Get real in individual participant data (IPD) meta‐analysis: a review of the methodology

Multiple Imputation for Nonresponse in Surveys

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Multiple imputation: a primer

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Randomized, Controlled Trials, Observational Studies, and the Hierarchy of Research Designs

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Review: a gentle introduction to imputation of missing values.

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Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves

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Meta-analysis of individual participant data: rationale, conduct, and reporting

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Flexible parametric proportional‐hazards and proportional‐odds models for censored survival data, with application to prognostic modelling and estimation of treatment effects

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Comparison of Evidence of Treatment Effects in Randomized and Nonrandomized Studies

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Zero‐Inflated Poisson and Binomial Regression with Random Effects: A Case Study

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Random effects meta-analysis of event outcome in the framework of the generalized linear mixed model with applications in sparse data

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Endometrial scratching in women undergoing IVF/ICSI: an individual participant data meta-analysis

van Hoogenhuijze, N. E., Casarramona, G. L., Lensen, S. F., Farquhar, C. M., Kamath, M. S., Kunjummen, A. T., Raine‐Fenning, N., Berntsen, S., Pinborg, A. B., Mackens, S., et al. (2023) · Human Reproduction Update · doi:10.1093/humupd/dmad014 · Cited by 26

Complex self-management interventions in chronic disease unravelled: a review of lessons learned from an individual patient data meta-analysis

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Working memory moderates the relation between the brain-derived neurotropic factor (BDNF) and psychotherapy outcome for depression

Bruijniks, S. J. E., van Grootheest, G., Cuijpers, P. J., de Kluiver, H., Vinkers, C. H., Peeters, F. P. M. L., Penninx, B. W. J. H., Teunissen, C. E., & Huibers, M. J. H. (2020) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2020.07.045 · Cited by 27

Harmonising measures of knee and hip osteoarthritis in population-based cohort studies: an international study

Leyland, K. M., Gates, L., Nevitt, M. C., Felson, D. T., Bierma‐Zeinstra, S., Conaghan, P. G., Engebretsen, L., Hochberg, M. C., Hunter, D. J., Jones, G., et al. (2018) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2018.01.024 · Cited by 25

Moderators of the Effect of Spinal Manipulative Therapy on Pain Relief and Function in Patients with Chronic Low Back Pain

de Zoete, A., de Boer, M. R., Rubinstein, S. M., van Tulder, M. W., Underwood, M. R., Hayden, J. A., Buffart, L. M., & Ostelo, R. (2020) · Spine · doi:10.1097/brs.0000000000003814 · Cited by 27

One‐stage random effects meta‐analysis using linear mixed models for aggregate continuous outcome data

Papadimitropoulou, K., Stijnen, T., Dekkers, O. M., & le Cessie, S. (2018) · Research Synthesis Methods · doi:10.1002/jrsm.1331 · Cited by 25

GetReal in mathematical modelling: a review of studies predicting drug effectiveness in the real world.

Panayidou, K., Gsteiger, S., Egger, M., Kilcher, G., Carreras, M., Efthimiou, O., Debray, T. P. A., Trelle, S., Hummel, N., & on behalf of the GetReal methods review group (2016) · Research Synthesis Methods · doi:10.1002/jrsm.1202 · Cited by 24

Adverse events after antipsychotic discontinuation: an individual participant data meta-analysis.

Brandt, L., Schneider‐Thoma, J., Siafis, S., Efthimiou, O., Bermpohl, F., Loncar, L., Neumann, K., Hasan, A., Heinz, A., Leucht, S., et al. (2022) · doi:10.48350/165893 · Cited by 24

Arthroscopic partial meniscectomy vs non-surgical or sham treatment in patients with MRI-confirmed degenerative meniscus tears: a systematic review and meta-analysis with individual participant data from 605 randomised patients

Wijn, S. R. W., Hannink, G., Østerås, H., Risberg, M. A., Roos, E. M., Hare, K. B., van de Graaf, V. A., Poolman, R. W., Ahn, H. W., Seon, J., et al. (2023) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2023.01.002 · Cited by 24

The impact of individual patient data in a network meta‐analysis: An investigation into parameter estimation and model selection

