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Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range
Open accessAbstract
The era of big data is coming, and evidence-based medicine is attracting increasing attention to improve decision making in medical practice via integrating evidence from well designed and conducted clinical research. Meta-analysis is a statistical technique widely used in evidence-based medicine for analytically combining the findings from independent clinical trials to provide an overall estimation of a treatment effectiveness. The sample mean and standard deviation are two commonly used statistics in meta-analysis but some trials use the median, the minimum and maximum values, or sometimes the first and third quartiles to report the results. Thus, to pool results in a consistent format, researchers need to transform those information back to the sample mean and standard deviation. In this article, we investigate the optimal estimation of the sample mean for meta-analysis from both theoretical and empirical perspectives. A major drawback in the literature is that the sample size, needless to say its importance, is either ignored or used in a stepwise but somewhat arbitrary manner, e.g. the famous method proposed by Hozo et al. We solve this issue by incorporating the sample size in a smoothly changing weight in the estimators to reach the optimal estimation. Our proposed estimators not only improve the existing ones significantly but also share the same virtue of the simplicity. The real data application indicates that our proposed estimators are capable to serve as "rules of thumb" and will be widely applied in evidence-based medicine.
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“When studies reported a median and interquartile range, we estimated the mean and standard deviation (SD) using conventional formulae (Luo et al., 2018;Wan et al., 2014).When both of these were absent, we estimated the standard deviation using prognostic imputation (Ma et al., 2008).”
From Decision making capacity for treatment in psychiatric inpatients: a systematic review and meta-analysis (2024) · cites this paper as Luo et al., 2018
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MethodThong, D., Halim, Z., Chia, J., Chua, F., & Wong, A. (2021) · Journal of Parenteral and Enteral Nutrition · doi:10.1002/jpen.2324 · Cited by 28
Comparison of Different Anti-Demodex Strategies: A Systematic Review and Meta-Analysis
Li, J., Wei, E., Reisinger, A., French, L. E., Clanner-Engelshofen, B. M., & Reinholz, M. (2022) · Dermatology · doi:10.1159/000526296 · Cited by 28
Jayedi, A., Zeraattalab-Motlagh, S., Shahinfar, H., Gregg, E. W., & Shab‐Bidar, S. (2023) · American Journal of Clinical Nutrition · doi:10.1016/j.ajcnut.2023.03.018 · Cited by 35
Aliseda, D., Sapisochín, G., Martí‐Cruchaga, P., Zozaya, G., Blanco, N., Goh, B. K. P., & Rotellar, F. (2023) · Annals of Surgical Oncology · doi:10.1245/s10434-023-13498-0 · Cited by 28
Tsakos, E., Xydias, E. M., Ziogas, A. C., Sorrentino, F., Nappi, L., Vlachos, N., & Daniilidis, A. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12124134 · Cited by 32
Machado, M. F., Felix, N. S., Melo, P., Gauza, M. D. M., Calomeni, P. A.-K. B., Generoso, G., Khatri, S., Altmayer, S., Blankstein, R., Bittencourt, M. S., et al. (2023) · Circulation Cardiovascular Imaging · doi:10.1161/circimaging.123.015800 · Cited by 30
Hughes, S. M., Levy, C., Katz, R., Lokken, E. M., Anahtar, M. N., Hall, M. B., Bradley, F., Castle, P. E., Cortez, V. A., Doncel, G. F., et al. (2022) · BMC Medicine · doi:10.1186/s12916-022-02532-9 · Cited by 27
Jensen, C. F. (2022) · Nutrition Reviews · doi:10.1093/nutrit/nuac096 · Cited by 27
Quantitative impact of frenotomy on breastfeeding: a systematic review and meta-analysis
Cordray, H., Raol, N., Mahendran, G. N., Tey, C. S., Nemeth, J. K., Sutcliffe, A. G., Ingram, J. C., & Sharp, W. G. (2023) · Pediatric Research · doi:10.1038/s41390-023-02784-y · Cited by 30
“For studies that reported summary statistics as median (IQR), the Luo 32 and Shi 33 derivation methods were used to estimate the mean (SD).”
Panunzio, A., Labate, C., Zacheo, F., Orlando, R., Rizzo, F. L., Porcaro, A. B., Migliorini, F., Pagliarulo, V., & Tafuri, A. (2023) · International Journal of Impotence Research · doi:10.1038/s41443-023-00798-y · Cited by 28
Czyż, S. H., Wójcik, A. M., Solarská, P., & Kiper, P. (2024) · Scientific Reports · doi:10.1038/s41598-024-65753-3 · Cited by 38
“If SEM (standard error of the mean) was available, we converted it into SD. Similarly, if quartiles were available, we converted these with Mean Variance calculator 30–33 .”
MethodDereje, D., Abessa, T. G., Lamba, D., Triccas, L. T., & Bonnechère, B. (2025) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-025-01603-1 · Cited by 34
“If the median and range were reported instead of the mean and standard deviation, these values were estimated using the methods developed by Luo et al. and Wan et al. [41, 43].”
