Statistical Software Components

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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
MINT: Stata module to examine across-groups equivalence of confirmatory factor analysis (CFA) measurement model parameters: Mehmet Mehmetoglu
MIPARALLEL: Stata module to perform parallel estimation for multiple imputed datasets: Timothy Mak
MIPOLATE: Stata module to interpolate values: Nicholas Cox
MIRA: Stata module to compute Rubin's measure for multiple imputation regression analysis: Rodrigo Alfaro
MISSING: Stata module to replace missing values: Jose Maria Sanchez Saez
MISSINGPLOT: Stata module to draw plot showing patterns of missing values in a dataset: Nicholas Cox
MISSINGS: Stata module to manage missing values: Nicholas Cox
MISUM: Stata module to calculate summary statistics in MI dataset: Daniel Klein
MIVCAUSAL: Stata module for testing the hypothesis about the signs of the 2SLS weights: Conroy Lau and Alexander Torgovitsky
MIVIF: Stata module to calculate variance inflation factors after mi estimate regress: Daniel Klein
MIXLELAST: Stata module to compute mixed logit sample elasticities and marginal effects: Lars Zeigermann
MIXLOGIT: Stata module to fit mixed logit models by using maximum simulated likelihood: Arne Hole
MIXLOGITWTP: Stata module to estimate mixed logit models in WTP space: Arne Hole
MIXMCM: Stata module to estimate finite mixtures of non-stationary Markov chain models by maximum likelihood (ML) and the Expectation-Maximization (EM) algorithm: Legrand Saint-Cyr and Laurent Piet