Template-Type: ReDIF-Article 1.0 Author-Name: Christopher F Baum Author-Workplace-Name: Boston College Author-Workplace-Name: DIW Berlin Author-Email: baum@bc.edu Author-Person: pba1 Author-Name: Stan Hurn Author-Workplace-Name: Queensland University of Technology Author-Email: s.hurn@qut.edu.au Author-Person: phu111 Author-Name: Kenneth Lindsay Author-Workplace-Name: University of Glasgow Author-Email: kenneth.lindsay@glasgow.ac.uk Title: The BDS test of independence Journal: Stata Journal Pages: 279-294 Issue: 2 Volume: 21 Year: 2021 Month: June Abstract: In this article, we describe and implement the Brock, Dechert, and Scheinkman (1987, Working paper) test of independence of the elements of a time series. Keywords: bds, BDS test, dependence, correlation integral File-URL: http://www.stata-journal.com/article.html?article=st0636 File-Function: link to article purchase DOI: 10.1177/1536867X211025796 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/st0636/ Handle:RePEc:tsj:stataj:v:21:y:2021:i:2:p:279-294 Template-Type: ReDIF-Article 1.0 Author-Name: Christopher F Baum Author-Workplace-Name: Boston College Author-Workplace-Name: DIW Berlin Author-Email: baum@bc.edu Author-Person: pba1 Author-Name: Stan Hurn Author-Workplace-Name: Queensland University of Technology Author-Email: s.hurn@qut.edu.au Author-Person: phu111 Title: “What good is a volatility model?” A reexamination after 20 years Journal: Stata Journal Pages: 295-319 Issue: 2 Volume: 21 Year: 2021 Month: June Abstract: This article is primarily a replication study of Engle and Patton (2001, Quantitative Finance 1: 237–245), but it also serves as a demonstration of the time-series features introduced into Stata over the past two decades. The dataset used in the original study is extended from the end date of the original sample on 22 August 2000 to 1 August 2017 to examine the robustness of the models. Keywords: volatility, GARCH, time series, reproducible research File-URL: http://www.stata-journal.com/article.html?article=st0637 File-Function: link to article purchase DOI: 10.1177/1536867X211025797 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/st0637/ Handle:RePEc:tsj:stataj:v:21:y:2021:i:2:p:295-319 Template-Type: ReDIF-Article 1.0 Author-Name: Nicola Orsini Author-Email: nicola.orsini@ki.se Author-WorkPlace-Name: Karolinska Institutet Author-Person: por11 Title: Weighted mixed-effects dose–response models for tables of correlated contrasts Journal: Stata Journal Pages: 320-347 Issue: 2 Volume: 21 Year: 2021 Month: June Abstract: Recognizing a dose–response pattern based on heterogeneous tables of contrasts is hard. Specification of a statistical model that can consider the possible dose–response data-generating mechanism, including its variation across studies, is crucial for statistical inference. The aim of this article is to increase the un- derstanding of mixed-effects dose–response models suitable for tables of correlated estimates. One can use the command drmeta with additive (mean difference) and multiplicative (odds ratios, hazard ratios) measures of association. The postes- timation command drmeta graph greatly facilitates the visualization of predicted average and study-specific dose–response relationships. I illustrate applications of the drmeta command with regression splines in experimental and observational data based on nonlinear and random-effects data-generation mechanisms that can be encountered in health-related sciences. Keywords: drmeta, drmeta graph, drmeta gof, predict after drmeta, meta-analysis, meta-regression, mixed effects, summarized data, dose–response File-URL: http://www.stata-journal.com/article.html?article=st0638 File-Function: link to article purchase DOI: 10.1177/1536867X211025798 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/st0638/ Handle:RePEc:tsj:stataj:v:21:y:2021:i:2:p:320-347 Template-Type: ReDIF-Article 1.0 Author-Name: Matthias Pierce Author-Workplace-Name: University of Manchester Author-Email: matthias.pierce@manchester.ac.uk Author-Name: Richard Emsley Author-Workplace-Name: King’s College London Author-Email: richard.emsley@kcl.ac.uk Title: Estimating and evaluating personalized treatment recommendations from randomized trials with ptr Journal: Stata Journal Pages: 348-359 Issue: 2 Volume: 21 Year: 2021 Month: June Abstract: One of the targets of personalized medicine is to provide treatment rec- ommendations using patient characteristics. We present the command ptr, which both predicts a personalized treatment recommendation algorithm and evaluates its effectiveness versus an alternative regime, using randomized trial data. The command allows for multiple (continuous or categorical) biomarkers and a binary or continuous outcome. Confidence intervals for the evaluation parameter are provided using bootstrap resampling. Keywords: ptr, personalized treatment recommendations, personalized