Ten circumstances and solutions for finding the sample mean and standard deviation for meta-analysis

被引:44
作者
Chi, Kuan-Yu [1 ]
Li, Man-Yun [1 ]
Chen, Chiehfeng [2 ,3 ,4 ,5 ]
Kang, Enoch [4 ,5 ,6 ,7 ]
机构
[1] Taipei Med Univ, Coll Med, Sch Med, Taipei, Taiwan
[2] Taipei Med Univ, Coll Med, Sch Med, Dept Publ Hlth, Taipei, Taiwan
[3] Taipei Med Univ, Wan Fang Hosp, Dept Surg, Div Plast Surg, Taipei, Taiwan
[4] Taipei Med Univ, Cochrane Taiwan, 250 Wu Hsing St, Taipei 110, Taiwan
[5] Taipei Med Univ, Wan Fang Hosp, Evidence Based Med Ctr, Taipei, Taiwan
[6] Taipei Med Univ, Wan Fang Hosp, Res Ctr big data & Meta Anal, Taipei, Taiwan
[7] Natl Taiwan Univ, Inst Hlth Policy & Management, Coll Publ Hlth, Taipei, Taiwan
关键词
Data conversion; Data estimation; p value; t value; z score; Interquartile; Range;
D O I
10.1186/s13643-023-02217-1
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
A common problem in meta-analyses is the unavailability of mean and standard deviation (SD). Unfortunately, only having values of the median, interquartile range (IQR), or range cannot be directly utilized for meta-analysis. Although some estimation and conversion methods have been proposed in the past two decades, there were no published and user-friendly tools developed based on multiple scenarios of missing SD. Therefore, this study aimed to provide a collection of possible circumstances of missing sample means or SD with solutions for teaching and research. A total of 10 common circumstances of missing SD or mean could have available statistics of p value, t value, z score, confidence interval, standard error, median, IQR, and range. Teachers and investigators can use relevant formulas for finding the sample mean and SD according to the available circumstance. Due to the complicated computations, our team provides a free available spreadsheet. With ever-evolving statistical methods, some formulas may be further improved in the future; therefore, it is recommended to involve statisticians in evidence-based practice or systematic reviews.
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页数:5
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