metandi: Meta-analysis of diagnostic accuracy using hierarchical logistic regression

被引:342
作者
Harbord, Roger M. [1 ]
Whiting, Penny [1 ]
机构
[1] Univ Bristol, Dept Social Med, Bristol, Avon, England
关键词
st0163; metandi; metandiplot; diagnosis; meta-analysis; sensitivity and specificity; hierarchical models; generalized mixed models; gllamm; xtmelogit; receiver operating characteristic (ROC); summary ROC; hierarchical summary ROC; SYSTEMATIC REVIEWS; SPECIFICITY; SENSITIVITY; REGIONS; CANCER; MODELS; CURVE; TESTS;
D O I
10.1177/1536867X0900900203
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
Meta-analysis of diagnostic test accuracy presents many challenges. Even in the simplest case, when the data are summarized by a 2 x 2 table from each study, a statistically rigorous analysis requires hierarchical (multilevel) models that respect the binomial data structure, such as hierarchical logistic regression. We present a Stata package, metandi, to facilitate the fitting of such models in Stata. The commands display the results in two alternative parameterizations and produce a customizable plot. metandi requires either Stata 10 or above (which has the new command xtmelogit), or Stata 8.2 or above with gllamm installed.
引用
收藏
页码:211 / 229
页数:19
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