medicine, stratified medicine File-URL: http://www.stata-journal.com/article.html?article=st0639 File-Function: link to article purchase DOI: 10.1177/1536867X211025799 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/st0639/ Handle:RePEc:tsj:stataj:v:21:y:2021:i:2:p:348-359 Template-Type: ReDIF-Article 1.0 Author-Name: Hannes Kröger Author-Email: hkroeger@diw.de Author-WorkPlace-Name: German Institute for Economic Research (DIW) Author-Name: Jörg Hartmann Author-Email: a.ferrara@pitt.edu Author-WorkPlace-Name: Georg-August-Universität Göttingen Title: Extending the Kitagawa–Oaxaca–Blinder decomposition approach to panel data Journal: Stata Journal Pages: 360-410 Issue: 2 Volume: 21 Year: 2021 Month: June Abstract: The Kitagawa–Oaxaca–Blinder decomposition approach has been widely used to attribute group-level differences in an outcome to differences in en- dowment, coefficients, and their interactions. The method has been implemented for Stata in the popular oaxaca command for cross-sectional analyses. In recent decades, however, research questions have been more often focused on the decom- position of group-based differences in change over time, for example, diverging income trajectories, as well as decomposition of change in differences between groups, for example, change in the gender pay gap over time. We review five exist- ing methods for the decomposition of changes in group means and contribute an extension that takes an interventionist perspective suitable for applications with a clear before–after comparison. These decompositions of levels and changes over time can be implemented using the xtoaxaca command, which works as a postestimation command for different regression commands in Stata. It is built to maximize flexibility in modeling and implements all decomposition techniques presented in this article. Keywords: xtoaxaca, decomposition, longitudinal data, panel data, Oaxaca, Blinder, Kitagawa File-URL: http://www.stata-journal.com/article.html?article=st0640 File-Function: link to article purchase DOI: 10.1177/1536867X211025800 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/st0640/ Handle:RePEc:tsj:stataj:v:21:y:2021:i:2:p:360-410 Template-Type: ReDIF-Article 1.0 Author-Name: Michael Oberfichtner Author-Workplace-Name: Institute for Employment Research (IAB) Author-Email: Michael.Oberfichtner2@iab.de Author-Name: Harald Tauchmann Author-Workplace-Name: University of Erlangen-Nuremberg (FAU) Author-Email: harald.tauchmann@fau.de Author-Person: pta144 Title: Stacked linear regression analysis to facilitate testing of hypotheses across OLS regressions Journal: Stata Journal Pages: 411-429 Issue: 2 Volume: 21 Year: 2021 Month: June Abstract: In empirical work, researchers frequently test hypotheses of parallel form in several regressions, which raises concerns about multiple testing. One way to address the multiple-testing issue is to jointly test the hypotheses (for exam- ple, Pei, Pischke, and Schwandt [2019, Journal of Business & Economic Statis- tics 37: 205–216] and Lee and Lemieux [2010, Journal of Economic Literature 48: 281–355]). While the existing commands suest (Weesie, 1999, Stata Tech- nical Bulletin Reprints 9: 231–248) and mvreg enable Stata users to follow this approach, both are limited in several dimensions. For instance, mvreg assumes homoskedasticity and uncorrelatedness across sampling units, and neither com- mand is designed to be used with panel data. In this article, we introduce the new community-contributed command stackreg, which overcomes the aforemen- tioned limitations and allows for some settings and features that go beyond the capabilities of the existing commands. To achieve this, stackreg runs an ordinary least-squares regression in which the regression equations are stacked as described, for instance, in Wooldridge (2010, Econometric Analysis of Cross Section and Panel Data, p. 166–173, MIT Press) and applies cluster–robust variance–covariance esti- mation. Keywords: stackreg, xtstackreg, multiple testing, stacked regression, clustering, fixed effects File-URL: http://www.stata-journal.com/article.html?article=st0641 File-Function: link to article purchase DOI: 10.1177/1536867X211025801 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/st0641/ Handle:RePEc:tsj:stataj:v:21:y:2021:i:2:p:411-429 Template-Type: ReDIF-Article 1.0 Author-Name: Giorgio Calzolari Author-Workplace-Name: University of Firenze Author-Email: giorgio.calzolari@unifi.it Author-Person: pca337 Author-Name: Maria Gabriella Campolo Author-Workplace-Name: University of Messina Author-Email: mgcampolo@unime.it Author-Person: pca865 Author-Name: Antonino Di Pino Author-Workplace-Name: University of Messina Author-Email: dipino@unime.it Author-Name: Laura Magazzini Author-Workplace-Name: Sant’Anna School of Advanced Studies Author-Email: laura.magazzini@santannapisa.it Author-Person: