Apply SAS Macros to Calculate Statistical Power in Meta-analysis_Chinese Journal of Evidence-Based Medicine

Authors：

 TIANXu ^1,2,3 ,  ZENGZi ³ , MAOZhi ⁴ , ZHOUQuan ⁵ ,  ZENGXian-tao ^1,2 , WANGYan ⁶ , SONGGuo-min ⁷

1. Center for Evidence-Based and Translational Medicine, Zhongnan Hospital, Wuhan University, Wuhan 430071, China;
2. Center for Evidence-Based and Translational Medicine, Wuhan University, Wuhan 430071, China;
3. Graduate College, T_ianjin University of Traditional Chinese Medicine, T_ianjin 300193, China;
4. Department of Orthopedics, General Hospital of PLA, Beijing 100853, China;
5. Department of Science and Education, First People's Hospital of Changde, Changde 415003, China;
6. School of Nursing, T_ianjin University of Traditional Chinese Medicine, T_ianjin 300193, China;
7. Department of Nursing, T_ianjin Hospital, T_ianjin 300211, China;

Corresponding?author：

ZENGXian-tao, Email: zengxiantao1128@163.com

Keywords：

Power analysis; Meta-analysis; SAS; Macro

DOI：

10.7507/1672-2531.20150019

Video：

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The SAS is considered as internationally-known standard software in the field of data processing and statistics, which is also excellent in conducting meta-analysis; however, it require users to have higher technical expertise due to its complex and difficult program coding. Assessing statistical power calculation of significance tests is one of important steps in meta-analysis. Guy Cafri et al., developed a macro (%metapower) for well implement this calculation in SAS. This macro is specifically designed to implement the statistical power calculation of overall results of meta-analysis, heterogenity, and subgroup analysis, which is easy to operate. This article introduces%metapower based on examples.

Citation： TIANXu, ZENGZi, MAOZhi, ZHOUQuan, ZENGXian-tao, WANGYan, SONGGuo-min. Apply SAS Macros to Calculate Statistical Power in Meta-analysis. Chinese Journal of Evidence-Based Medicine, 2015, 15(1): 110-115. doi: 10.7507/1672-2531.20150019 Copy

1.	羅杰, 冷衛東, 主編. 系統評價/Meta分析理論與實踐. 北京:軍事醫學科學出版社, 2013:1-5.
2.	Hedges LV, Pigott TD. The Power of Statistical Tests in Meta-Analysis. Psychol Methods, 2001, 6(3):203-217.
3.	Cohen J. Statistical power analysis for the behavioral sciences. Hillsdale, NJ:Lawrence Erlbaum, 1988.
4.	Steven M, Shirley T, Mark C. Power dressing and meta-analysis:incorporating power analysis into meta-analysis. J Adv Nurs, 2002, 38(3):274-80.
5.	Hedges LV, Pigott TD. The Power of Statistical Tests for Moderators in Meta-Analysis. Psychol Methods, 2004, 9(4):426-445.
6.	Cafri G, Kromrey JD, Brannick MT. A SAS macro for statistical power calculations in meta-analysis. Behav Res Methods, 2009, 41(1):35-46.
7.	Mizuguchi T, Kawamoto M, Meguro M, et al. Laparoscopic Hepatectomy:A Systematic Review, Meta-Analysis, and Power Analysi. Surg Today, 2011, 41(1):39-47.
8.	Jia ZW, Chen C, Wu YH, et al. No difference in clinical outcomes after total knee arthroplasty between patellar eversion and non-eversion. Knee Surg Sport Tr A, doi:10.1007/s00167-014-3351-4.
9.	Yakoob MY, Bateman BT, Ho E, et al. The risk of congenital malformations associated with exposure to β-blockers early in pregnancy:a meta-analysis. Hypertension, 2013, 62(2):375-381.
10.	鄢金柱, 李勝, 翁鴻, 等. 應用SAS軟件宏命令實現二分類數據的Meta分析. 中國循證心血管醫學雜志, 2014, 4(6):121-124.
11.	羅美玲, 林希建, 劉如春, 等. 劑量反應關系meta分析在S^TATA軟件中的實現. 循證醫學, 2014, 14(3):812-187.
12.	Egger M, Smith GD. Misleading meta-analysis. BMJ, 1995, 311(7007):753-754.
13.	Egger M, Davey-Smith G, Schneider M, et al. Bias in meta-analysis detected by a simple, graphical test. BMJ, 1997, 315(7109):629-634.
14.	Feinstein AR. Meta-analysis:statistical alchemy for the 21st century. J Clin Epidemiol, 1995, 48(1):71-79.
15.	Erdfelder E, Faul F, Buchner A. GPOWER:a general power analysis program. Behav Res Methods, 1996, 28(1):1-11.
16.	Kraemer HC, Gardner C, Brooks J, et al. Advantages of excluding underpowered studies in meta-analysis:Inclusionist versus exclusionist viewpoints. Psychol Methods, 1998, 3(1):23-31.
17.	鄢金柱, 翁鴻, 冷衛東, 等. 診斷準確性試驗Meta分析分層受試者工作特征曲線的SAS實現. 湖北醫藥學院學報, 2014, 33(4):365-369.
18.	鄢金柱, 吳平勇, 張超, 等. 應用SAS軟件PROC MCMC過程實現網狀Meta分析. 中國循證醫學雜志, 2014, 14(8):1004-1008.
19.	Naylor CD. Meta-analysis and the meta-epidemiology of clinical research:meta-analysis is an important contribution to research and practice but it's not a panacea. BMJ, 1997, 315(7109):617-619.
20.	Takwoingi Y, Hopewell S, Tovey D, et al. A multicomponent decision tool for prioritising the updating of systematic reviews. BMJ, 2013, 347:f7191.
21.	Muncer SJ. Power dressing is important in meta-analysis. BMJ, 1999, 318(7187):870-871.
22.	Polit D, Sherman R. Statistical power in nursing research. Nurs Res, 1990, 39(6):365-369.

