English, Article, Journal or magazine article edition: Meta-analytical Integration of Diagnostic Accuracy Studies in Stata Ben Dwamena

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Bookmark: http://trove.nla.gov.au/version/176113
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Meta-analytical Integration of Diagnostic Accuracy Studies in Stata
Author
  • Ben Dwamena
Physical Description
  • preprint
Notes
  • This presentation will demonstrate how to perform diagnostic meta-analysis using user-written macros midas and xtmidas for Stata versions 9 and 10 respectively. Both midas and xtmidas are comprehensive programs of statistical and graphical routines for undertaking meta-analysis of diagnostic test performance in Stata. Primary data synthesis is performed within the bivariate generalized linear mixed modeling framework (binomial likelihood and logit link). Model estimation is by adaptive gaussian quadrature using gllamm and xtmelogit for midas and xtmidas respectively. The estimated coefficients and variance–covariance matrices are used to calculate the summary operating sensitivity and specificity (with confidence and prediction ellipses) in SROC space. Summary likelihood and odds ratios with relevant heterogeneity statistics are provided. midas and xtmidas facilitate statistical and graphical data synthesis and exploratory analyses of unobserved heterogeneity, covariate effects, publication bias, and subgroup analyses. Bayes’ nomograms, likelihood-ratio matrices, and conditional probability plots may be obtained and used to guide clinical decision making.
  • RePEc:boc:wsug07:1
  • This presentation will demonstrate how to perform diagnostic meta-analysis using midas , a user-written macro. midas is is comprehensive program of statistical and graphical routines for undertaking meta-analysis of diagnostic test performance in Stata. Primary data synthesis is performed within the bivariate generalized linear mixed modeling framework. Model specification, estimation and prediction are carried out with gllamm (Rabe-Hesketh et.al, spherical adaptive quadrature). Using the estimated coefficients and variance-covariance matrices, midas calculates the summary operating sensitivity and specificity (with confidence and prediction ellipses) in SROC space. Summary likelihood and odds ratios with relevant heterogeneity statistics are provided. midas facilitates extensive statistical and graphical data synthesis and exploratory analyses of unobserved heterogeneity, covariate effects, publication bias and subgroup analyses. Bayes' nomograms, likelihood ratio matrices and conditional probability plots may be obtained and used to guide clinical decision-making.
  • RePEc:boc:asug07:4
Language
  • English
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