# StataCorp LP

# Stata Journal

This journal used to be published by StataCorp LP under the name Stata Technical Bulletin.
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### 2016, Volume 16, Issue 3

**523-549 The Keane and Runkle estimator for panel-data models with serial correlation and instruments that are not strictly exogenous***by*Michael Keane & Timothy Neal**550-589 Nonparametric frontier analysis using Stata***by*Oleg Badunenko & Pavlo Mozharovskyi**590-612 Multiple imputation for categorical time series***by*Brendan Halpin**613-631 Hot and cold spot analysis using Stata***by*Keisuke Kondo**632-649 A sparser, speedier reshape***by*Kenneth L. Simons**650-661 Using mi impute chained to fit ANCOVA models in randomized trials with censored dependent and independent variables***by*Andreas Andersen & Andreas Rieckmann**662-677 dynsimpie: A command to examine dynamic compositional dependent variables***by*Andrew Q. Philips & Amanda Rutherford & Guy D. Whitten**678-690 Versatile tests for comparing survival curves based on weighted log-rank statistics***by*Theodore G. Karrison**691-701 eq5dds: A command to analyze the descriptive system of EQ-5D quality-of-life instrument***by*Juan Manuel Ramos-Goñi & JYolanda Ramallo-Fariña**702-716 strmst2 and strmst2pw: New commands to compare survival curves using the restricted mean survival time***by*Angel Cronin & Lu Tian & Hajime Uno**717-739 Implementing Rubin's alternative multiple-imputation method for statistical matching in Stata***by*Anil Alpman**740-760 The lag-length selection and detrending methods for HEGY seasonal unit-root tests using Stata***by*Tomás del Barrio Castro & Andrii Bodnar & Andreu Sansó**761-777 A test for exogeneity in the presence of nonlinearities***by*Michael P. Babington & Javier Cano-Urbina**778-804 Estimation of panel vector autoregression in Stata***by*Michael R. M. Abrigo & Inessa Love**805-812 Speaking Stata: Shading zones on time series and other plots***by*Nicholas J. Cox**813-814 Software updates***by*Editors

### 2016, Volume 16, Issue 2

**245-263 Creating LaTeX documents from within Stata using texdoc***by*Ben Jann**264-300 Assessing inequality using percentile shares***by*Ben Jann**301-315 Regression models for bivariate count outcomes***by*Xinling Xu & James W. Hardin**316-330 Implementing weighted-average estimation of substance concentration using multiple dilutions***by*Ying Xu & Paul Milligan & Edmond J. Remarque & Yin Bun Cheung**331-367 Inference in regression discontinuity designs under local randomization***by*Matias D. Cattaneo & Roc ́ıo Titiunik & Gonzalo Vazquez-Bare**368-385 Simpler standard errors for two-stage optimization estimators estimation in normal linear models***by*Joseph V. Terza**386-402 igmobil: A command for intergenerational mobility analysis in Stata***by*Marco Savegnago**403-415 Fixed effects in unconditional quantile regression***by*Nicolai T. Borgen**416-423 Calculate travel time and distance with OpenStreetMap data using the Open Source Routing Machine (OSRM)***by*Stephan Huber & Christoph Rust**424-442 Panel time series: Review of the methodological evolution***by*Tamara Burdisso & Maximo Sangiacomo**443-463 Reference-based sensitivity analysis via multiple imputation for longitudinal trials with protocol deviation***by*Suzie Cro & Tim P. Morris & Michael G. Kenward & James R. Carpenter**464-481 Partial credit model: Estimations and tests of fit with pcmodel***by*Jean-Francois Hamel & Veronique Sebille & Gaelle Challet-Bouju & Jean-Benoit Hardouin**482-490 Abadie’s semiparametric difference-in-differences estimator***by*Kenneth Houngbedji**491-510 Speaking Stata: Multiple bar charts in table form***by*Nicholas J. Cox**511-516 Review of Christopher F. Baum’s An Introduction to Stata Programming, Second Edition***by*Clyde Schechter**517-520 Stata tip 126: Handling irregularly spaced high-frequency transactions data***by*Christopher F Baum & Sebastiaan Bibo**521-522 Software updates***by*Editors