1. 羅杰, 冷衛東, 主編. 系統評價/Meta分析理論與實踐. 北京:軍事醫學科學出版社, 2013:1-5.
2. Hedges LV, Pigott TD. The Power of Statistical Tests in Meta-Analysis. Psychol Methods, 2001, 6(3):203-217.
3. Cohen J. Statistical power analysis for the behavioral sciences. Hillsdale, NJ:Lawrence Erlbaum, 1988.
4. Steven M, Shirley T, Mark C. Power dressing and meta-analysis:incorporating power analysis into meta-analysis. J Adv Nurs, 2002, 38(3):274-80.
5. Hedges LV, Pigott TD. The Power of Statistical Tests for Moderators in Meta-Analysis. Psychol Methods, 2004, 9(4):426-445.
6. Cafri G, Kromrey JD, Brannick MT. A SAS macro for statistical power calculations in meta-analysis. Behav Res Methods, 2009, 41(1):35-46.
7. Mizuguchi T, Kawamoto M, Meguro M, et al. Laparoscopic Hepatectomy:A Systematic Review, Meta-Analysis, and Power Analysi. Surg Today, 2011, 41(1):39-47.
8. Jia ZW, Chen C, Wu YH, et al. No difference in clinical outcomes after total knee arthroplasty between patellar eversion and non-eversion. Knee Surg Sport Tr A, doi:10.1007/s00167-014-3351-4.
9. Yakoob MY, Bateman BT, Ho E, et al. The risk of congenital malformations associated with exposure to β-blockers early in pregnancy:a meta-analysis. Hypertension, 2013, 62(2):375-381.
10. 鄢金柱, 李勝, 翁鴻, 等. 應用SAS軟件宏命令實現二分類數據的Meta分析. 中國循證心血管醫學雜志, 2014, 4(6):121-124.
11. 羅美玲, 林希建, 劉如春, 等. 劑量反應關系meta分析在S^TATA軟件中的實現. 循證醫學, 2014, 14(3):812-187.
12. Egger M, Smith GD. Misleading meta-analysis. BMJ, 1995, 311(7007):753-754.
13. Egger M, Davey-Smith G, Schneider M, et al. Bias in meta-analysis detected by a simple, graphical test. BMJ, 1997, 315(7109):629-634.
14. Feinstein AR. Meta-analysis:statistical alchemy for the 21st century. J Clin Epidemiol, 1995, 48(1):71-79.
15. Erdfelder E, Faul F, Buchner A. GPOWER:a general power analysis program. Behav Res Methods, 1996, 28(1):1-11.
16. Kraemer HC, Gardner C, Brooks J, et al. Advantages of excluding underpowered studies in meta-analysis:Inclusionist versus exclusionist viewpoints. Psychol Methods, 1998, 3(1):23-31.
17. 鄢金柱, 翁鴻, 冷衛東, 等. 診斷準確性試驗Meta分析分層受試者工作特征曲線的SAS實現. 湖北醫藥學院學報, 2014, 33(4):365-369.
18. 鄢金柱, 吳平勇, 張超, 等. 應用SAS軟件PROC MCMC過程實現網狀Meta分析. 中國循證醫學雜志, 2014, 14(8):1004-1008.
19. Naylor CD. Meta-analysis and the meta-epidemiology of clinical research:meta-analysis is an important contribution to research and practice but it's not a panacea. BMJ, 1997, 315(7109):617-619.
20. Takwoingi Y, Hopewell S, Tovey D, et al. A multicomponent decision tool for prioritising the updating of systematic reviews. BMJ, 2013, 347:f7191.
21. Muncer SJ. Power dressing is important in meta-analysis. BMJ, 1999, 318(7187):870-871.
22. Polit D, Sherman R. Statistical power in nursing research. Nurs Res, 1990, 39(6):365-369.

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