Leahy, J., O’Leary, A. C., Afdhal, N. H., Gray, E., Milligan, S., Wehmeyer, M. H., & Walsh, C. (2018) · Research Synthesis Methods · doi:10.1002/jrsm.1305 · Cited by 24

Best practice for analysis of shared clinical trial data

Hollis, S., Fletcher, C., Lynn, F., Urban, H.-J., Branson, J., Burger, H.-U., Smith, C. T., Sydes, M. R., & Gerlinger, C. (2016) · BMC Medical Research Methodology · doi:10.1186/s12874-016-0170-y · Cited by 22

Subgrouping and TargetEd Exercise pRogrammes for knee and hip OsteoArthritis (STEER OA): a systematic review update and individual participant data meta-analysis protocol

Holden, M. A., Burke, D. L., Runhaar, J., van der Windt, D., Riley, R. D., Dziedzic, K., Legha, A., Evans, A. L., Abbott, J. H., Baker, K., et al. (2017) · BMJ Open · doi:10.1136/bmjopen-2017-018971 · Cited by 22

When does the use of individual patient data in network meta-analysis make a difference? A simulation study

Kanters, S., Karim, M. E., Thorlund, K., Anis, A. H., & Bansback, N. J. (2021) · BMC Medical Research Methodology · doi:10.1186/s12874-020-01198-2 · Cited by 21

Individual participant data systematic reviews with meta-analyses of psychotherapies for borderline personality disorder

Storebø, O. J., Ribeiro, J. P., Kongerslev, M., Stoffers‐Winterling, J., Jørgensen, M. S., Lieb, K., BATEMAN, A. W., Kirubakaran, R., Dérian, N., Karyotaki, E., et al. (2021) · BMJ Open · doi:10.1136/bmjopen-2020-047416 · Cited by 23

Harmonization-Information Trade-Offs for Sharing Individual Participant Data in Biomedicine

Espin, A. T. (2022) · Harvard Data Science Review · doi:10.1162/99608f92.a9717b34 · Cited by 23

Trunk postural control during unstable sitting among individuals with and without low back pain: A systematic review with an individual participant data meta-analysis

Alshehri, M. A., Alzahrani, H. A., van den Hoorn, W., Klyne, D. M., Vette, A. H., Hendershot, B. D., Roberts, B. W. R., Larivière, C., Barbado, D., Vera-García, F. J., et al. (2024) · PLoS ONE · doi:10.1371/journal.pone.0296968 · Cited by 22

A comparison of analytic approaches for individual patient data meta-analyses with binary outcomes

Thomas, D., Platt, R. W., & Benedetti, A. (2017) · BMC Medical Research Methodology · doi:10.1186/s12874-017-0307-7 · Cited by 21

A Procedure and Guidelines for Analyzing Groups of Software Engineering Replications

Santos, A., Vegas, S., Oivo, M., & Juristo, N. (2019) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2019.2935720 · Cited by 23

Comparison of methods that combine multiple randomized trials to estimate heterogeneous treatment effects

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Challenges in Systematic Reviews and Meta-Analyses of Mediation Analyses

Vo, T., & Vansteelandt, S. (2022) · American Journal of Epidemiology · doi:10.1093/aje/kwac028 · Cited by 20

Efficacy of bisphosphonates in specific knee osteoarthritis subpopulations: protocol for an OA Trial Bank systematic review and individual patient data meta-analysis

Deveza, L. A., Bierma‐Zeinstra, S., van Spil, W. E., Oo, W. M., Saragiotto, B. T., Neogi, T., van Middelkoop, M., & Hunter, D. J. (2018) · BMJ Open · doi:10.1136/bmjopen-2018-023889 · Cited by 20

Current trends in the application of causal inference methods to pooled longitudinal non-randomised data: a protocol for a methodological systematic review

Yeboah, E., Mauer, N. S., Hufstedler, H., Carr, S., Matthay, E. C., Maxwell, L., Rahman, S., Debray, T. P. A., de Jong, V. M. T., Campbell, H., et al. (2021) · BMJ Open · doi:10.1136/bmjopen-2021-052969 · Cited by 19

Early Versus Delayed Flow Diversion for Ruptured Intracranial Aneurysms: A Meta-Analysis

Dossani, R. H., Patra, D. P., Kosty, J. A., Jumah, F., Kuybu, O., Mohammed, N., Waqas, M., Riaz, M., & Cuellar, H. (2019) · World Neurosurgery · doi:10.1016/j.wneu.2019.02.044 · Cited by 18