### 2016, Volume 16, Issue 1

**3-4 16 and all that***by*Editors**5-22 Regressions are commonly misinterpreted***by*David C. Hoaglin**23-24 Regressions are commonly misinterpreted: Comments on the article***by*James W. Hardin**30-36 Regressions are commonly misinterpreted: A rejoinder***by*David C. Hoaglin**37-51 Estimation of multivariate probit models via bivariate probit***by*John Mullahy**52-71 diff: Simplifying the estimation of difference-in-differences treatment effects***by*Juan M. Villa**72-87 mfpa: Extension of mfp using the ACD covariate transformation for enhanced parametric multivariable modeling***by*Patrick Royston & Willi Sauerbrei**88-95 Quantifying the uptake of user-written commands over time***by*Babak Choodari-Oskooei & Tim P. Morris**96-111 bireprob: An estimator for bivariate random-effects probit models***by*Alexander Plum**112-138 conindex: Estimation of concentration indices***by*Owen O’Donnell & Stephen O’Neill & Tom Van Ourti & Brendan Walsh**139-158 Estimating polling accuracy in multiparty elections using surveybias***by*Kai Arzheimer & Jocelyn Evans**159-184 bicop: A command for fitting bivariate ordinal regressions with residual dependence characterized by a copula function and normal mixture marginals***by*Mónica Hernández-Alava & Stephen Pudney**185-196 Features of the area under the receiver operating characteristic (ROC) curve. A good practice***by*David Lora & Israel Contador & José F. Pérez-Regadera & Agustín Gómez de la Cámara**197-228 Implementing factor models for unobserved heterogeneity in Stata***by*Miguel Sarzosa & Sergio Urzúa**229-236 Speaking Stata: Truth, falsity, indication, and negation***by*Nicholas J. Cox**237-242 Review of Michael N. Mitchell’s Stata for the Behavioral Sciences***by*Philip B. Ender**244 Software updates***by*Editors

### 2015, Volume 15, Issue 4

**Cumulative author index, volumes 1-15***by*Christopher F Baum**901-904 The Stata Journal Editors' Prize 2014: Richard Williams***by*H. Joseph Newton & Nicholas J. Cox**905-950 Visualizing assumptions and results in network meta-analysis: The network graphs package***by*Anna Chaimani & Georgia Salanti**951-985 Network meta-analysis***by*Ian R. White**986-1018 Bootstrap-based bias correction and inference for dynamic panels with fixed effects***by*Ignace De Vos & Gerdie Everaert & Ilse Ruyssen**1019-1045 ctreatreg: Command for fitting dose–response models under exogenous and endogenous treatment***by*Giovanni Cerulli**1060-1074 EORTC QLQ-C30 descriptive analysis with the qlqc30 command***by*Caroline Bascoul-Mollevi & Florence Castan & David Azria & Sophie Gourgou-Bourgade**1075-1097 Implementing a strategy to reduce the instrument count in panel GMM***by*Maria Elena Bontempi & Irene Mammi**1098-1117 Estimating the treatment effect in a clinical trial using difference in restricted mean survival time***by*Patrick Royston**1118-1156 Studying coincidences with network analysis and other multivariate tools***by*Modesto Escobar**1157-1166 Testing for spectral Granger causality***by*Hüseyin Tastan**1167-1173 Complete automation of a participant characteristics table***by*Seth T. Lirette**1174-1185 Speaking Stata: A set of utilities for managing missing values***by*Nicholas J. Cox**1186-1187 Software updates***by*Editors

