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Siemens, Waldemar; Meerpohl, Joerg J.; Rohe, Miriam S.; Buroh, Sabine; Schwarzer, Guido; Becker, Gerhild – Research Synthesis Methods, 2022
Using the Hartung-Knapp method and 95% prediction intervals (PIs) in random-effects meta-analyses is recommended by experts but rarely applied. Therefore, we aimed to reevaluate statistically significant meta-analyses using the Hartung-Knapp method and 95% PIs. In this methodological study, three databases were searched from January 2010 to July…
Descriptors: Cancer, Meta Analysis, Medical Research, Patients
Siegel, Lianne; Chu, Haitao – Research Synthesis Methods, 2023
Reference intervals, or reference ranges, aid medical decision-making by containing a pre-specified proportion (e.g., 95%) of the measurements in a representative healthy population. We recently proposed three approaches for estimating a reference interval from a meta-analysis based on a random effects model: a frequentist approach, a Bayesian…
Descriptors: Bayesian Statistics, Meta Analysis, Intervals, Decision Making
Prathiba Natesan Batley; Erica B. McClure; Brandy Brewer; Ateka A. Contractor; Nicholas John Batley; Larry Vernon Hedges; Stephanie Chin – Grantee Submission, 2023
N-of-1 trials, a special case of Single Case Experimental Designs (SCEDs), are prominent in clinical medical research and specifically psychiatry due to the growing significance of precision/personalized medicine. It is imperative that these clinical trials be conducted, and their data analyzed, using the highest standards to guard against threats…
Descriptors: Medical Research, Research Design, Data Analysis, Effect Size
Weber, Frank; Knapp, Guido; Glass, Änne; Kundt, Günther; Ickstadt, Katja – Research Synthesis Methods, 2021
There exists a variety of interval estimators for the overall treatment effect in a random-effects meta-analysis. A recent literature review summarizing existing methods suggested that in most situations, the Hartung-Knapp/Sidik-Jonkman (HKSJ) method was preferable. However, a quantitative comparison of those methods in a common simulation study…
Descriptors: Meta Analysis, Computation, Intervals, Statistical Analysis
Noma, Hisashi; Hamura, Yasuyuki; Sugasawa, Shonosuke; Furukawa, Toshi A. – Research Synthesis Methods, 2023
Network meta-analysis has played an important role in evidence-based medicine for assessing the comparative effectiveness of multiple available treatments. The prediction interval has been one of the standard outputs in recent network meta-analysis as an effective measure that enables simultaneous assessment of uncertainties in treatment effects…
Descriptors: Intervals, Meta Analysis, Evidence Based Practice, Comparative Analysis
Raykov, Tenko; Pusic, Martin – Educational and Psychological Measurement, 2023
This note is concerned with evaluation of location parameters for polytomous items in multiple-component measuring instruments. A point and interval estimation procedure for these parameters is outlined that is developed within the framework of latent variable modeling. The method permits educational, behavioral, biomedical, and marketing…
Descriptors: Item Analysis, Measurement Techniques, Computer Software, Intervals
Qijun Li, Kendrick; Rice, Kenneth – Research Synthesis Methods, 2020
Meta-analysis of 2 × 2 tables is common and useful in research topics including analysis of adverse events and survey research data. Fixed-effects inference typically centers on measures of association such as the Cochran-Mantel-Haenszel statistic or Woolf's estimator, but relies on assuming exact homogeneity across studies, which is often…
Descriptors: Inferences, Meta Analysis, Intervals, Prevention
Hoyer, Annika; Kuss, Oliver – Research Synthesis Methods, 2019
Diagnostic test accuracy studies frequently report on sensitivities and specificities for more than one threshold of the diagnostic test under study. Although it is obvious that the information from all thresholds should be used for a meta-analysis, in practice, frequently, only a single pair of sensitivity and specificity is selected. To overcome…
Descriptors: Meta Analysis, Diagnostic Tests, Correlation, Intervals
Günhan, Burak Kürsad; Röver, Christian; Friede, Tim – Research Synthesis Methods, 2020
Meta-analyses of clinical trials targeting rare events face particular challenges when the data lack adequate numbers of events for all treatment arms. Especially when the number of studies is low, standard random-effects meta-analysis methods can lead to serious distortions because of such data sparsity. To overcome this, we suggest the use of…
Descriptors: Meta Analysis, Medical Research, Drug Therapy, Bayesian Statistics
Langan, Dean; Higgins, Julian P. T.; Simmonds, Mark – Research Synthesis Methods, 2017
Random-effects meta-analysis methods include an estimate of between-study heterogeneity variance. We present a systematic review of simulation studies comparing the performance of different estimation methods for this parameter. We summarise the performance of methods in relation to estimation of heterogeneity and of the overall effect estimate,…
Descriptors: Meta Analysis, Simulation, Comparative Analysis, Intervals
Mawdsley, David; Higgins, Julian P. T.; Sutton, Alex J.; Abrams, Keith R. – Research Synthesis Methods, 2017
In meta-analysis, the random-effects model is often used to account for heterogeneity. The model assumes that heterogeneity has an additive effect on the variance of effect sizes. An alternative model, which assumes multiplicative heterogeneity, has been little used in the medical statistics community, but is widely used by particle physicists. In…
Descriptors: Databases, Meta Analysis, Goodness of Fit, Effect Size
Friede, Tim; Röver, Christian; Wandel, Simon; Neuenschwander, Beat – Research Synthesis Methods, 2017
Meta-analyses in orphan diseases and small populations generally face particular problems, including small numbers of studies, small study sizes and heterogeneity of results. However, the heterogeneity is difficult to estimate if only very few studies are included. Motivated by a systematic review in immunosuppression following liver…
Descriptors: Meta Analysis, Diseases, Medical Research, Research Problems
Parker, Richard I.; Vannest, Kimberly J.; Brown, Leanne – Exceptional Children, 2009
This article describes and field-tests the improved rate difference (IRD), a new effect size for summarizing single-case research data. Termed "risk difference" in medical research, IRD expresses the difference in successful performance between baseline and intervention phases. IRD can be calculated from visual analysis of nonoverlapping data, and…
Descriptors: Effect Size, Risk, Differences, Medical Research
Salsbury, Tom; Crossley, Scott A.; McNamara, Danielle S. – Second Language Research, 2011
This study uses word information scores from the Medical Research Council (MRC) Psycholinguistic Database to analyse word development in the spontaneous speech data of six adult learners of English as a second language (L2) in a one-year longitudinal study. In contrast to broad measures of lexical development, such as word frequency and lexical…
Descriptors: Medical Research, Psycholinguistics, Second Language Learning, Familiarity
Torgerson, Carole J.; Torgerson, David J.; Birks, Yvonne F.; Porthouse, Jill – British Educational Research Journal, 2005
Health care and educational trials face similar methodological challenges. Methodological reviews of health care trials have shown that a significant proportion have methodological flaws. Whether or not educational trials have a similar proportion of poor-quality trials is unknown. The authors undertook a methodological comparison between health…
Descriptors: Intervals, Sample Size, Statistical Significance, Medical Research