STATA-只有OR值的meta分析方法.ppt

1、Meta-analysis in Stata,柏建岭,南京医科大学公共卫生学院流统系,STATA简介,由美国计算机资源中心（Computer Resource Center）研制； 现在为Stata公司的产品； 目前最高版本9.0； 与SAS、SPSS一起并称为三大权威统计软件。 操作灵活、简单、易学易用，同时具有数据管理软件、统计分析软件、绘图软件、矩阵计算软件和程序语言的特点 。,STATA的进入和退出,进入：双击STATA软件图标 退出：菜单方式: FileExit 窗口方式 命令方式:exit,STATA的用户界面,命令回顾,变量列表,结果输出,STATA数据管理,数据的输入与储存 数

2、据库的排序 删除变量或记录 保留变量或记录 产生新变量 替换已存在的变量值,数据的输入与存储,数据输入 数据编辑窗口； 复制和粘贴。 数据储存 save命令 FileSave As,数据编辑窗口,使用数据编辑窗口输入,数据库的排序,sort 变量名1 变量名2 gsort +/- 变量清单 sort x 对变量x中数值从小到大进行排列 gsort x 对变量x中数值从小到大进行排列 gsort -x 对变量x中数值从大到小进行排列,删除（或保留）变量或记录,删除变量或记录 drop varlist drop if exp drop in range 保留变量或记录 keep varlist k

3、eep if exp keep in range if exp,删除变量或记录,drop x1 x2 /* 删除变量x1和x2 drop x1-x3 /* 删除数据库中介于x1和x3间的所 有变量 (包括x1和x3) drop if x0 /* 删去x0的所有记录 drop in 1/3 /* 删去第13个记录 drop if x=. /* 删去x为缺失值的所有记录 drop if x=.|y=. /* 删去x或y之一为缺失值的所有记录 drop if x=.&y=. /* 删去x和y同时为缺失值的所有记录 drop _all /* 删掉数据库中所有变量和数据,保留变量或记录,keep in

4、1/5 /* 保留第15个记录，其余记录删除 keep x1-x3 /* 保留数据库中介于x1和x3间的所有变量 (包括x1和x3)，其余变量删除 keep if x0 /* 保留x0的所有记录，其余记录删除,用generate产生新变量,generate 新变量表达式 gen yx+1 /*产生新变量y，其值为x+1。 gen y=log(x) if x0 /* 产生新变量y，其值为所有x0的对数log(x)，当x=0时，用缺失值代替。,替换已存在的变量值,replace 变量表达式 replace bolck=6 if block=0 /* 将block0的数全部替换为6。 replace

5、 z=. if z0 /* 将所有小于0的z值用缺失值代替。 replace age = 25 in 2 /* 将第2条记录中的变量age替换为25。,Fixed and random effects meta-analysis,metan varlist if exp in range , rr or rd fixed random fixedi randomi peto by(byvar) label(namevar=name, yearvar=year) rr pools risk ratios default or pools odds ratios rd pools risk dif

6、ferences fixed specifies a fixed effect model random specifies a random effects model,The following new variables to the data set,_ES Effect size (ES) _seES Standard error of ES or, when OR or RR are specfied: _selogES the standard error of its logarithm _LCI Lower confidence limit for ES _UCI Upper

7、 confidence limit for ES _WT Study percentage weight _SS Study sample size,Example 1,Stata result,metan casec casea controlc controla if country=European,or label(namevar=study) metan a b c d,or label(namevar=study) Study | OR 95% Conf. Interval % Weight -+- Misra RR | 1.060 0.658 1.707 14.60 Hou SM

8、 | 1.111 0.606 2.036 8.85 Zhou W | 1.166 0.907 1.498 50.23 Spitz MR | 1.359 0.840 2.199 12.68 David-Beabes GL1 | 1.724 1.039 2.859 9.72 David-beabes GL2 | 1.392 0.595 3.258 3.92 -+- M-H pooled OR | 1.233 1.035 1.469 100.00 -+- Heterogeneity chi-squared = 2.61 (d.f. = 5) p = 0.760 I-squared (variatio

9、n in OR attributable to heterogeneity) = 0.0% Test of OR=1 : z= 2.34 p = 0.019,Forest plot,Stata result,metan casec casea controlc controla if country=Asian,or label(namevar=study) Study | OR 95% Conf. Interval % Weight -+- Ling G | 2.358 0.902 6.166 25.55 Chen S | 0.442 0.190 1.027 71.85 Park JY |