### 2015, Volume 15, Issue 3

**607-626 precombine: A command to examine n ≥ 2 datasets before combining***by*Mark D. Chatfield**627-644 Prediction in linear index models with endogenous regressors***by*Christopher L. Skeels & Larry W. Taylor**645-671 Fitting fixed- and random-effects meta-analysis models using structural equation modeling with the sem and gsem commands***by*Tom M. Palmer & Jonathan A. C. Sterne**672-697 Record linkage using Stata: Preprocessing, linking, and reviewing utilities***by*Nada Wasi & Aaron Flaaen**712-736 Approximate Bayesian logistic regression via penalized likelihood by data augmentation***by*Andrea Discacciati & Nicola Orsini & Sander Greenland**737-750 Fitting adjusted limited dependent variable mixture models to EQ-5D***by*Monica Hernandez Alava & Allan Wailoo**751-755 A note on adding objects to an existing twoway graph***by*Ben Jann**756-774 Estimating treatment effects for ordered outcomes using maximum simulated likelihood***by*Christian A. Gregory**775-783 Creating summary tables using the sumtable command***by*Lauren J. Scott & Chris A. Rogers**784-795 Bandwidth selection in kernel distribution function estimation***by*Ignacio Lopez-de-Ullibarri**796-808 didq: A command for treatment-effect estimation under alternative assumptions***by*Ricardo Mora & Iliana Reggio**809-821 Regression analysis of censored data using pseudo-observations: An update***by*Morten Overgaard & Per K. Andersen & Erik T. Parner**822-832 Tests for normality in linear panel-data models***by*Javier Alejo & Antonio Galvao & Gabriel Montes-Rojas & Walter Sosa-Escudero**833-844 Bandwidth selection in kernel distribution function estimation***by*W. Scott Comulada**845-853 mqtime: A Stata tool for calculating travel time and distance using MapQuest web services***by*John Voorheis**854-880 The Berry–Levinsohn–Pakes estimator of the random-coefficients logit demand model***by*David W. Vincent**881-898 Feasible fitting of linear models with N fixed effects***by*Fernando Rios-Avila**899 Software updates***by*Editors

### 2015, Volume 15, Issue 2

**325-349 Global search regression: A new automatic model-selection technique for cross-section, time-series, and panel-data regressions***by*Pablo Gluzmann & Demian Panigo**350-368 A menu-driven facility for sample-size calculation in multiarm, multistage randomized controlled trials with time-to-event outcomes: Update***by*Daniel J. Bratton & Babak Choodari-Oskooei & Patrick Royston**369-396 Two-stage individual participant data meta-analysis and generalized forest plots***by*David J. Fisher**397-410 Person-centered treatment (PeT) effects: Individualized treatment effects using instrumental variables***by*Anirban Basu**411-436 Bounding treatment effects: A command for the partial identification of the average treatment effect with endogenous and misreported treatment assignment***by*Ian McCarthy & Daniel L. Millimet & Manan Roy**437-456 Multiple imputation of covariates by substantive-model compatible fully conditional specification***by*Jonathan W. Bartlett & Tim P. Morris**457-479 Modeling heaped count data***by*Tammy H. Cummings & James W. Hardin & Alexander C. McLain & James R. Hussey & Kevin J. Bennett & Gina M. Wingood**480-500 Conducting interrupted time-series analysis for single- and multiple-group comparisons***by*Ariel Linden**501-511 Top 10 Stata "gotchas"***by*Jonathan Shaw**512-522 Generalized maximum entropy estimation of discrete choice models***by*Paul Corral & Mungo Terbish**523-536 gpsbound: A command for importing and verifying geographical information from a user-provided shapefile***by*Tim S. L. Brophy & Reza Che Daniels & Sibongile Musundwa**537-546 A general-purpose nomogram generator for predictive logistic regression models***by*Alexander Zlotnik & Victor Abraira**547-553 Transition matrix for a bivariate normal distribution in Stata***by*Marco Savegnago**554-573 Estimating almost-ideal demand systems with endogenous regressors***by*Sebastien Lecocq & Jean-Marc Robin**574-587 Speaking Stata: Species of origin***by*Nicholas J. Cox**588-593 Review of Alan Acock's A Gentle Introduction to Stata, Fourth Edition***by*Tim Collier**594-596 graphlog: Creating log files with embedded graphics***by*Martin Rune Hansen**597-598 Stata tip 124: Passing temporary variables to subprograms***by*Maarten L. Buis**599-604 Stata tip 125: Binned residual plots for assessing the fit of regression models for binary outcomes***by*Jessica Kasza**605-606 Software updates***by*Editors