pma1141 Title: Maximum likelihood estimation of an across-regime correlation parameter Journal: Stata Journal Pages: 430-461 Issue: 2 Volume: 21 Year: 2021 Month: June Abstract: In this article, we describe the mlcar command, which implements a maximum likelihood method to simultaneously estimate the regression coefficients of a two-regime endogenous switching model and the coefficient measuring the correlation of outcomes between the two regimes. This coefficient, known as the “across-regime” correlation parameter, is generally unidentified in the traditional estimation procedures. Keywords: mlcar, mlcartestn, Roy model, endogenous switching, maximum likelihood, across-regime correlation File-URL: http://www.stata-journal.com/article.html?article=st0642 File-Function: link to article purchase DOI: 10.1177/1536867X211025834 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/st0642/ Handle:RePEc:tsj:stataj:v:21:y:2021:i:2:p:430-461 Template-Type: ReDIF-Article 1.0 Author-Name: Thomas Kaspereit Author-Workplace-Name: University of Luxembourg Author-Email: thomas.kaspereit@uni.lu Title: Event studies with daily stock returns in Stata: Which command to use? Journal: Stata Journal Pages: 462-497 Issue: 2 Volume: 21 Year: 2021 Month: June Abstract: In this article, I provide an overview of existing community-contributed commands for executing event studies. I assess which command could have been used to conduct event studies that have appeared in the past 10 years in 3 leading accounting, finance, and management journals. The older command eventstudy provides a comfortable graphical user interface and good functionality for event studies that do not require hypotheses testing. The command estudy, described in Pacicco, Vena, and Venegoni (2018, Stata Journal 18: 461–476; 2021, Stata Journal 21: 141–151), provides a set of commonly applied test statistics and useful exporting routines to spreadsheet software and LATEX for event studies with a limited number of events. The most complete command in terms of available test statistics and benchmark models as well as its ability to handle events with insufficient data, thin trading, and large samples is eventstudy2. Keywords: event studies, estudy, eventstudy, eventstudy2 File-URL: http://www.stata-journal.com/article.html?article=st0643 File-Function: link to article purchase DOI: 10.1177/1536867X211025835 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/st0643/ Handle:RePEc:tsj:stataj:v:21:y:2021:i:2:p:462-497 Template-Type: ReDIF-Article 1.0 Author-Name: B. M. Fernandez-Felix Author-Email: borjam.fernandez@hrc.es Author-WorkPlace-Name: Clinical Biostatistics Unit Hospital Ramón y Cajal (IRYCIS) Author-Name: E. García-Esquinas Author-WorkPlace-Name: Autonomous University of Madrid Author-Name: A. Muriel Author-WorkPlace-Name: Clinical Biostatistics Unit Hospital Ramón y Cajal (IRYCIS) Author-Name: A. Royuela Author-WorkPlace-Name: Puerta de Hierro Biomedical Research Institute Author-Name: J. Zamora Author-WorkPlace-Name: Clinical Biostatistics Unit Hospital Ramón y Cajal (IRYCIS) Title: Bootstrap internal validation command for predictive logistic regression models Journal: Stata Journal Pages: 498-509 Issue: 2 Volume: 21 Year: 2021 Month: June Abstract: Overfitting is a common problem in the development of predictive models. It leads to an optimistic estimation of apparent model performance. Internal validation using bootstrapping techniques allows one to quantify the optimism of a predictive model and provide a more realistic estimate of its performance mea- sures. Our objective is to build an easy-to-use command, bsvalidation, aimed to perform a bootstrap internal validation of a logistic regression model. Keywords: bsvalidation, bootstrap, internal validation, predictive model, performance, logistic, logit File-URL: http://www.stata-journal.com/article.html?article=st0644 File-Function: link to article purchase DOI: 10.1177/1536867X211025836 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/st0644/ Handle:RePEc:tsj:stataj:v:21:y:2021:i:2:p:498-509 Template-Type: ReDIF-Article 1.0 Author-Name: Joseph N. Luchman Author-Workplace-Name: Fors Marsh Group LLC Author-Email: jluchman@forsmarshgroup.com Author-Person: plu284 Title: Determining relative importance in Stata using dominance analysis: domin and domme Journal: Stata Journal Pages: 510-538 Issue: 2 Volume: 21 Year: 2021 Month: June Abstract: Dominance analysis is a common method applied to statistical models to determine the importance of independent variables. In this article, I describe two community-contributed commands, domin and domme, that can be used to dominance-analyze both independent variables and parameter estimates in Stata estimation commands. I discuss how to compute dominance statistics, provide multiple examples of each command applied to data, and outline how to inter- pret the results from