scholarly journals Partial derivatives meta-analysis: pooled analyses when individual participant data cannot be shared

2016 ◽  
Author(s):  
Hieab HH Adams ◽  
Hadie Adams ◽  
Lenore J Launer ◽  
Sudha Seshadri ◽  
Reinhold Schmidt ◽  
...  
Keyword(s):  
Gold Standard ◽  
Statistical Power ◽  
Large Scale ◽  
Meta Analysis ◽  
Scientific Evidence ◽  
Joint Analysis ◽  
Individual Participant Data ◽  
Partial Derivatives ◽  
Individual Participant ◽  
Post Hoc

Joint analysis of data from multiple studies in collaborative efforts strengthens scientific evidence, with the gold standard approach being the pooling of individual participant data (IPD). However, sharing IPD often has legal, ethical, and logistic constraints for sensitive or high-dimensional data, such as in clinical trials, observational studies, and large-scale omics studies. Therefore, meta-analysis of study-level effect estimates is routinely done, but this compromises on statistical power, accuracy, and flexibility. Here we propose a novel meta-analytical approach, named partial derivatives meta-analysis, that is mathematically equivalent to using IPD, yet only requires the sharing of aggregate data. It not only yields identical results as pooled IPD analyses, but also allows post-hoc adjustments for covariates and stratification without the need for site-specific re-analysis. Thus, in case that IPD cannot be shared, partial derivatives meta-analysis still produces gold standard results, which can be used to better inform guidelines and policies on clinical practice.

scholarly journals Retrieval of Individual Participant Data for Exercise Meta-Analyses May Not Be Worth the Time and Effort

2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
George A. Kelley ◽  
Kristi S. Kelley
Keyword(s):  
Logistic Regression ◽  
Rheumatic Diseases ◽  
Gold Standard ◽  
Odds Ratio ◽  
Meta Analysis ◽  
Individual Participant Data ◽  
Individual Participant ◽  
Using Data ◽  
Meta Analyses

Purpose. While individual participant data (IPD) meta-analyses are considered the gold standard for meta-analysis, the feasibility of obtaining IPD may be problematic.Methods. Using data from a previous meta-analysis of 29 studies on exercise in adults with arthritis and other rheumatic diseases, the percentage of studies in which useable IPD was provided was calculated.Results. Eight of 29 authors (28%, 95% CI = 11% to 44%) provided IPD. Using logistic regression, neither year of publication (odds ratio = 1.05, 95% CI = 0.90 to 1.27,p=0.58) nor country (odds ratio = 1.36, 95% CI = 0.20 to 10.9,p=1.00) was significantly associated with the obtainment of IPD.Conclusions. The retrieval of IPD for exercise meta-analyses may not be worth the time and effort. However, further research is needed before any final recommendations can be made.

scholarly journals Analyzing data of a multi-lab replication project with individual participant data meta-analysis: A tutorial

2020 ◽  
Author(s):  
Robbie Cornelis Maria van Aert
Keyword(s):  
Statistical Power ◽  
Meta Analysis ◽  
Individual Participant Data ◽  
Moderator Effects ◽  
Analysis Methods ◽  
Individual Participant ◽  
Level I ◽  
Summary Data ◽  
Analyze Data

Multi-lab replication projects such as Registered Replication Reports and Many Labs projects are used to replicate an effect in different labs. Data of these projects are usually analyzed using conventional meta-analysis methods. This is a valid approach, but it does not make optimal use of the available data as summary data are analyzed rather than the participant data. I propose to analyze data of multi-lab replication projects by using individual participant data (IPD) meta-analysis where the participant data are analyzed directly. Two important advantages of IPD meta-analysis are that it generally has larger statistical power to detect moderator effects and allows drawing conclusions at the participant rather than lab level. I illustrate IPD meta-analysis using the published Registered Replication Report by McCarthy et al. (2018) and provide R code and offer recommendations to facilitate researchers to apply these methods to their own data.

scholarly journals The Contribution of “Individual Participant Data” Meta-Analyses of Psychotherapies for Depression to the Development of Personalized Treatments: A Systematic Review

2022 ◽  
Vol 12 (1) ◽  
pp. 93
Author(s):  
Pim Cuijpers ◽  
Marketa Ciharova ◽  
Soledad Quero ◽  
Clara Miguel ◽  
Ellen Driessen ◽  
...  
Keyword(s):  
Systematic Review ◽  
Statistical Power ◽  
Randomized Trials ◽  
Meta Analysis ◽  
Primary Data ◽  
Individual Participant Data ◽  
Psychological Treatments ◽  
Gender Education ◽  
Individual Participant ◽  
Meta Analyses