### 2015, Volume 15, Issue 1

**3-20 twopm: Two-part models***by*Federico Belotti & Partha Deb & Willard G. Manning & Edward C. Norton**21-44 Implementing intersection bounds in Stata***by*Victor Chernozhukov & Wooyoung Kim & Sokbae Lee & Adam M. Rosen**45-76 More power through symbolic computation: Extending Stata by using the Maxima computer algebra system***by*Giovanni L. Lo Magno**77-94 Time-efficient algorithms for robust estimators of location, scale, symmetry, and tail heaviness***by*Wouter Gelade & Vincenzo Verardi & Catherine Vermandele**95-109 Generating univariate and multivariate nonnormal data***by*Sunbok Lee**110-120 Bayesian optimal interval design for phase I oncology clinical trials***by*Bryan M. Fellman & Ying Yuan**121-134 Fixed-effect panel threshold model using Stata***by*Qunyong Wang**135-154 Frailty models and frailty-mixture models for recurrent event times***by*Ying Xu & Yin Bun Cheung**155-172 newspell: Easy management of complex spell data***by*Hannes Kroger**173-185 Estimating net survival using a life-table approach***by*Enzo Coviello & Paul W. Dickman & Karri Seppa & Arun Pokhrel**186-215 Estimating and modeling relative survival***by*Paul W. Dickman & Enzo Coviello**216-225 A robust test for weak instruments in Stata***by*Carolin E. Pflueger & Su Wang**226-246 Regression models for count data from truncated distributions***by*James W. Hardin & Joseph M. Hilbe**247-274 dynemp: A routine for distributed microdata analysis of business dynamics***by*Chiara Criscuolo & Peter N. Gal & Carlo Menon**275-291 Tools for checking calibration of a Cox model in external validation: Prediction of population-averaged survival curves based on risk groups***by*Patrick Royston**292-300 Nonparametric pairwise multiple comparisons in independent groups using Dunn's test***by*Alexis Dinno**301-308 Bayesian optimal interval design for phase I oncology clinical trials***by*Minxing Chen**309-315 Review of Alan Acock’s Discovering Structural Equation Modeling Using Stata, Revised Edition***by*Richard Williams**316-318 Stata tip 122: Variable bar widths in two-way graphs***by*Ben Jann**319-323 Stata tip 123: Spell boundaries***by*Nicholas J. Cox**324 Software updates***by*Editors

### 2014, Volume 14, Issue 4

**703-707 The Stata Journal Editors' Prize 2014: Roger Newson***by*H. Joseph Newton & Nicholas J. Cox**708-737 Plotting regression coefficients and other estimates***by*Ben Jann**738-755 Tools for checking calibration of a Cox model in external validation: Approach based on individual event probabilities***by*Patrick Royston**756-777 Estimation of multiprocess survival models with cmp***by*Tamas Bartus & David Roodman**778-797 dhreg, xtdhreg, and bootdhreg: Commands to implement double-hurdle regression***by*Christoph Engel & Peter G. Moffatt**798-816 The chi-squared goodness-of-fit test for count-data models***by*Miguel Manjon & Oscar Martinez**817-829 txttool: Utilities for text analysis in Stata***by*Unislawa Williams & Sean P. Williams**830-846 iop: Estimating ex-ante inequality of opportunity***by*Florian Wendelspiess Chavez Juarez & Isidro Soloaga**847-862 femlogit-Implementation of the multinomial logit model with fixed effects***by*Klaus Pforr**863-883 Analysis of partially observed clustered data using generalized estimating equations and multiple imputation***by*Kathryn M. Aloisio & Sonja A. Swanson & Nadia Micali & Alison Field & Nicholas J. Horton**884-894 Lee (2009) treatment-effect bounds for nonrandom sample selection***by*Harald Tauchmann**895-908 General-to-specific modeling in Stata***by*Damian Clarke**909-946 Robust data-driven inference in the regression-discontinuity design***by*Sebastian Calonico & Matias D. Cattaneo & Rocio Titiunik**947-964 adjcatlogit, ccrlogit, and ucrlogit: Fitting ordinal logistic regression models***by*Morten W. Fagerland**965-974 Collecting and organizing Stata graphs***by*Joseph D. Wolfe & Shawn Bauldry**975-990 Speaking Stata: Design plots for graphical summary of a response given factors***by*Nicholas J. Cox**991-996 Stata tip 121: Box plots side by side***by*Nicholas J. Cox**997 Software updates***by*Editors