10、1.980 0.080 48.927 2.60 -+- M-H pooled OR | 0.972 0.544 1.737 100.00 -+- Heterogeneity chi-squared = 6.81 (d.f. = 2) p = 0.033 I-squared (variation in OR attributable to heterogeneity) = 70.6% Test of OR=1 : z= 0.10 p = 0.923,Stata result,metan casec casea controlc controla if country=Asian,or label

11、(namevar=study) random Study | OR 95% Conf. Interval % Weight -+- Ling G | 2.358 0.902 6.166 42.15 Chen S | 0.442 0.190 1.027 44.27 Park JY | 1.980 0.080 48.927 13.57 -+- D+L pooled OR | 1.097 0.279 4.316 100.00 -+- Heterogeneity chi-squared = 6.81 (d.f. = 2) p = 0.033 I-squared (variation in OR att

12、ributable to heterogeneity) = 70.6% Estimate of between-study variance Tau-squared = 0.9175 Test of OR=1 : z= 0.13 p = 0.894,Forest plot,Stata result,metan casec casea controlc controla ,or by(country) label(namevar=study) Study | OR 95% Conf. Interval % Weight -+- Asian Ling G | 2.358 0.902 6.166 2

13、.38 Chen S | 0.442 0.190 1.027 6.69 Park JY | 1.980 0.080 48.927 0.24 Sub-total M-H pooled OR | 0.972 0.544 1.737 9.32 -+- European Misra RR | 1.060 0.658 1.707 13.24 Hou SM | 1.111 0.606 2.036 8.02 Zhou W | 1.166 0.907 1.498 45.55 Spitz MR | 1.359 0.840 2.199 11.50 David-Beabes GL1 | 1.724 1.039 2.

14、859 8.81 David-beabes GL2 | 1.392 0.595 3.258 3.56 Sub-total M-H pooled OR | 1.233 1.035 1.469 90.68 -+- Overall M-H pooled OR | 1.209 1.022 1.430 100.00 -+- Test(s) of heterogeneity: Heterogeneity degrees of statistic freedom P I-squared* Asian 6.81 2 0.033 70.6% European 2.61 5 0.760 0.0% Overall

15、10.09 8 0.259 20.7% Overall Test for heterogeneity between sub-groups : 0.67 1 0.415 * I-squared: the variation in OR attributable to heterogeneity) Significance test(s) of OR=1 Asian z= 0.10 p = 0.923 European z= 2.34 p = 0.019 Overall z= 2.21 p = 0.027 -,Forest plot,Example 2,Stata result,metan n1

16、 mean1 sd1 n2 mean2 sd2 Study | SMD 95% Conf. Interval % Weight -+- 1 | -0.329 -0.820 0.162 15.34 2 | -0.677 -1.178 -0.176 14.74 3 | -0.357 -0.855 0.141 14.91 4 | -0.658 -1.162 -0.154 14.57 5 | -0.305 -0.806 0.196 14.73 6 | -0.408 -0.787 -0.029 25.71 -+- I-V pooled SMD | -0.449 -0.642 -0.257 100.00

17、-+- Heterogeneity chi-squared = 2.18 (d.f. = 5) p = 0.824 I-squared (variation in SMD attributable to heterogeneity) = 0.0% Test of SMD=0 : z= 4.58 p = 0.000,Forest plot,Tests for publication bias in meta-analysis,metabias theta se_theta , by(by_var) graph(begg),Stata result,gen logor=log(_ES) gen s

18、elogor= _selogES metabias logor selogor, graph(begg) Note: default data input format (theta, se_theta) assumed. Tests for Publication Bias Beggs Test adj. Kendalls Score (P-Q) = 6 Std. Dev. of Score = 9.59 Number of Studies = 9 z = 0.63 Pr |z| = 0.532 z = 0.52 (continuity corrected) Pr |z| = 0.602 (continuity corrected) Eggers test - Std_Eff | Coef. Std. Err. t P|t| 95% Conf. Interval -+- slope |.1546435 .2095145 0.74 0.484 -.3407797 .6500667 bias |.1631062 .8120607 0.20 0.847 -1.757112 2.083325 -,Lung cancer2005年第