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Jiang, Ziren; Cao, Wenhao; Chu, Haitao; Bazerbachi, Fateh; Siegel, Lianne – Research Synthesis Methods, 2023
A reference interval, or an interval in which a prespecified proportion of measurements from a healthy population are expected to fall, is used to determine whether a person's measurement is typical of a healthy individual. For a specific biomarker, multiple published studies may provide data collected from healthy participants. A reference…
Descriptors: Intervals, Computation, Meta Analysis, Measurement
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Rott, Kollin W.; Lin, Lifeng; Hodges, James S.; Siegel, Lianne; Shi, Amy; Chen, Yong; Chu, Haitao – Research Synthesis Methods, 2021
Meta-analysis is commonly used to compare two treatments. Network meta-analysis (NMA) is a powerful extension for comparing and contrasting multiple treatments simultaneously in a systematic review of multiple clinical trials. Although the practical utility of meta-analysis is apparent, it is not always straightforward to implement, especially for…
Descriptors: Bayesian Statistics, Meta Analysis, Computation, Networks
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Cao, Wenhao; Siegel, Lianne; Zhou, Jincheng; Zhu, Motao; Tong, Tiejun; Chen, Yong; Chu, Haitao – Research Synthesis Methods, 2021
A reference interval provides a basis for physicians to determine whether a measurement is typical of a healthy individual. It can be interpreted as a prediction interval for a new individual from the overall population. However, a reference interval based on a single study may not be representative of the broader population. Meta-analysis can…
Descriptors: Meta Analysis, Statistical Analysis, Intervals, Computation
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Siegel, Lianne; Murad, M. Hassan; Chu, Haitao – Research Synthesis Methods, 2021
Often clinicians are interested in determining whether a subject's measurement falls within a normal range, defined as a range of values of a continuous outcome which contains some proportion (eg, 95%) of measurements from a healthy population. Several studies in the biomedical field have estimated reference ranges based on a meta-analysis of…
Descriptors: Meta Analysis, Medical Research, Biomedicine, Bayesian Statistics
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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
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Shi, Jiandong; Luo, Dehui; Weng, Hong; Zeng, Xian-Tao; Lin, Lu; Chu, Haitao; Tong, Tiejun – Research Synthesis Methods, 2020
When reporting the results of clinical studies, some researchers may choose the five-number summary (including the sample median, the first and third quartiles, and the minimum and maximum values) rather than the sample mean and standard deviation (SD), particularly for skewed data. For these studies, when included in a meta-analysis, it is often…
Descriptors: Statistics, Computation, Sample Size, Mathematical Formulas
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Shi, Linyu; Chu, Haitao; Lin, Lifeng – Research Synthesis Methods, 2020
Publication bias threatens meta-analysis validity. It is often assessed via the funnel plot; an asymmetric plot implies small-study effects, and publication bias is one cause of the asymmetry. Egger's regression test is a widely used tool to quantitatively assess such asymmetry. It examines the association between the observed effect sizes and…
Descriptors: Bayesian Statistics, Meta Analysis, Effect Size, Publications
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Lin, Lifeng; Chu, Haitao – Research Synthesis Methods, 2018
In medical sciences, a disease condition is typically associated with multiple risk and protective factors. Although many studies report results of multiple factors, nearly all meta-analyses separately synthesize the association between each factor and the disease condition of interest. The collected studies usually report different subsets of…
Descriptors: Bayesian Statistics, Multivariate Analysis, Meta Analysis, Correlation
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Hong, Hwanhee; Chu, Haitao; Zhang, Jing; Carlin, Bradley P. – Research Synthesis Methods, 2016
Bayesian statistical approaches to mixed treatment comparisons (MTCs) are becoming more popular because of their flexibility and interpretability. Many randomized clinical trials report multiple outcomes with possible inherent correlations. Moreover, MTC data are typically sparse (although richer than standard meta-analysis, comparing only two…
Descriptors: Bayesian Statistics, Meta Analysis, Outcomes of Treatment, Comparative Analysis