Stata JournalPub Date : 2022-06-01DOI: 10.1177/1536867x221106458
S. Weber
{"title":"Software Updates","authors":"S. Weber","doi":"10.1177/1536867x221106458","DOIUrl":"https://doi.org/10.1177/1536867x221106458","url":null,"abstract":"gr0066_3. Speaking Stata: Multiple bar charts in table form. N. J. Cox. Stata Journal 20: 757; 17: 779; 16: 491–510. A bug has been fixed whereby a call to the note() option could be thrown if the user had set dp comma. The help file has been updated to include further references, both ancient and modern. st0507_1: Testing for Granger causality in panel data. L. Lopez and S. Weber. Stata Journal 17: 972–984. In the previous version, we used the display directive “input” to print the final results, which overrode the quietly command. We have now replaced all occurrences of as input with the boldface SMCL tag {bf:}.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":"22 1","pages":"467 - 467"},"PeriodicalIF":4.8,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45134069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stata JournalPub Date : 2022-04-01DOI: 10.1177/1536867X221124553
E. Norton
{"title":"The inverse hyperbolic sine transformation and retransformed marginal effects","authors":"E. Norton","doi":"10.1177/1536867X221124553","DOIUrl":"https://doi.org/10.1177/1536867X221124553","url":null,"abstract":"In this article, I show how to calculate consistent marginal effects on the original scale of the outcome variable in Stata after estimating a linear regression with a dependent variable that has been transformed by the inverse hyperbolic sine function. The method uses a nonparametric retransformation of the error term and accounts for any scaling of the dependent variable. The inverse hyperbolic sine function is not invariant to scaling, which is known to shift marginal effects between those from an untransformed dependent variable to those of a logtransformed dependent variable, when all observations are positive.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":"22 1","pages":"702 - 712"},"PeriodicalIF":4.8,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48888336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stata JournalPub Date : 2022-03-01DOI: 10.1177/1536867X221083927
G. Cerulli, R. Simone, F. Di Iorio, D. Piccolo, Christopher F. Baum
{"title":"Fitting mixture models for feeling and uncertainty for rating data analysis","authors":"G. Cerulli, R. Simone, F. Di Iorio, D. Piccolo, Christopher F. Baum","doi":"10.1177/1536867X221083927","DOIUrl":"https://doi.org/10.1177/1536867X221083927","url":null,"abstract":"In this article, we present the command cub, which fits ordinal rating data using combination of uniform and binomial (CUB) models, a class of finite mixture distributions accounting for both feeling and uncertainty of the response process. CUB identifies the components that define the mixture in the baseline model specification. We apply maximum likelihood methods to estimate feeling and uncertainty parameters, which are possibly explained in terms of covariates. An extension to inflated CUB models is discussed. We also present a subcommand, scattercub, for visualization of results. We then illustrate the use of cub using a case study on students’ satisfaction for the orientation services provided by the University of Naples Federico II in Italy.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":"22 1","pages":"195 - 223"},"PeriodicalIF":4.8,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47263297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stata JournalPub Date : 2022-03-01DOI: 10.1177/1536867X221083931
P. Dickman, E. Coviello, A. Borin, M. Mancini
{"title":"Software Updates","authors":"P. Dickman, E. Coviello, A. Borin, M. Mancini","doi":"10.1177/1536867X221083931","DOIUrl":"https://doi.org/10.1177/1536867X221083931","url":null,"abstract":"There have been several enhancements to the strs command. The using file can now be read from the web. Two new options, cilog and noconfirm, have been added. indweight() now gives warning messages if weights are zero, missing, or negative. There have been various minor bug fixes. The official support page, http://pauldickman.com/software/ strs/history/history/ , provides the complete version history.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":"22 1","pages":"238 - 241"},"PeriodicalIF":4.8,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42024874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stata JournalPub Date : 2022-03-01DOI: 10.1177/1536867X221083857
Sylvain Weber, Martin Péclat, August Warren
{"title":"Travel distance and travel time using Stata: New features and major improvements in georoute","authors":"Sylvain Weber, Martin Péclat, August Warren","doi":"10.1177/1536867X221083857","DOIUrl":"https://doi.org/10.1177/1536867X221083857","url":null,"abstract":"The community-contributed command georoute is designed to calculate travel distance and travel time between two addresses or two geographical points identified by their coordinates. Since its conception and description by Weber and Péclat (2017, Stata Journal 17: 962–971), the command has been gradually maintained and enriched. The new version of georoute presented in this article encompasses major improvements, such as the possibility to specify transport mode and departure time. The new features open the way to a multitude of more sophisticated research applications.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":"22 1","pages":"89 - 102"},"PeriodicalIF":4.8,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45069219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stata JournalPub Date : 2022-03-01DOI: 10.1177/1536867X221083854
M. Cococcioni, Marco Grazzi, Leyan Li, F. Ponchio
{"title":"A toolbox for measuring heterogeneity and efficiency using zonotopes","authors":"M. Cococcioni, Marco Grazzi, Leyan Li, F. Ponchio","doi":"10.1177/1536867X221083854","DOIUrl":"https://doi.org/10.1177/1536867X221083854","url":null,"abstract":"In this work, we describe the new command zonotope, which, by resorting to a geometry-based approach, provides a measure of productivity that fully accounts for the existing heterogeneity across firms within the same industry. The method we propose also enables assessment of the extent of multidimensional heterogeneity with applications to fields beyond that of production analysis. Finally, we detail the functioning of the software to perform the related empirical analysis, and we discuss the main computational issues encountered in its development.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":"22 1","pages":"25 - 59"},"PeriodicalIF":4.8,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42036023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stata JournalPub Date : 2022-03-01DOI: 10.1177/1536867X221083929
Ariel Linden
{"title":"Erratum: A comprehensive set of postestimation measures to enrich interrupted time-series analysis","authors":"Ariel Linden","doi":"10.1177/1536867X221083929","DOIUrl":"https://doi.org/10.1177/1536867X221083929","url":null,"abstract":"The article “A comprehensive set of postestimation measures to enrich interrupted time-series analysis”, by Ariel Linden ( Stata Journal 17: 73–88), contains the following errors.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":"22 1","pages":"231 - 233"},"PeriodicalIF":4.8,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47256030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stata JournalPub Date : 2022-03-01DOI: 10.1177/1536867X221083902
W. Vach, Cornelia Alder, Sandra Pichler
{"title":"Analyzing coarsened categorical data with or without probabilistic information","authors":"W. Vach, Cornelia Alder, Sandra Pichler","doi":"10.1177/1536867X221083902","DOIUrl":"https://doi.org/10.1177/1536867X221083902","url":null,"abstract":"In some applications, only a coarsened version of a categorical outcome variable can be observed. Parametric inference based on the maximum likelihood approach is feasible in principle, but it cannot be covered computationally by standard software tools. In this article, we present two commands facilitating maximum likelihood estimation in this situation for a wide range of parametric models for categorical outcomes—in the cases both of a nominal and an ordinal scale. In particular, the case of probabilistic information about the possible values of the outcome variable is also covered. Two examples motivating this scenario are presented and analyzed.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":"22 1","pages":"158 - 194"},"PeriodicalIF":4.8,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41553455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}