Template-Type: ReDIF-Article 1.0 Author-Name: Paul A. Tiffin Author-Workplace-Name: University of York Author-Email: paul.tiffin@york.ac.uk Title: miesize: Effect-size calculation in imputed data Journal: Stata Journal Pages: 503-513 Issue: 3 Volume: 24 Year: 2024 Month: September Abstract: In this article, I describe the miesize command for the calculation of effect sizes in imputed data. There may be situations where an effect size needs to be estimated for an intervention, an exposure, or a group membership variable but data on the independent or dependent variable are missing. Such missing data are commonly dealt with by multiply imputing plausible values. However, in this circumstance, the estimated effect size and associated standard errors will need to be pooled and estimated from the imputed dataset. The miesize command auto- mates this process and calculates effect sizes for a binary variable from multiply imputed data in wide format. The estimates and standard errors (used to calculate the confidence intervals) are recombined using Rubin’s (1987, Multiple Imputation for Nonresponse in Surveys [Wiley]) rules. These rules are applied such that the average point estimate for the effect size is calculated from the imputed datasets. The pooled standard error, and hence confidence intervals, is calculated to account for both the variance between the imputed datasets and the variance within them. Pooled effect sizes and confidence intervals for Cohen’s (1988, Statistical Power Analysis for the Behavioral Sciences, 2nd ed. [Lawrence Erlbaum]) 𝑑, Hedges’s (1981, Journal of Educational Statistics 6: 107–128) 𝑔, and Glass’s (Smith and Glass, 1977, American Psychologist 32: 752–760) delta are provided by miesize. Keywords: miesize, effect size, imputation, Rubin’s rules, Cohen’s 𝑑, Hedges’s 𝑔, Glass’s delta File-URL: http://www.stata-journal.com/article.html?article=st0755 File-Function: link to article purchase X-DOI: 10.1177/1536867X241276113 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj24-3/st0755/ Handle:RePEc:tsj:stataj:v:24:y:2024:i:3:p:503-513 Template-Type: ReDIF-Article 1.0 Author-Name: Filippo Palomba Author-Workplace-Name: Princeton University Author-Email: fpalomba@princeton.edu Title: Getting away from the cutoff in regression discontinuity designs Journal: Stata Journal Pages: 371-401 Issue: 3 Volume: 24 Year: 2024 Month: September Abstract: Regression discontinuity (RD) designs are highly popular in economic research because of their strong internal validity and straightforward intuition. While RD estimates are local in nature, several recent articles propose methods that generalize RD estimates to units outside a small neighborhood of the cutoff. In this article, I introduce the getaway package, which implements the method proposed by Angrist and Rokkanen (2015, Journal of the American Statistical As- sociation 110: 1331–1344) to extrapolate treatment-effect estimates “away from the cutoff”, relying on a classical unconfoundedness condition. Additionally, the package features a data-driven algorithm designed to identify a set of covariates that fulfills the unconfoundedness assumption. It also incorporates a toolkit in- tended for testing and visualization purposes. Keywords: getaway, ciasearch, ciatest, ciares, ciacs, getawayplot, regression discontinuity designs, treatment effects File-URL: http://www.stata-journal.com/article.html?article=st0751 File-Function: link to article purchase X-DOI: 10.1177/1536867X241276108 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj24-3/st0751/ Handle:RePEc:tsj:stataj:v:24:y:2024:i:3:p:371-401 Template-Type: ReDIF-Article 1.0 Author-Name: Chuntao Li Author-Workplace-Name: Henan University Author-Email: chtl@henu.edu.cn Author-Name: Yizhuo Fang Author-Workplace-Name: Henan University Author-Email: yzhfang1@163.com Author-Name: Lifang Cao Author-Workplace-Name: Henan University Author-Email: caolifang64@163.com Title: cnevent: Event study with Chinese equity market data Journal: Stata Journal Pages: 478-502 Issue: 3 Volume: 24 Year: 2024 Month: September Abstract: In this article, we present a new command, cnevent, that runs event studies about Chinese-listed companies. With cnevent, researchers are required to provide only a list of events with the Chinese stock code and the corresponding date for each event, and the command can automatically extract indexes and each individual stock’s return data to run the whole process of the event study. Furthermore, cnevent enables users to choose the benchmark from among different market indexes and different event window sets with options. The command then generates daily abnormal returns for all trading days within the event window and aggregates the cumulative abnormal returns (CARs) for the whole event window. Finally, cnevent can plot a graph to show the trend of the CAR𝑡 within the event window and test whether the event has a significant effect on valuation. Keywords: cnevent, Chinese listed companies, event study, abnormal returns, cumulative abnormal returns, CARs File-URL: http://www.stata-journal.com/article.html?article=st0754 File-Function: link to article purchase X-DOI: 10.1177/1536867X241276112 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj24-3/st0754/ Handle:RePEc:tsj:stataj:v:24:y:2024:i:3:p:478-502 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: Quantile–quantile plots, generalized Journal: Stata Journal Pages: 513-534 Issue: 3 Volume: 24 Year: 2024 Month: September Abstract: Quantile–quantile plots in the precise sense of scatterplots showing corresponding quantiles of two variables have long been supported by official command qqplot. That command is generalized here in several ways in a new command, qqplotg. In this article, I explain the major features of qqplotg and give several examples of its use. Themes include the use of quantile–quantile plots to explore the possibilities for working on a transformed scale and