Neglect of publication bias compromises meta-analyses of educational research.
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ABSTRACT:
SUBMITTER: Ropovik I
PROVIDER: S-EPMC8174709 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionPositive results have a greater chance of being published and outcomes that are statistically significant have a greater chance of being fully reported. One consequence of research underreporting is that it may influence the sample of studies that is available for a meta-analysis. Smaller studies are often characterized by larger effects in published meta-analyses, which can be possibly explained by publication bias. We investigated the association between the statistical significance of the results and the probability of being included in recent meta-analyses.MethodsFor meta-analyses of clinical trials, we defined the relative risk as the ratio of the probability of including statistically significant results favoring the treatment to the probability of including other results. For meta-analyses of other studies, we defined the relative risk as the ratio of the probability of including biologically plausible statistically significant results to the probability of including other results. We applied a Bayesian selection model for meta-analyses that included at least 30 studies and were published in four major general medical journals (BMJ, JAMA, Lancet, and PLOS Medicine) between 2008 and 2012.ResultsWe identified 49 meta-analyses. The estimate of the relative risk was greater than one in 42 meta-analyses, greater than two in 16 meta-analyses, greater than three in eight meta-analyses, and greater than five in four meta-analyses. In 10 out of 28 meta-analyses of clinical trials, there was strong evidence that statistically significant results favoring the treatment were more likely to be included. In 4 out of 19 meta-analyses of observational studies, there was strong evidence that plausible statistically significant outcomes had a higher probability of being included.ConclusionsPublication bias was present in a substantial proportion of large meta-analyses that were recently published in four major medical journals.
| S-EPMC3868709 | biostudies-literature
Project description:We propose sensitivity analyses for publication bias in meta-analyses. We consider a publication process such that 'statistically significant' results are more likely to be published than negative or "non-significant" results by an unknown ratio, η. Our proposed methods also accommodate some plausible forms of selection based on a study's standard error. Using inverse probability weighting and robust estimation that accommodates non-normal population effects, small meta-analyses, and clustering, we develop sensitivity analyses that enable statements such as 'For publication bias to shift the observed point estimate to the null, "significant" results would need to be at least 30 fold more likely to be published than negative or "non-significant" results'. Comparable statements can be made regarding shifting to a chosen non-null value or shifting the confidence interval. To aid interpretation, we describe empirical benchmarks for plausible values of η across disciplines. We show that a worst-case meta-analytic point estimate for maximal publication bias under the selection model can be obtained simply by conducting a standard meta-analysis of only the negative and 'non-significant' studies; this method sometimes indicates that no amount of such publication bias could 'explain away' the results. We illustrate the proposed methods by using real meta-analyses and provide an R package: PublicationBias.
| S-EPMC7590147 | biostudies-literature
Project description:OBJECTIVE:To assess the effect of publication bias on the results and conclusions of systematic reviews and meta-analyses. DESIGN:Analysis of published meta-analyses by trim and fill method. STUDIES:48 reviews in Cochrane Database of Systematic Reviews that considered a binary endpoint and contained 10 or more individual studies. MAIN OUTCOME MEASURES:Number of reviews with missing studies and effect on conclusions of meta-analyses. RESULTS:The trim and fill fixed effects analysis method estimated that 26 (54%) of reviews had missing studies and in 10 the number missing was significant. The corresponding figures with a random effects model were 23 (48%) and eight. In four cases, statistical inferences regarding the effect of the intervention were changed after the overall estimate for publication bias was adjusted for. CONCLUSIONS:Publication or related biases were common within the sample of meta-analyses assessed. In most cases these biases did not affect the conclusions. Nevertheless, researchers should check routinely whether conclusions of systematic reviews are robust to possible non-random selection mechanisms.
| S-EPMC27401 | biostudies-literature
Project description:Publication bias is a substantial problem for the credibility of research in general and of meta-analyses in particular, as it yields overestimated effects and may suggest the existence of non-existing effects. Although there is consensus that publication bias exists, how strongly it affects different scientific literatures is currently less well-known. We examined evidence of publication bias in a large-scale data set of primary studies that were included in 83 meta-analyses published in Psychological Bulletin (representing meta-analyses from psychology) and 499 systematic reviews from the Cochrane Database of Systematic Reviews (CDSR; representing meta-analyses from medicine). Publication bias was assessed on all homogeneous subsets (3.8% of all subsets of meta-analyses published in Psychological Bulletin) of primary studies included in meta-analyses, because publication bias methods do not have good statistical properties if the true effect size is heterogeneous. Publication bias tests did not reveal evidence for bias in the homogeneous subsets. Overestimation was minimal but statistically significant, providing evidence of publication bias that appeared to be similar in both fields. However, a Monte-Carlo simulation study revealed that the creation of homogeneous subsets resulted in challenging conditions for publication bias methods since the number of effect sizes in a subset was rather small (median number of effect sizes equaled 6). Our findings are in line with, in its most extreme case, publication bias ranging from no bias until only 5% statistically nonsignificant effect sizes being published. These and other findings, in combination with the small percentages of statistically significant primary effect sizes (28.9% and 18.9% for subsets published in Psychological Bulletin and CDSR), led to the conclusion that evidence for publication bias in the studied homogeneous subsets is weak, but suggestive of mild publication bias in both psychology and medicine.