Cai, B., Luo, X., Zhang, P., Luan, Y., Cai, X., & He, X. (2021) · Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2021.06.013 · Cited by 27
Gravier, F., Smondack, P., Boujibar, F., Prieur, G., Médrinal, C., Combret, Y., Muir, J., Baste, J. M., Cuvelier, A., Debeaumont, D., et al. (2021) · Journal of physiotherapy · doi:10.1016/j.jphys.2021.12.010 · Cited by 27
Kow, C. S., Lee, L., Ramachandram, D. S., Hasan, S. S., Ming, L. C., & Goh, H. P. (2021) · Immunity Inflammation and Disease · doi:10.1002/iid3.562 · Cited by 27
“When the duration of hospital stay was not reported in mean and standard deviation, we first estimated the skewness of the data distribution using median and interquartile range with the method developed by Shi et al.8; if the distribution of data was significantly skewed from normality, the trial was excluded for ana…”
MethodRademacher, J., Glaubitz, S., Zechel, S., Oettler, M., Tampe, B., Schmidt, J., & Korsten, P. (2022) · Clinical and Experimental Rheumatology · doi:10.55563/clinexprheumatol/2ao5ze · Cited by 27
Outcomes of enhanced recovery after surgery in lung cancer: A systematic review and meta-analysis
Zhang, W., Zhang, Y., Qin, Y., & Shi, J. (2022) · Asia-Pacific Journal of Oncology Nursing · doi:10.1016/j.apjon.2022.100110 · Cited by 27
Sarcopenic obesity and therapeutic outcomes in gastrointestinal surgical oncology: A meta-analysis
Wang, P., Wang, S., Ma, Y., Li, H., Liu, Z., Lin, G., Li, X., Yang, F., & Qiu, M. (2022) · Frontiers in Nutrition · doi:10.3389/fnut.2022.921817 · Cited by 29
The Status of Oxidative Stress in Patients with Alcohol Dependence: A Meta-Analysis
Yang, M., Zhou, X., Tan, X., Huang, X., Lu, Y., Zhang, Z., Yang, Y., Xu, M., Wan, Y., & Li, Z. (2022) · Antioxidants · doi:10.3390/antiox11101919 · Cited by 29
Fu, Y., Qiu, J., Yu, Y., Wu, D., & Zhang, T. (2022) · Frontiers in Surgery · doi:10.3389/fsurg.2022.989065 · Cited by 27
“The inclusion criteria were as followed: (1) comparative study of RPD and OPD; (2) papers written in English; (3) papers published in or after 2016.”
BackgroundClinical Indicators for Asthma-COPD Overlap: A Systematic Review and Meta-Analysis
Peng, J., Wang, M., Wu, Y., Shen, Y., & Chen, L. (2022) · International Journal of COPD · doi:10.2147/copd.s374079 · Cited by 27
“…were offered only in a study, we converted the data into approximate means with standard deviations (SDs) according to the validated statistical method, 13,14 and if there were two or more subgroups in a study, we calculated the combined means and SDs according to the Cochrane Handbook guidelines.”
Liang, S., Mijatovic, J., Li, A., Koemel, N. A., Nasir, R., Toniutti, C., Bell-Anderson, K. S., Skilton, M. R., & O’Leary, F. (2022) · Nutrients · doi:10.3390/nu15010076 · Cited by 28
Steinkamp, M. P., Lagutina, I. V., Brayer, K. J., Schultz, F. A., Burke, D., Pankratz, V. S., Adams, S. F., Hudson, L. G., Ness, S. A., & Wandinger‐Ness, A. (2023) · Cancer Research Communications · doi:10.1158/2767-9764.crc-22-0300 · Cited by 27
“For uniformity, average and SEM for MDC levels were estimated from the listed median and interquartile range using an online estimator (31).”
Tian, Y., Ran, H., Wen, X., Fu, G., Zhou, X., Liu, R., & Pan, T. (2023) · Frontiers in Nutrition · doi:10.3389/fnut.2023.1179432 · Cited by 27
Luan, J., Wu, M., Wang, X., Qiao, L., Guo, G., & Zhang, C. (2020) · Radiation Oncology · doi:10.1186/s13014-020-01643-y · Cited by 27
Metadata
- Authors
- Luo, D., Wan, X., Liu, J., & Tong, T.
- Affiliations
- Hong Kong Baptist University (HK)
- Corresponding author
- Wan, Xiang
- Venue
- Statistical Methods in Medical Research
- Publisher
- SAGE Publications
- Published
- 2016-09-27
- Volume
- 27
- Issue
- 6
- Pages
- 1785-1805
- ISSN
- 0962-2802 (ISSN-L)
- 1477-0334
- OpenAlex
- W1534181333
- Cited by
- 4,066
- References
- 21
- Citations by year
- 2026: 789 · 2025: 833 · 2024: 700 · 2023: 601 · 2022: 462 · 2021: 379 · 2020: 188 · 2019: 91 · 2018: 20 · 2017: 1
- FWCI
- 34.66
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Statistical Methods in Medical Research (publishedVersion)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Hong Kong Baptist University (FRG2/14-15/077, FRG1/14-15/084, FRG2/15-16/019)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- sample mean estimation, meta-analysis, median, sample size, standard deviation estimation, optimal estimators, evidence-based medicine
- MeSH terms
- Algorithms, Sampling Studies, Meta-Analysis as Topic, Sample Size, Evidence-Based Medicine
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