Papers in this group
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Awareness of potential biases is important for both researchers and policy-makers in public health: for researchers when designing and conducting studies, and for policy-makers when reading study reports and making decisions. This paper explains the…
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BACKGROUND: Statistical tests for funnel-plot asymmetry are common in meta-analyses. Inappropriate application can generate misleading inferences about publication bias. We aimed to measure, in a survey of meta-analyses, how frequently the…
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ABSTRACT: BACKGROUND: Laboratory testing in clinical practice is never a random process. In this study we evaluated testing bias for neutrophil counts in clinical practice by using results from requested and non-requested hematological blood tests.…
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Based on the epidemiological association between residential exposure to extremely low frequency-magnetic fields (ELF-MF) and childhood leukaemia, the International Agency for Research on Cancer classified ELF-MF as a possible human carcinogen.…
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BACKGROUND: Assessing the risk of bias in individual studies in a systematic review can be done using individual components or by summarizing the study quality in an overall score. METHODS: We examined the instructions to authors of the 50 Cochrane…
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BACKGROUND: The study design with the smallest bias for causal inference is a perfect randomized clinical trial. Since this design is often not feasible in epidemiologic studies, an important challenge is to model bias properly and take random and…
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PURPOSE: To systematically review observational studies on medical interventions to determine the quality of reporting of confounding. METHODS: Articles on observational studies on medical interventions in five general medical journals and five…
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BACKGROUND: Cluster randomised trials can be susceptible to a range of methodological problems. These problems are not commonly recognised by many researchers. In this paper we discuss the issues that can lead to bias in cluster trials. METHODS: We…
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In randomized studies with missing outcomes, non-identifiable assumptions are required to hold for valid data analysis. As a result, statisticians have been advocating the use of sensitivity analysis to evaluate the effect of varying assumptions on…
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OBJECTIVES: Despite the recognition of selection biases arising from the healthy worker effect in occupational mortality studies, the possibility of similar effects in occupational cohort studies on respiratory symptoms is not well known. Two…
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The trustworthiness of meta-analysis, a set of techniques used to quantitatively combine results from different studies, has recently been questioned. Problems with meta-analysis stem from bias in selecting studies to include in a meta-analysis and…
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CONTEXT: The literature contains a large number of potential biases in the evaluation of diagnostic tests. Strict application of appropriate methodological criteria would invalidate the clinical application of most study results. OBJECTIVE: To…