| S-EPMC6461282 | biostudies-literature
Project description:Publication bias is a serious problem in systematic reviews and meta-analyses, which can affect the validity and generalization of conclusions. Currently, approaches to dealing with publication bias can be distinguished into two classes: selection models and funnel-plot-based methods. Selection models use weight functions to adjust the overall effect size estimate and are usually employed as sensitivity analyses to assess the potential impact of publication bias. Funnel-plot-based methods include visual examination of a funnel plot, regression and rank tests, and the nonparametric trim and fill method. Although these approaches have been widely used in applications, measures for quantifying publication bias are seldom studied in the literature. Such measures can be used as a characteristic of a meta-analysis; also, they permit comparisons of publication biases between different meta-analyses. Egger's regression intercept may be considered as a candidate measure, but it lacks an intuitive interpretation. This article introduces a new measure, the skewness of the standardized deviates, to quantify publication bias. This measure describes the asymmetry of the collected studies' distribution. In addition, a new test for publication bias is derived based on the skewness. Large sample properties of the new measure are studied, and its performance is illustrated using simulations and three case studies.
| S-EPMC5953768 | biostudies-literature
Project description:Selective publication and reporting in individual papers compromise the scientific record, but are meta-analyses as compromised as their constituent studies? We systematically sampled 63 meta-analyses (each comprising at least 40 studies) in PLoS One, top medical journals, top psychology journals, and Metalab, an online, open-data database of developmental psychology meta-analyses. We empirically estimated publication bias in each, including only the peer-reviewed studies. Across all meta-analyses, we estimated that "statistically significant" results in the expected direction were only 1.17 times more likely to be published than "nonsignificant" results or those in the unexpected direction (95% CI: [0.93, 1.47]), with a confidence interval substantially overlapping the null. Comparable estimates were 0.83 for meta-analyses in PLoS One, 1.02 for top medical journals, 1.54 for top psychology journals, and 4.70 for Metalab. The severity of publication bias did differ across individual meta-analyses; in a small minority (10%; 95% CI: [2%, 21%]), publication bias appeared to favor "significant" results in the expected direction by more than threefold. We estimated that for 89% of meta-analyses, the amount of publication bias that would be required to attenuate the point estimate to the null exceeded the amount of publication bias estimated to be actually present in the vast majority of meta-analyses from the relevant scientific discipline (exceeding the 95th percentile of publication bias). Study-level measures ("statistical significance" with a point estimate in the expected direction and point estimate size) did not indicate more publication bias in higher-tier versus lower-tier journals, nor in the earliest studies published on a topic versus later studies. Overall, we conclude that the mere act of performing a meta-analysis with a large number of studies (at least 40) and that includes non-headline results may largely mitigate publication bias in meta-analyses, suggesting optimism about the validity of meta-analytic results.
| S-EPMC7954980 | biostudies-literature
Project description:BackgroundSystematic reviews and meta-analyses of pre-clinical studies, in vivo animal experiments in particular, can influence clinical care. Publication bias is one of the major threats of validity in systematic reviews and meta-analyses. Previous empirical studies suggested that systematic reviews and meta-analyses have become more prevalent until 2010 and found evidence for compromised methodological rigor with a trend towards improvement. We aim to comprehensively summarize and update the evidence base on systematic reviews and meta-analyses of animal studies, their methodological quality and assessment of publication bias in particular.Methods/designThe objectives of this systematic review are as follows: •To investigate the epidemiology of published systematic reviews of animal studies until present. •To examine methodological features of systematic reviews and meta-analyses of animal studies with special attention to the assessment of publication bias. •To investigate the influence of systematic reviews of animal studies on clinical research by examining citations of the systematic reviews by clinical studies. Eligible studies for this systematic review constitute systematic reviews and meta-analyses that summarize in vivo animal experiments with the purpose of reviewing animal evidence to inform human health. We will exclude genome-wide association studies and animal experiments with the main purpose to learn more about fundamental biology, physical functioning or behavior. In addition to the inclusion of systematic reviews and meta-analyses identified by other empirical studies, we will systematically search Ovid Medline, Embase, ToxNet, and ScienceDirect from 2009 to January 2013 for further eligible studies without language restrictions. Two reviewers working independently will assess titles, abstracts, and full texts for eligibility and extract relevant data from included studies. Data reporting will involve a descriptive summary of meta-analyses and systematic reviews.DiscussionResults are expected to be publicly available later in 2013 and may form the basis for recommendations to improve the quality of systematic reviews and meta-analyses of animal studies and their use with respect to clinical care.