A review of the quantitative effectiveness evidence synthesis methods used in public health intervention guidelines

Smith, E., Cooper, N. J., Sutton, A. J., Abrams, K. R., & Hubbard, S. (2021) · BMC Public Health · doi:10.1186/s12889-021-10162-8 · Cited by 17

Prior distributions for variance parameters in a sparse‐event meta‐analysis of a few small trials

Pateras, K., Nikolakopoulos, S., & Roes, K. C. B. (2020) · Pharmaceutical Statistics · doi:10.1002/pst.2053 · Cited by 17

Prognostic accuracy of clinical markers of postpartum bleeding in predicting maternal mortality or severe morbidity: a WHO individual participant data meta-analysis

Gallos, I. D., Williams, C. R., Price, M. J., Tobı́as, A., Devall, A., Allotey, J., Althabe, F., Cresswell, J. A., Durocher, J., Gülmezoglu, A. M., et al. (2025) · The Lancet · doi:10.1016/s0140-6736(25)01639-3 · Cited by 16

Comparison of surgical and endovascular treatments for fusiform intracranial aneurysms: systematic review and individual patient data meta-analysis

Telles, J. P. M., Solla, D. J. F., Yamaki, V. N., Rabelo, N. N., da Silva, S. A., Caldas, J. G. P., Teixeira, M. J., Rosí, J., & Figueiredo, E. G. (2020) · Neurosurgical Review · doi:10.1007/s10143-020-01440-x · Cited by 16

Using the SOCIO Chatbot for UML Modelling: A Family of Experiments

Ren, R., Castro, J. W., Santos, A., Dieste, Ó., & Acuña, S. T. (2022) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2022.3150720 · Cited by 16

Surgical Revascularization for Pediatric Patients with Sickle Cell Disease and Moyamoya Disease in the Prevention of Ischemic Strokes: A Single-Center Case Series and a Systematic Review

Aguilar‐Salinas, P., Hayward, K., Santos, R., Agarwal, V., Sauvageau, E. A., Hanel, R. A., & Aldana, P. R. (2018) · World Neurosurgery · doi:10.1016/j.wneu.2018.11.157 · Cited by 16

Effects of Nutritional Interventions in Older Adults with Malnutrition or at Risk of Malnutrition on Muscle Strength and Mortality: Results of Pooled Analyses of Individual Participant Data from Nine RCTs

van Zwienen-Pot, J., Reinders, I., de Groot, C. P. G. M., Beck, A. M., Feldblum, I., Jobse, I., Neelemaat, F., de van der Schueren, M. A. E., Shahar, D. R., Smeets, E. T. H. C., et al. (2023) · Nutrients · doi:10.3390/nu15092025 · Cited by 17

Responsiveness of Critically Ill Adults With Multimorbidity to Rehabilitation Interventions: A Patient-Level Meta-Analysis Using Individual Pooled Data From Four Randomized Trials*

Jones, J. R. A., Karahalios, A., Puthucheary, Z., Berry, M. J., Files, D. C., Griffith, D. M., McDonald, L. A., Morris, P. E., Moss, M., Nordon‐Craft, A., et al. (2023) · Critical Care Medicine · doi:10.1097/ccm.0000000000005936 · Cited by 15

Evaluating the performance of propensity score matching based approaches in individual patient data meta-analysis

Johara, F. T., Benedetti, A., Platt, R. W., Menzies, D., Viiklepp, P., Schaaf, H. S., & Chan, E. D. (2021) · BMC Medical Research Methodology · doi:10.1186/s12874-021-01452-1 · Cited by 15

A framework for identifying treatment‐covariate interactions in individual participant data network meta‐analysis

Freeman, S. C., Fisher, D. J., Tierney, J. F., & Carpenter, J. R. (2018) · Research Synthesis Methods · doi:10.1002/jrsm.1300 · Cited by 14

Extending the Environmental influences on Child Health Outcomes (ECHO) Cohort through 2030: Rationale and study protocol

Blackwell, C. K., Cella, D. F., Adair, L. S., Cordero, J. F., Das, S. R., Elliott, A. J., Hipwell, A. E., Jacobson, L. P., Neiderhiser, J. M., Stanford, J. B., et al. (2024) · PLoS ONE · doi:10.1371/journal.pone.0312677 · Cited by 14