### 2014, Volume 14, Issue 3

**453-480 ivtreatreg: A command for fitting binary treatment models with heterogeneous response to treatment and unobservable selection***by*Giovanni Cerulli**481-498 Obtaining critical values for test of Markov regime switching***by*Valerie K. Bostwick & Douglas G. Steigerwald**499-510 A command for significance and power to test for the existence of a unique most probable category***by*Bryan M. Fellman & Joe Ensor**511-540 Merger simulation with nested logit demand***by*Jonas Björnerstedt & Frank Verboven**541-561 treatrew: A user-written command for estimating average treatment effects by reweighting on the propensity score***by*Giovanni Cerulli**562-579 Modeling count data with generalized distributions***by*Tammy Harris & Joseph M. Hilbe & James W. Hardin**580-604 A Stata package for the application of semiparametric estimators of dose–response functions***by*Michela Bia & Carlos A. Flores & Alfonso Flores-Lagunes & Alessandra Mattei**605-622 Space-filling location selection***by*Michela Bia & Philippe Van Kerm**623-661 Adaptive Markov chain Monte Carlo sampling and estimation in Mata***by*Matthew J. Baker**662-669 csvconvert: A simple command to gather comma-separated value files into Stata***by*Alberto A. Gaggero**670-683 The bmte command: Methods for the estimation of treatment effects when exclusion restrictions are unavailable***by*Ian McCarthy & Daniel Millimet & Rusty Tchernis**684-692 Panel cointegration analysis with xtpedroni***by*Timothy Neal**693-696 Stata and Dropbox***by*Raymond Hicks**697-700 Review of An Introduction to Stata for Health Researchers, Fourth Edition, by Juul and Frydenberg***by*Ariel Linden**701 Software updates***by*Editors

### 2014, Volume 14, Issue 2

**237-258 Self-consistent density estimation***by*Joerg Luedicke & Alberto Bernacchia**259-279 Simulated multivariate random-effects probit models for unbalanced panels***by*Alexander Plum**280-291 Regression models for count data based on the negative binomial(p) distribution***by*James W. Hardin & Joseph M. Hilbe**292-303 Estimation and testing of binomial and beta-binomial regression models with and without zero inflation***by*James W. Hardin & Joseph M. Hilbe**304-328 Density-based empirical likelihood procedures for testing symmetry of data distributions and K-sample comparisons***by*Albert Vexler & Hovig Tanajian & Alan D. Hutson**329-341 A smooth covariate rank transformation for use in regression models with a sigmoid dose–response function***by*Patrick Royston**342-362 From Stata to aML***by*Sara Ayllon**363-380 A menu-driven facility for power and detectable-difference calculations in stepped-wedge cluster-randomized trials***by*Karla Hemming & Alan Girling**381-388 Importing Chinese historical stock market quotations from NetEase***by*Xuan Zhang & Chuntao Li**389-397 Power analyses for detecting effects for multiple coefficients in regression***by*Christopher L. Aberson**398-406 Note on Lilien and modified Lilien index***by*Muhammad Rashid Ansari & Chiara Mussida & Francesco Pastore**407-417 Stata command for calculating adverse event and efficacy stopping boundaries for phase II single-arm trials***by*Bryan M. Fellman**418-431 Application of multiple imputation using the two-fold fully conditional specification algorithm in longitudinal clinical data***by*Catherine Welch & Jonathan Bartlett & Irene Petersen**432-444 Speaking Stata: Self and others***by*Nicholas J. Cox**445-448 Review of Introduction to Time Series Using Stata by Sean Becketti***by*Dimitriy V. Masterov**449-450 Stata tip 120: Certifying subroutines***by*Maarten L. Buis**451 Software updates***by*Editors

