Statistical Software Components

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METAFUNNEL: Stata module to produce funnel plots for meta-analysis: Jonathan Sterne
METAGEN: Stata module to perform meta-analysis of genetic-association studies: Pantelis Bagos
METAGRAPH: Stata module to draw Forrest plot after meta command: Adrian Mander
METAMISS2: Stata module accounting for missing outcome data in meta-analysis: Anna Chaimani and Ian White
METAMISS: Stata module to perform meta-analysis with missing data: Ian White and Julian Higgins
METAN: Stata module for fixed and random effects meta-analysis: David Fisher, Ross Harris, Mike Bradburn, Jon Deeks, Roger Harbord, Doug Altman, Thomas Steichen, Jonathan Sterne and Julian Higgins
METANDI: Stata module to perform meta-analysis of diagnostic accuracy: Roger Harbord
METANINF: Stata module to evaluate influence of a single study in meta-analysis estimation: Thomas Steichen
METAPOW: Stata module for simulation based sample size calculations for designing new clinical trials and diagnostic test accuracy studies to update an existing meta-analysis: Michael J. Crowther and Sally R. Hinchliffe
METAPRED: Stata module producing outlier and influence diagnostics for meta-analysis: Ariel Linden
METAPREG: Stata module to compute fixed and random effects meta-analysis and meta-regression of proportions: Victoria Nyaga
METAPROP: Stata module to perform fixed and random effects meta-analysis of proportions: Victoria Nyaga, Marc Arbyn and Marc Aerts
METAPROP_ONE: Stata module to perform fixed and random effects meta-analysis of proportions: Victoria Nyaga, Marc Arbyn and Marc Aerts
METAREG: Stata module to perform meta-analysis regression: Roger Harbord and Julian Higgins
METASTRONG: Stata module for estimating the proportion of true effect sizes above or below a threshold in random-effects meta-analysis: Ariel Linden
METATEF: Stata module to perform IPD meta analysis of an interaction between treatment and a continuous covariate: Patrick Royston
METATREND: Stata module to implement regression methods for detecting trends in cumulative meta-analysis: Pantelis Bagos
METATRIM: Stata module to perform nonparametric analysis of publication bias: Thomas Steichen
MFCURVE: Stata module for plotting results from multifactorial research designs: Daniel Krähmer
MFELOGIT: Stata module to estimate marginal effects (AME) and average treatment effects (ATE) in fixed effect logit models: Laurent Davezies, Xavier D'Haultfoeuille, Christophe Gaillac and Louise Laage
MFILEGR: Stata module to view and save multiple graphs with filenames based on a numeric identifier: Philip Ryan
MFPI: Stata module for modelling and displaying interactions: Patrick Royston
MFPIGEN: Stata module for modelling and displaying interactions between continuous predictors: Patrick Royston
MFPMI: Stata module to build multivariable fractional polynomial models in multiply imputed data: Tim Morris and Patrick Royston
MFX2: Stata module to enhance mfx command for obtaining marginal effects or elasticities after estimation: Richard Williams
MGBE: Stata module to compute Multimodel Generalized Beta Estimator: Yutong Duan and Paul von Hippel
MGEN: Stata module to apply generate to a matrix: Ben Jann
MGOF: Stata module to perform goodness-of-fit tests for multinomial data: Ben Jann
MHEGY: RATS procedure to implement the monthly version of the "HEGY" tests: Tom Doan
MHTEXP: Stata module to perform multiple hypothesis testing correction procedure: Joseph Seidel and Yang Xu
MHTREG: Stata module for multiple hypothesis testing controlling for FWER: Andreas Steinmayr
MI_IMPUTE_FROM: Stata module to impute using an external imputation model: Robert Thiesmeier, Matteo Bottai and Nicola Orsini
MI_IMPUTE_WLOGIT: Stata module to perform weighted multiple imputation for binary/categorical variables: Tra My Pham
MI_MVNCAT: Stata module to assign "final" values to (mvn) imputed categorical variables: Daniel Klein
MI_TWOWAY: Stata module for computing scores on questionnaires containing missing item responses: Jean-François Hamel
MIBMI: Stata module for cleaning and multiple imputation algorithm for body mass index (BMI) in longitudinal datasets: Evangelos Kontopantelis
MICT: Stata module to provide Multiple imputation for Categorical Time-series: Brendan Halpin
MIDAS: Stata module for meta-analytical integration of diagnostic test accuracy studies: Ben Dwamena
MIESIZE: Stata module to estimate effect sizes from multiply imputed data: Paul A Tiffin
MIF2DTA: Stata module convert MapInfo Interchange Format boundary files to Stata boundary files: Maurizio Pisati
MIINC: Stata module to conduct multi-model inference using information criteria: Joseph Luchman
MILDEVGOALS: HTML routine to display Millenium Development Goals indicators: Jochen Jesinghaus
MIM: Stata module to analyse and manipulate multiply imputed datasets: John C. Galati, Patrick Royston and John B. Carlin
MIMIX: Stata module to perform reference based multiple imputation for sensitivity analysis of longitudinal clinical trials with protocol deviation: Suzie Cro
MIMPT: Stata module to impute missing values and persist in case of non-convergence: Daniel Klein
MIMRGNS: Stata module to run margins after mi estimate: Daniel Klein
MIMSTACK: Stata module to stack multiply-imputed datasets into format required by mim: John C. Galati, Patrick Royston and John B. Carlin
MINAP: Stata module to calculate minimum average partial correlation for principal components: Stephen Soldz
MINIMAX: RATS module to estimate a minimax regression: Eric Blankmeyer
MINMSE: Stata module to create balanced groups for treatment in experiments with one or several treatment arms: Sebastian Schneider