Impact of Usability Mechanisms: A Family of Experiments on Efficiency, Effectiveness and User Satisfaction

Ferreira, J. M., Rodríguez, F. D., Santos, A., Dieste, Ó., Acuña, S. T., & Juristo, N. (2022) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2022.3149586 · Cited by 14

Systematic Review Reveals Lack of Causal Methodology Applied to Pooled Longitudinal Observational Infectious Disease Studies

Hufstedler, H., Rahman, S., Danzer, A. M., Goymann, H., de Jong, V. M. T., Campbell, H., Gustafson, P., Debray, T. P. A., Jaenisch, T., Maxwell, L., et al. (2022) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2022.01.008 · Cited by 13

Investigating change across time in prevalence or association: the challenges of cross-study comparative research and possible solutions

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Comparative efficacy and tolerability of new-generation antidepressants for major depressive disorder in children and adolescents: protocol of an individual patient data meta-analysis

Zhou, X., Cipriani, A., Furukawa, T. A., Cuijpers, P. J., Zhang, Y., Hetrick, S. E., Pu, J., Yuan, S., Giovane, C. D., & Xie, P. (2018) · BMJ Open · doi:10.1136/bmjopen-2017-018357 · Cited by 13

Diabetes and the risk of cardiovascular events and all‐cause mortality among older adults: an individual participant data analysis of five prospective studies

Ribero, V. A., Efthimiou, O., Abolhassani, N., Alwan, H., Bauer, D. C., Henrard, S., Christiaens, A., O’Mahony, D., Knol, W., Peters, M. J. L., et al. (2024) · European Journal of Clinical Investigation · doi:10.1111/eci.14340 · Cited by 12

PRIME-IPD SERIES Part 1. The PRIME-IPD tool promoted verification and standardization of study datasets retrieved for IPD meta-analysis

Dewidar, O., Riddle, A. Y., Ghogomu, E. T., Hossain, A., Arora, P., Bhutta, Z. A., Black, R. E., Cousens, S., Gaffey, M. F., Mathew, C. M., et al. (2021) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2021.05.007 · Cited by 13

Agency through hierarchy? A group-based account of increased approval of social hierarchies under conditions of threatened control

Lautenbacher, J. M., & Fritsche, I. (2023) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2023.104500 · Cited by 12

Individual patient data meta-analysis of prophylactic cranial irradiation in locally advanced non-small cell lung cancer

Witlox, W. J. A., Ramaekers, B. L. T., Lacas, B., Pechoux, C. L., Pignon, J., Sun, A. Y., Wang, S., Hu, C., Redman, M. W., van der Noort, V., et al. (2021) · Radiotherapy and Oncology · doi:10.1016/j.radonc.2021.02.002 · Cited by 12

Genetic and geographic influence on phenotypic variation in European sarcoidosis patients

Freitag‐Wolf, S., Schupp, J. C., Frye, B. C., Fischer, A., Anwar, R., Kieszko, R., Mihailović-Vučinić, V., Milanowski, J., Jovanović, D. M., Zissel, G., et al. (2023) · Frontiers in Medicine · doi:10.3389/fmed.2023.1218106 · Cited by 11

How to plan and manage an individual participant data meta‐analysis. An illustrative toolkit

Maxwell, L., Shreedhar, P., Carabalí, M., & Levis, B. (2023) · Research Synthesis Methods · doi:10.1002/jrsm.1670 · Cited by 13

PROspective Meta‐analysis Of Trials of Initial Oxygen in preterm Newborns ( PROMOTION ): Protocol for a systematic review and prospective meta‐analysis with individual participant data on initial oxygen concentration for resuscitation of preterm infants

Sotiropoulos, J. X., Schmölzer, G. M., Oei, J. L., Libesman, S., Hunter, K. E., Williams, J. G., Webster, A. C., Tarnow-Mordi, W. O., Vento, M., Asztalos, E. V., et al. (2022) · Acta Paediatrica · doi:10.1111/apa.16622 · Cited by 11

Smoking Cessation Pharmacotherapy Based on Genetically-Informed Biomarkers: What is the Evidence?