the value of plotting difference between quantiles versus mean quantile or plotting position. Various historical and methodological remarks are sprinkled throughout. Keywords: qqplotg, quantile–quantile plots, quantile plots, quantiles, plotting positions, additivity, homoskedasticity, symmetry, linearity, transformations, difference versus mean, graphics, distributions File-URL: http://www.stata-journal.com/article.html?article=gr0096 File-Function: link to article purchase DOI: 10.1177/1536867X231196519 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj24-3/gr0096/ Handle:RePEc:tsj:stataj:v:24:y:2024:i:3:p:513-534 Template-Type: ReDIF-Article 1.0 Author-Name: Marcel F. Jonker Author-Workplace-Name: Erasmus University Rotterdam Author-Email: marcel@mfjonker.com Title: Fitting garbage class mixed logit models in Stata Journal: Stata Journal Pages: 427-445 Issue: 3 Volume: 24 Year: 2024 Month: September Abstract: In this article, I describe the garbage_mixl command, which fits the garbage class and standard panel mixed logit models in Stata. Keywords: garbage_mixl, garbage class, mixlogit, mixed logit, random parameter logit File-URL: http://www.stata-journal.com/article.html?article=st0753 File-Function: link to article purchase X-DOI: 10.1177/1536867X241276110 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj24-3/st0753/ Handle:RePEc:tsj:stataj:v:24:y:2024:i:3:p:427-445 Template-Type: ReDIF-Article 1.0 Author-Name: Kerui Du Author-Workplace-Name: Xiamen University Author-Email: kerrydu@xmu.edu.cn Author-Name: Luis Orea Author-Workplace-Name: University of Oviedo Author-Email: lorea@uniovi.es Author-Person: por56 Author-Name: Inmaculada C. Álvarez Author-Workplace-Name: Universidad Autónoma de Madrid Author-Email: inmaculada.alvarez@uam.es Author-Person: pal460 Title: Fitting spatial stochastic frontier models in Stata Journal: Stata Journal Pages: 402-426 Issue: 3 Volume: 24 Year: 2024 Month: September Abstract: In this article, we introduce a new command, xtsfsp, for fitting spatial stochastic frontier models in Stata. Over the last decades, stochastic frontier models have seen important theoretical progress via the incorporation of various types of spatial components. Models that can account for spatial dependence and spillovers have been developed for efficiency and productivity analysis, drawing extensive attention from industry and academia. Because of the unavailability of the statistical packages, the empirical applications of the new stochastic frontier models appear to be lagging. The xtsfsp command provides a procedure for fitting spatial stochastic frontier models in the style of Orea and Álvarez (2019, Journal of Econometrics 213: 556–577) and Galli (2023, Spatial Economic Analysis 18: 239–258), enabling users to handle different sources of spatial dependence. In this article, we introduce spatial stochastic frontier models, describing the syntax and options of the new command and providing several examples to illustrate its usage. Keywords: xtsfsp, stochastic frontier models, SFA, spatial dependence, technical efficiency, spillovers File-URL: http://www.stata-journal.com/article.html?article=st0752 File-Function: link to article purchase X-DOI: 10.1177/1536867X241276109 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj24-3/st0752/ Handle:RePEc:tsj:stataj:v:24:y:2024:i:3:p:402-426 Template-Type: ReDIF-Article 1.0 Author-Name: David M. Drukker Author-Workplace-Name: Clemson University Author-Email: ddrukke@clemson.edu Author-Person: pdr184 Author-Name: Kevin S. S. Henning Author-Workplace-Name: Sam Houston State University Author-Email: henning@shsu.edu Author-Name: Christian Raschke Author-Workplace-Name: Sam Houston State University Author-Email: raschke@shsu.edu Author-Person: pra598 Title: Tests and confidence bands for multiple one-sided comparisons Journal: Stata Journal Pages: 446-477 Issue: 3 Volume: 24 Year: 2024 Month: September Abstract: One-sided inference should be used in some applications, but Stata has limited support for one-sided tests and confidence intervals for a single compari- son and almost no support for one-sided tests and confidence bands for multiple comparisons. In this article, we provide an introduction to one-sided tests and confidence intervals for a single hypothesis and to one-sided tests and confidence intervals for multiple comparisons. We also discuss extensions of the sotable com- mand introduced in Drukker (2023, Stata Journal 23: 518–544) to cover one-sided tests and confidence bands for a single comparison and for multiple comparisons. We also provide examples of how to use sotable to perform multiple tests against values other than zero and how to perform multiple tests after commands like margins and nlcom that support the post option. Keywords: sotable, one-sided testing, multiple comparisons, confidence bands, simultaneous inference, multiple testing, max-𝑡, simultaneous tests File-URL: http://www.stata-journal.com/article.html?article=st0718_1 File-Function: link to article purchase X-DOI: 10.1177/1536867X241276111 Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj24-3/st0718_1/ Handle:RePEc:tsj:stataj:v:24:y:2024:i:3:p:446-477 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: Stata tip 156: Concentration and diversity measures using egen Journal: Stata Journal Pages: 535-545 Issue: 2 Volume: 23 Year: 2024 Month: September File-URL: http://www.stata-journal.com/article.html?article=st0756 File-Function: link to article purchase DOI: 10.1177/1536867X241276115 Handle:RePEc:tsj:stataj:v:24:y:2024:i:3:p:535-545 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: Stata tip 157: Adding extra lines to graphs Journal: Stata Journal Pages: 546-550 Issue: 2 Volume: 23 Year: 2024 Month: September File-URL: http://www.stata-journal.com/article.html?article=gr0097 File-Function: link to article purchase DOI: 10.1177/1536867X241276115 Handle:RePEc:tsj:stataj:v:24:y:2024:i:3:p:546-550