good enough for practical use and is it similarly good for different definitions of the odds ratio? / Methods. We conducted a simulation study to examine the accuracy of four commonly used bias-detection methods with various ORs and P1-P2 combinations. In a simulation study, the true bias status can be predetermined and thus be compared with the results of the bias-detection methods. The four methods are Egger's regression, funnel plot regression, rank correlation regression, and Tang's regression. Realistic sample size was used for simulating individual studies and the numbers of studies in a meta-analysis was also varied. Both the sensitivity and specificity are examined against the magnitude of the OR and the P1-P 2 combination to identify the ORs and P1-P 2 combinations for which a method is sufficiently accurate. Predictive values are also examined for the same reason and in the same manner. / Results. The sensitivity and positive predictive value are generally low and in particular when the OR is close to one for which publication bias is of a particular concern. Egger's regression has the highest sensitivity among the four, in particular when the OR is neither close to one nor exceptionally large or small. Due to the relatively lower specificity, the positive predictive value of Egger's regression is not as high as that for Tang's regression and funnel plot regression. Tang's regression and funnel plot regression are very similar in sensitivity, specificity and predictive values, with the former being slightly better. Rank correlation seems the least accurate method overall. Tang's regression has in general the highest positive predictive value among the four methods in particular when the OR is below one. / Chung Chi-keung. / "June 2006." / Adviser: Tang Jin Ling. / Source: Dissertation Abstracts International, Volume: 68-03, Section: B, page: 1588. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 116-124). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

This diploma thesis presents a meta-analysis of the accumulated empirical evidence on the relationship between financial development and economic growth. So far, hundreds of studies have been written on the role of financial systems in economic growth; however, their results are ambiguous. This is supported both by theory and empirical research. In order to shed some light on the underlying relationship, narrative literature surveys have been conducted. Nevertheless, the authors of these surveys select representative studies for inclusion subjectively and thus build their results on only a limited set of information. Moreover, due to the nature of their analyses, they cannot systematically assess which factors influence the heterogeneity in reported findings or whether the results are driven by the desire to produce only positive and statistically significant results. Thus, the main focus of our work lies in investigating what the role of financial development in economic growth is, adjusted for possible publication selection, and to systematically explain the heterogeneity behind reported results. For this analysis a pool of available studies investigating the underlying relationship was collected. More specifically, our analysis takes into account data from 67 empirical studies with 1334...

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As an economically as well as politically sensitive topic, labor market interventions stir up discussions among professionals as well as general public. Most economists take negative stance against minimum wage policies providing arguments backed by theoretical reasoning rather then sound empirical evidence. Knowledge of labor market outcomes and their transmission channel to other segments of the economy are till nowadays limited and inconsistent. Neither empirical research in the field contributes to a uniform consent on the impact of minimum wage hikes on the price level. Moreover, the reported estimates display large heterogeneity and after a brief inspection reveal that the field is infested with publication selectivity. A uniquely constructed dataset consisting of 469 estimates of the price effect of minimum wage changes and their associated characteristics is analyzed using a set of statistical tools generally known as meta-analysis. The method is a powerful tool nowadays widely used in empirical research to synthesize and systematically evaluate sometimes inconsistent research results. While the study finds no consistent evidence of an actual link between minimum wage hikes and inflationary pressures, the empirical results show strong presence of publication selectivity. Powered by TCPDF (www.tcpdf.org)

The impact of inequality on economic growth has become a topic of broad and current interest. Multiple researches investigated the issue but the disparity of opinions and empirical results is huge. The present thesis revises the pri- mary literature through a meta-analytical approach applying Bayesian Model Averaging (BMA) estimation technique. We examine 562 estimates collected from 58 studies published between 1991 and 2015. I find the evidence of the publication bias presence in the literature. The authors of primary studies tend to report preferentially negative and significant estimates. The BMA results suggest that the effect of inequality on growth is not straightforward and is likely not linear. A single pattern for inequality/growth relationship is not fea- sible since the results vary across used income inequality measures, estimation methods and data structure and quality. JEL Classification D31, O10, C11, C82 Keywords meta-analysis, inequality, economic growth, Bayesian model averaging, publication bias Author's e-mail 23376990@fsv.cuni.cz Supervisor's e-mail zuzana.havrankova@fsv.cuni.cz