Panagiotou, O. A., Schuit, E., Munafo, M. R., Bennett, D., Bergen, A. W., & David, S. P. (2019) · Nicotine & Tobacco Research · doi:10.1093/ntr/ntz009 · Cited by 11

Interpretation of meta-analyses

Clephas, P. R. D., & Heesen, M. A. (2022) · Interventional Pain Medicine · doi:10.1016/j.inpm.2022.100120 · Cited by 13

Meta-Analysis of 11 Heterogeneous Studies regarding Dipeptidyl Peptidase 4 Inhibitor Add-On Therapy for Type 2 Diabetes Mellitus Patients Treated with Insulin

Shibuki, K., Shimada, S., & Aoyama, T. (2020) · Journal of Diabetes Research · doi:10.1155/2020/6321826 · Cited by 10

Association between proliferative-to-secretory endometrial compaction and pregnancy outcomes after embryo transfer: a systematic review and meta-analysis

Feng, S., Wang, B., Chen, S., Xie, Q., Yu, L., Xiong, C., Wang, S., Huang, Z., Xing, G., Li, K., et al. (2024) · Human Reproduction · doi:10.1093/humrep/deae012 · Cited by 10

The use of one-stage meta-analytic method based on individual participant data for binary adverse events under the rule of three: a simulation study

Cheng, L.-L., Ju, K., Cai, R., & Xu, C. (2019) · PeerJ · doi:10.7717/peerj.6295 · Cited by 10

Deep Brain Stimulation for Chronic Facial Pain: An Individual Participant Data (IPD) Meta-Analysis

Qassim, H., Zhao, Y., Ströbel, A., Regensburger, M., Buchfelder, M., de Oliveira, D. S., Vecchio, A. D., & Kinfe, T. M. (2023) · Brain Sciences · doi:10.3390/brainsci13030492 · Cited by 10

Health professionals’ attitudes toward religiosity and spirituality: a NERSH Data Pool based on 23 surveys from six continents

Kørup, A. K., Søndergaard, J., Alyousefi, N. A., Lucchetti, G., Baumann, K., Lee, E., Karimah, A., Ramakrishnan, P., Frick, E., Büssing, A., et al. (2021) · F1000Research · doi:10.12688/f1000research.52512.1 · Cited by 8

Accuracy of physicians’ intuitive risk estimation in the diagnostic management of pulmonary embolism: an individual patient data meta-analysis

van Maanen, R., Martens, E. S. L., Takada, T., Roy, P., de Wit, K., Parpia, S., Kraaijpoel, N., Huisman, M. V., Wells, P. S., Gal, G. L., et al. (2023) · Journal of Thrombosis and Haemostasis · doi:10.1016/j.jtha.2023.05.023 · Cited by 13

Causally interpretable meta‐analysis: Clearly defined causal effects and two case studies

Rott, K. W., Brønfort, G., Chu, H., Huling, J. D., Leininger, B. D., Murad, M. H., Wang, Z., & Hodges, J. S. (2023) · Research Synthesis Methods · doi:10.1002/jrsm.1671 · Cited by 9

Methods for Integrating Trials and Non-experimental Data to Examine Treatment Effect Heterogeneity

Lupton‐Smith, C., Chang, T.-H., Nguyen, T. Q., Hong, H., Stefano, L. D., & Stuart, E. A. (2023) · Statistical Science · doi:10.1214/23-sts890 · Cited by 18

Placebo response in neuropathic pain after spinal cord injury: a meta-analysis of individual participant data

Jutzeler, C. R., Warner, F. M., Cragg, J. J., Haefeli, J., Richards, S., Andresen, S. R., Finnerup, N. B., Mercier, C., & Kramer, J. (2018) · Journal of Pain Research · doi:10.2147/jpr.s155979 · Cited by 9

Analyzing Families of Experiments in SE: A Systematic Mapping Study

Santos, A., Gómez, O. S., & Juristo, N. (2018) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2018.2864633 · Cited by 10

Predicting the treatment response of certolizumab for individual adult patients with rheumatoid arthritis: protocol for an individual participant data meta-analysis

Luo, Y., Chalkou, K., Yamada, R., Funada, S., Salanti, G., & Furukawa, T. A. (2020) · Systematic Reviews · doi:10.1186/s13643-020-01401-x · Cited by 9