| S-EPMC3651300 | biostudies-literature
Project description:BACKGROUND: Despite efforts to assure high methodological standards, systematic reviews may be affected by publication bias. The objective of this study was to evaluate the occurrence of publication bias in a collection of high quality systematic reviews on reproductive health. METHODS: Systematic reviews included in the Reproductive Health Library (RHL), issue No 9, were assessed. Funnel plot was used to assess meta-analyses containing 10 or more trials reporting a binary outcome. A funnel plot, the estimated number of missing studies and the adjusted combined effect size were obtained using the "trim and fill method". Meta-analyses results that were not considered to be robust due to a possible publication bias were submitted to a more detailed assessment. RESULTS: A total of 21 systematic reviews were assessed. The number of trials comprising each one ranged from 10 to 83 (median = 13), totaling 379 trials, whose results have been summarized. None of the reviews had reported any evaluation of publication bias or funnel plot asymmetry. Some degree of asymmetry in funnel plots was observed in 18 of the 21 meta-analyses evaluated (85.7%), with the estimated number of missing studies ranging from 1 to 18 (median = 3). Only for three meta-analyses, the conclusion could not be considered robust due to a possible publication bias. CONCLUSION: Asymmetry is a frequent finding in funnel plots of meta-analyses in reproductive health, but according to the present evaluation, less than 15% of meta-analyses report conclusions that would not be considered robust. Publication bias and other sources of asymmetry in funnel plots should be systematically addressed by reproductive health meta-analysts. Next amendments in Cochrane systematic reviews should include this type of evaluation. Further studies regarding the evolution of effect size and publication bias over time in systematic reviews in reproductive health are needed.
| S-EPMC1855315 | biostudies-literature
Project description:The validity of research synthesis is threatened if published studies comprise a biased selection of all studies that have been conducted. We conducted a meta-analysis to ascertain the strength and consistency of the association between study results and formal publication.The Cochrane Methodology Register Database, MEDLINE and other electronic bibliographic databases were searched (to May 2009) to identify empirical studies that tracked a cohort of studies and reported the odds of formal publication by study results. Reference lists of retrieved articles were also examined for relevant studies. Odds ratios were used to measure the association between formal publication and significant or positive results. Included studies were separated into subgroups according to starting time of follow-up, and results from individual cohort studies within the subgroups were quantitatively pooled.We identified 12 cohort studies that followed up research from inception, four that included trials submitted to a regulatory authority, 28 that assessed the fate of studies presented as conference abstracts, and four cohort studies that followed manuscripts submitted to journals. The pooled odds ratio of publication of studies with positive results, compared to those without positive results (publication bias) was 2.78 (95% CI: 2.10 to 3.69) in cohorts that followed from inception, 5.00 (95% CI: 2.01 to 12.45) in trials submitted to regulatory authority, 1.70 (95% CI: 1.44 to 2.02) in abstract cohorts, and 1.06 (95% CI: 0.80 to 1.39) in cohorts of manuscripts.Dissemination of research findings is likely to be a biased process. Publication bias appears to occur early, mainly before the presentation of findings at conferences or submission of manuscripts to journals.
| S-EPMC2789098 | biostudies-literature
Project description:Publication bias frequently appears in meta-analyses when the included studies' results (e.g., p-values) influence the studies' publication processes. Some unfavorable studies may be suppressed from publication, so the meta-analytic results may be biased toward an artificially favorable direction. Many statistical tests have been proposed to detect publication bias in recent two decades. However, they often make dramatically different assumptions about the cause of publication bias; therefore, they are usually powerful only in certain cases that support their particular assumptions, while their powers may be fairly low in many other cases. Although several simulation studies have been carried out to compare different tests' powers under various situations, it is typically infeasible to justify the exact mechanism of publication bias in a real-world meta-analysis and thus select the corresponding optimal publication bias test. We introduce a hybrid test for publication bias by synthesizing various tests and incorporating their benefits, so that it maintains relatively high powers across various mechanisms of publication bias. The superior performance of the proposed hybrid test is illustrated using simulation studies and three real-world meta-analyses with different effect sizes. It is compared with many existing methods, including the commonly used regression and rank tests, and the trim-and-fill method.
| S-EPMC7434640 | biostudies-literature