Metandi: Meta-analysis of Diagnostic Accuracy Using Hierarchical Logistic Regression

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.

[1]  David J Samson,et al.  Challenges in Systematic Reviews of Diagnostic Technologies , 2005, Annals of Internal Medicine.

[2]  L E Moses,et al.  Combining independent studies of a diagnostic test into a summary ROC curve: data-analytic approaches and some additional considerations. , 1993, Statistics in medicine.

[3]  J. Douglas,et al.  Confidence Regions for Parameter Pairs , 1993 .

[4]  J. C. Houwelingen,et al.  Bivariate Random Effects Meta-Analysis of ROC Curves , 2008, Medical decision making : an international journal of the Society for Medical Decision Making.

[5]  C M Rutter,et al.  A hierarchical regression approach to meta‐analysis of diagnostic test accuracy evaluations , 2001, Statistics in medicine.

[6]  S. Rabe-Hesketh,et al.  Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects , 2005 .

[7]  C. Gatsonis,et al.  Meta-analysis of diagnostic and screening test accuracy evaluations: methodologic primer. , 2006, AJR. American journal of roentgenology.

[8]  Victor M Montori,et al.  Conducting systematic reviews of diagnostic studies: didactic guidelines , 2002, BMC medical research methodology.

[9]  Haitao Chu,et al.  A unification of models for meta-analysis of diagnostic accuracy studies. , 2009, Biostatistics.

[10]  M R Segal,et al.  Radiological evaluation of lymph node metastases in patients with cervical cancer. A meta-analysis. , 1997, JAMA.

[11]  Steve Halligan,et al.  Systematic reviews of diagnostic tests in cancer: review of methods and reporting , 2006, BMJ : British Medical Journal.

[12]  D. Cox,et al.  Analysis of Binary Data (2nd ed.). , 1990 .

[13]  Petra Macaskill,et al.  Empirical Bayes estimates generated in a hierarchical summary ROC analysis agreed closely with those of a full Bayesian analysis. , 2004, Journal of clinical epidemiology.

[14]  Bruce D. Spencer,et al.  The Delta Method , 1980 .

[15]  Patrick M M Bossuyt,et al.  Exploring sources of heterogeneity in systematic reviews of diagnostic tests , 2002, Statistics in medicine.

[16]  Johannes B Reitsma,et al.  Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. , 2005, Journal of clinical epidemiology.

[17]  Christian Gluud,et al.  Evidence based diagnostics , 2005, BMJ : British Medical Journal.

[18]  S. Walter,et al.  Properties of the summary receiver operating characteristic (SROC) curve for diagnostic test data , 2002, Statistics in medicine.

[19]  Haitao Chu,et al.  Bivariate meta-analysis of sensitivity and specificity with sparse data: a generalized linear mixed model approach. , 2006, Journal of clinical epidemiology.

[20]  Patrick M Bossuyt,et al.  We should not pool diagnostic likelihood ratios in systematic reviews , 2008, Statistics in medicine.

[21]  Jonathan J Deeks,et al.  Systematic reviews in health care: Systematic reviews of evaluations of diagnostic and screening tests. , 2001, BMJ.

[22]  Jonathan J Deeks,et al.  metan-an alternative meta-analysis command , 1999 .

[23]  Victor Chew,et al.  Confidence, Prediction, and Tolerance Regions for the Multivariate Normal Distribution , 1966 .

[24]  Richard D Riley,et al.  Beyond the Bench: Hunting Down Fugitive Literature , 2004, Environmental Health Perspectives.

[25]  L. Corrado.  Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models , 2005 .

[26]  D. Cox,et al.  The analysis of binary data , 1971 .

[27]  Anders Alexandersson,et al.  Graphing Confidence Ellipses: An Update of Ellip for Stata 8 , 2004 .