Prediction of Real-World Drug Effectiveness Prelaunch: Case Study in Rheumatoid Arthritis

Didden, E., Ruffieux, Y., Hummel, N., Efthimiou, O., Reichenbach, S., Gsteiger, S., Finckh, A., Fletcher, C., Salanti, G., & Egger, M. (2018) · Medical Decision Making · doi:10.1177/0272989x18775975 · Cited by 8

Effect of antihypertensive drug treatment on long-term blood pressure reduction: An individual patient-level data meta-analysis of 352,744 Participants from 51 large-scale randomised clinical trialsPreprint

The Blood Pressure Lowering Treatment Trialists’ Collaboration (2021) · medRxiv · doi:10.1101/2021.02.19.21252066 · Cited by 9

Individual Participant Data Meta-Analysis: Individual Differences in Mediators of Parenting Program Effects on Disruptive Behavior

Sigurðardóttir, L. B. L., Meléndez‐Torres, G. J., Backhaus, S., Gardner, F. E. M., Scott, S., Bodenmann, G., Canário, C., Döpfner, M., Eisner, M., de Jong, S., et al. (2024) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2024.10.003 · Cited by 8

Individual participant data meta‐analysis of the impact of educational interventions on pupils eligible for Free School Meals

Ashraf, B. H., Singh, A., Uwimpuhwe, G., Higgins, S., & Kasim, A. (2021) · British Educational Research Journal · doi:10.1002/berj.3749 · Cited by 8

Identifying placebo responders and predictors of response in osteoarthritis: a protocol for individual patient data meta-analysis

Fu, Y., Persson, M. S. M., Bhattacharya, A., Goh, S. L., Stocks, J., van Middelkoop, M., Bierma‐Zeinstra, S., Walsh, D. A., Doherty, M., & Zhang, W. (2016) · Systematic Reviews · doi:10.1186/s13643-016-0362-x · Cited by 8

Mindfulness-based programmes for mental health promotion in adults in non-clinical settings: protocol of an individual participant data meta-analysis of randomised controlled trials

Galante, J., Friedrich, C., Dalgleish, T., White, I. R., & Jones, P. B. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-058976 · Cited by 8

Moderators of exercise effects on self-reported cognitive functioning in cancer survivors: an individual participant data meta-analysis

Hiensch, A. E., Beckhaus, J., Witlox, L., Monninkhof, E. M., Schagen, S. B., van Vulpen, J. K., Sweegers, M. G., Newton, R. U., Aaronson, N. K., Galvao, D. A., et al. (2023) · Journal of Cancer Survivorship · doi:10.1007/s11764-023-01392-3 · Cited by 8

Combining evidence from multiple electronic health care databases: performances of one‐stage and two‐stage meta‐analysis in matched case‐control studies

Gamba, F. L., Corrao, G., Romio, S., Sturkenboom, M., Trifirò, G., Schink, T., & de Ridder, M. A. J. (2017) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.4280 · Cited by 8

Measuring the Performance of Survival Models to Personalize Treatment Choices

Efthimiou, O., Hoogland, J., Debray, T. P. A., Ribero, V. A., Knol, W., Koek, H. L., Schwenkglenks, M. M., Henrard, S., Egger, M., Rodondi, N., et al. (2025) · Statistics in Medicine · doi:10.1002/sim.70050 · Cited by 7

Combining individual patient data from randomized and non-randomized studies to predict real-world effectiveness of interventions

Seo, M., Debray, T. P. A., Ruffieux, Y., Gsteiger, S., Bujkiewicz, S., Finckh, A., Egger, M., & Efthimiou, O. (2022) · Statistical Methods in Medical Research · doi:10.1177/09622802221090759 · Cited by 7

Development of minimum reporting sets of patient characteristics in epidemiological research: A methodological systematic review

Vuong, M. L., Tu, P. H. T., Duong, K. L., & Vo, T. (2023) · Research Methods in Medicine & Health Sciences · doi:10.1177/26320843231191777 · Cited by 7

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

Kelley, G. A., & Kelley, K. S. (2016) · BioMed Research International · doi:10.1155/2016/5059041 · Cited by 7

Rational and design of an individual participant data meta-analysis of spinal manipulative therapy for chronic low back pain—a protocol

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