Bmc Med Res Methodol
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Bmc Med Res Methodol · Jan 2011
Comparative StudyLogistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes.
Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. ⋯ On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. Thus, for a large data set there seems to be no explicit preference (of course if there is no preference from a philosophical point of view) for either a frequentist or Bayesian approach (if based on vague priors). The choice for a particular implementation may largely depend on the desired flexibility, and the usability of the package. For small data sets the random effects variances are difficult to estimate. In the frequentist approaches the MLE of this variance was often estimated zero with a standard error that is either zero or could not be determined, while for Bayesian methods the estimates could depend on the chosen "non-informative" prior of the variance parameter. The starting value for the variance parameter may be also critical for the convergence of the Markov chain.
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Bmc Med Res Methodol · Jan 2011
Using qualitative synthesis to explore heterogeneity of complex interventions.
Including qualitative evidence on patients' perspectives in systematic reviews of complex interventions may reveal reasons for variation in trial findings. This is particularly the case when the intervention is for a long-term disease, as management may rely heavily on the efforts of the patient. Inclusion though seldom happens, possibly because of methodological challenges, and when it does occur the different forms of evidence are often kept separate. To explore heterogeneity in trial findings, we tested a novel approach to integrate qualitative review evidence on patients' perspectives with evidence from a Cochrane systematic review. ⋯ This simple approach breaks new ground in cross tabulating qualitative evidence with the characteristics of trialled interventions. In doing so it tests the assumption that patients are more likely to adhere to interventions that match more closely with their concerns. The potential of this approach in exploring varying content and rates of success in trialled complex interventions deserves further evaluation.
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Bmc Med Res Methodol · Jan 2011
The Global Evidence Mapping Initiative: scoping research in broad topic areas.
Evidence mapping describes the quantity, design and characteristics of research in broad topic areas, in contrast to systematic reviews, which usually address narrowly-focused research questions. The breadth of evidence mapping helps to identify evidence gaps, and may guide future research efforts. The Global Evidence Mapping (GEM) Initiative was established in 2007 to create evidence maps providing an overview of existing research in Traumatic Brain Injury (TBI) and Spinal Cord Injury (SCI). ⋯ GEM Initiative evidence maps have a broad range of potential end-users including funding agencies, researchers and clinicians. Evidence mapping is at least as resource-intensive as systematic reviewing. The GEM Initiative has made advancements in evidence mapping, most notably in the area of question development and prioritisation. Evidence mapping complements other review methods for describing existing research, informing future research efforts, and addressing evidence gaps.
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Bmc Med Res Methodol · Jun 2010
Comparative StudyA simulation study for comparing testing statistics in response-adaptive randomization.
Response-adaptive randomizations are able to assign more patients in a comparative clinical trial to the tentatively better treatment. However, due to the adaptation in patient allocation, the samples to be compared are no longer independent. At large sample sizes, many asymptotic properties of test statistics derived for independent sample comparison are still applicable in adaptive randomization provided that the patient allocation ratio converges to an appropriate target asymptotically. However, the small sample properties of commonly used test statistics in response-adaptive randomization are not fully studied. ⋯ The Cook's correction to chi-square test and Williams' correction to log-likelihood-ratio test are generally recommended for hypothesis test in response-adaptive randomization, especially when sample sizes are small. The generalized drop-the-loser urn design is the recommended method for its good overall properties. Also recommended is the use of the RRSIHR allocation target.
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Bmc Med Res Methodol · May 2010
The null hypothesis significance test in health sciences research (1995-2006): statistical analysis and interpretation.
The null hypothesis significance test (NHST) is the most frequently used statistical method, although its inferential validity has been widely criticized since its introduction. In 1988, the International Committee of Medical Journal Editors (ICMJE) warned against sole reliance on NHST to substantiate study conclusions and suggested supplementary use of confidence intervals (CI). Our objective was to evaluate the extent and quality in the use of NHST and CI, both in English and Spanish language biomedical publications between 1995 and 2006, taking into account the International Committee of Medical Journal Editors recommendations, with particular focus on the accuracy of the interpretation of statistical significance and the validity of conclusions. ⋯ Overall, results of our review show some improvements in statistical management of statistical results, but further efforts by scholars and journal editors are clearly required to move the communication toward ICMJE advices, especially in the clinical setting, which seems to be imperative among publications in Spanish.