While randomized trials typically lack sufficient statistical power to identify predictors and moderators of outcome, “individual participant data” (IPD) meta-analyses, which combine primary data of multiple randomized trials, can increase the statistical power to identify predictors and moderators of outcome. We conducted a systematic review of IPD meta-analyses on psychological treatments of depression to provide an overview of predictors and moderators identified. We included 10 (eight pairwise and two network) IPD meta-analyses. Six meta-analyses showed that higher baseline depression severity was associated with better outcomes, and two found that older age was associated with better outcomes. Because power was high in most IPD meta-analyses, non-significant findings are also of interest because they indicate that these variables are probably not relevant as predictors and moderators. We did not find in any IPD meta-analysis that gender, education level, or relationship status were significant predictors or moderators. This review shows that IPD meta-analyses on psychological treatments can identify predictors and moderators of treatment effects and thereby contribute considerably to the development of personalized treatments of depression.

Meta-analysis using individual participant data is the gold standard for diagnostic studies

Hepatology ◽  
2011 ◽  
Vol 53 (3) ◽  
pp. 1062-1063 ◽  
Author(s):  
Ming-Hua Zheng ◽  
Ke-Qing Shi ◽  
Yu-Chen Fan ◽  
Yong-Ping Chen
Keyword(s):  
Gold Standard ◽  
Meta Analysis ◽  
Individual Participant Data ◽  
Diagnostic Studies ◽  
Individual Participant

scholarly journals Effect of dietary nitrate on human muscle power: a systematic review and individual participant data meta-analysis

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Andrew R. Coggan ◽  
Marissa N. Baranauskas ◽  
Rachel J. Hinrichs ◽  
Ziyue Liu ◽  
Stephen J. Carter
Keyword(s):  
Systematic Review ◽  
Fixed Effects ◽  
Statistical Power ◽  
Muscle Power ◽  
Meta Analysis ◽  
Human Muscle ◽  
Individual Participant Data ◽  
Fixed Effects Model ◽  
Dietary Nitrate ◽  
Individual Participant

Abstract Background Previous narrative reviews have concluded that dietary nitrate (NO3−) improves maximal neuromuscular power in humans. This conclusion, however, was based on a limited number of studies, and no attempt has been made to quantify the exact magnitude of this beneficial effect. Such information would help ensure adequate statistical power in future studies and could help place the effects of dietary NO3− on various aspects of exercise performance (i.e., endurance vs. strength vs. power) in better context. We therefore undertook a systematic review and individual participant data meta-analysis to quantify the effects of NO3− supplementation on human muscle power. Methods The literature was searched using a strategy developed by a health sciences librarian. Data sources included Medline Ovid, Embase, SPORTDiscus, Scopus, Clinicaltrials.gov, and Google Scholar. Studies were included if they used a randomized, double-blind, placebo-controlled, crossover experimental design to measure the effects of dietary NO3− on maximal power during exercise in the non-fatigued state and the within-subject correlation could be determined from data in the published manuscript or obtained from the authors. Results Nineteen studies of a total of 268 participants (218 men, 50 women) met the criteria for inclusion. The overall effect size (ES; Hedge’s g) calculated using a fixed effects model was 0.42 (95% confidence interval (CI) 0.29, 0.56; p = 6.310 × 10− 11). There was limited heterogeneity between studies (i.e., I2 = 22.79%, H2 = 1.30, p = 0.3460). The ES estimated using a random effects model was therefore similar (i.e., 0.45, 95% CI 0.30, 0.61; p = 1.064 × 10− 9). Sub-group analyses revealed no significant differences due to subject age, sex, or test modality (i.e., small vs. large muscle mass exercise). However, the ES in studies using an acute dose (i.e., 0.54, 95% CI 0.37, 0.71; p = 6.774 × 10− 12) was greater (p = 0.0211) than in studies using a multiple dose regimen (i.e., 0.22, 95% CI 0.01, 0.43; p = 0.003630). Conclusions Acute or chronic dietary NO3− intake significantly increases maximal muscle power in humans. The magnitude of this effect–on average, ~ 5%–is likely to be of considerable practical and clinical importance.

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