### 2014, Volume 14, Issue 1

**4-21 sreweight: A Stata command to reweight survey data to external totals***by*Daniele Pacifico**22-59 Calibrating survey data using iterative proportional fitting (raking)***by*Stanislav Kolenikov**60-75 miivfind: A command for identifying model-implied instrumental variables for structural equation models in Stata***by*Shawn Bauldry**76-86 Indirect treatment comparison***by*Branko Miladinovic & Anna Chaimani & Iztok Hozo & Benjamin Djulbegovic**87-102 Net survival estimation with stns***by*Isabelle Clerc-Urmes & Michel Grzebyk & Guy Hedelin**103-118 Reports and other PDF documents***by*Rafael J. A. Camara**119-140 Estimating adjusted associations between random effects from multilevel models: The reffadjust package***by*Tom M. Palmer & Corrie M. Macdonald-Wallis & Debbie A. Lawlor & Kate Tilling**141-158 Estimating the dose–response function through a generalized linear model approach***by*Barbara Guardabascio & Marco Ventura**159-175 Sample size and power calculations for trials and quasi-experimental studies with clustering***by*Evridiki Batistatou & Chris Roberts & Steve Roberts**176-190 strel2: A command for estimating excess hazard and relative survival in large population-based studies***by*Michael Hills & Bernard Rachet & Milena Falcaro**191-217 Estimating marginal treatment effects using parametric and semiparametric methods***by*Scott Brave & Thomas Walstrum**218-220 Stata tip 116: Where did my p-values go? (Part 3)***by*Maarten L. Buis**221-225 Stata tip 117: graph combine--Combining graphs***by*Lars Angquist**226-229 Stata tip 118: Orthogonalizing powered and product terms using residual centering***by*Carsten Sauer**230-235 Stata tip 119: Expanding datasets for graphical ends***by*Nicholas J. Cox

### 2013, Volume 13, Issue 4

**669-671 The Stata Journal Editors' Prize 2013: Erik Thorlund Parner and Per Kragh Andersen***by*H. Joseph Newton & Nicholas J. Cox**672-698 Attributable and unattributable risks and fractions and other scenario comparisons***by*Roger B. Newson**699-718 Dealing with identifier variables in data management and analysis***by*P. Wilner Jeanty**718-758 Stochastic frontier analysis using Stata***by*Federico Belotti & Silvio Daidone & Giuseppe Ilardi & Vincenzo Atella**759-775 Flexible parametric illness-death models***by*Sally R. Hinchliffe & David A. Scott & Paul C. Lambert**776-794 Implementation of a double-hurdle model***by*Bruno Garcia**795-809 Little's test of missing completely at random***by*Cheng Li**810-835 Testing for zero inflation in count models: Bias correction for the Vuong test***by*Bruce A. Desmarais & Jeffrey J. Harden**836-861 Parametric inference using structural break tests***by*Zachary L. Flynn & Leandro M. Magnusson**862-866 cmpute: A tool to generate or replace a variable***by*Patrick Royston**867-875 group2: Generating the finest partition that is coarser than two given partitions***by*Christian H. Salas Pauliac**876-883 A score test for group comparisons in single-index models***by*Paulo Guimaraes