each data-analytic example. I conclude with computational considerations for users applying larger models. Keywords: domin, domme, dominance analysis, relative importance analysis, decomposition, Shapley value decomposition File-URL: http://www.stata-journal.com/article.html?article=st0645 File-Function: link to article purchase DOI: 10.1177/1536867X211025837 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/st0645/ Handle:RePEc:tsj:stataj:v:21:y:2021:i:2:p:510-538 Template-Type: ReDIF-Article 1.0 Author-Name: Nicholas J. Cox Author-Workplace-Name: Durham University Author-Email: n.j.cox@durham.ac.uk Author-Person: pco34 Title: Speaking Stata: Front-and-back plots to ease spaghetti and paella problems Journal: Stata Journal Pages: 539-554 Issue: 2 Volume: 21 Year: 2021 Month: June Abstract: The spaghetti problem arises in graphics when multiple time series or other functional traces show mostly a tangled mess. The related paella problem (often experienced but not usually named as such) arises for multiple patterns combined in scatterplots. This column is a sequel to those in Stata Journal 10: 670–681 (2010) and 19: 989–1008 (2019). The focus is on what are here called front-and-back plots, in which each subset of data is shown separately with the other subsets as backdrop. The strategy is thus a hybrid of two more common strategies, showing each subset separately (juxtaposing) and showing subsets to- gether (superimposing). A new command, fabplot, is introduced and used in examples. Keywords: fabplot, graphics, front-and-back plots, juxtaposing, superimposing, line plots, scatterplots, panel data, longitudinal data, quantile plots File-URL: http://www.stata-journal.com/article.html?article=gr0087 File-Function: link to article purchase DOI: 10.1177/1536867X211025838 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/gr0087/ Handle:RePEc:tsj:stataj:v:21:y:2021:i:2:p:539-554 Template-Type: ReDIF-Article 1.0 Author-Name: Nicholas J. Cox Author-Workplace-Name: Durham University Author-Email: n.j.cox@durham.ac.uk Author-Person: pco34 Title: Erratum: Speaking Stata: Loops, again and again Journal: Stata Journal Pages: 555 Issue: 2 Volume: 21 Year: 2021 Month: June Abstract: The spaghetti problem arises in graphics when multiple time series or other functional traces show mostly a tangled mess. The related paella problem (often experienced but not usually named as such) arises for multiple patterns combined in scatterplots. This column is a sequel to those in Stata Journal 10: 670–681 (2010) and 19: 989–1008 (2019). The focus is on what are here called front-and-back plots, in which each subset of data is shown separately with the other subsets as backdrop. The strategy is thus a hybrid of two more common strategies, showing each subset separately (juxtaposing) and showing subsets to- gether (superimposing). A new command, fabplot, is introduced and used in examples. Keywords: fabplot, graphics, front-and-back plots, juxtaposing, superimposing, line plots, scatterplots, panel data, longitudinal data, quantile plots File-URL: http://www.stata-journal.com/article.html?article=pr0074_1 File-Function: link to article purchase DOI: 10.1177/1536867X211025839 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/pr0074_1/ Handle:RePEc:tsj:stataj:v:21:y:2021:i:2:p:555 Template-Type: ReDIF-Article 1.0 Author-Name: Claire Hills Author-Name: Bianca L. De Stavola Author-Workplace-Name: UCL GOS Institute of Child Health Author-Email: b.destavola@ucl.ac.uk Author-Name: Simon Cousens Author-Workplace-Name: Department of Infectious Disease Epidemiology, LSHTM Author-Email: Simon.Cousens@lshtm.ac.uk Author-Name: David Leon Author-Workplace-Name: Department of Non-communicable Disease Epidemiology, LSHTM Author-Email: David.Leon@lshtm.ac.uk Author-Name: Nicholas J. Cox Author-Workplace-Name: Durham University Author-Email: n.j.cox@durham.ac.uk Author-Person: pco34 Title: Michael Hills (1934–2021) Journal: Stata Journal Pages: 273-278 Issue: 2 Volume: 21 Year: 2021 Month: June File-URL: http://www.stata-journal.com/article.html?article=gn0086 File-Function: link to article purchase DOI: 10.1177/1536867X211026525 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/gn0086/ Handle:RePEc:tsj:stataj:v:21:y:2021:i:2:p:273-278 Template-Type: ReDIF-Article 1.0 Author-Name: Editors Author-Email: editors@stata.com Title: Software updates Journal: Stata Journal Pages: 556-557 Issue: 2 Volume: 21 Year: 2021 Month: June Abstract: Updates for previously published packages are provided. Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/dm0101_1/ Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/st0389_6/ Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/st0390_2/ Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/st0393_3/ Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/st0599_1/ Handle:RePEc:tsj:stataj:v:21:y:2021:i:2:p:556-557