Teaching your course with Stata provides your students with tools and skills that translate to their professional lives. Stata is affordable, is easy to use and learn, and provides all the statistics, data manipulation, visualization, and reporting that your students need. ...
in a single step, estimate parameters using the imputed datasets, and combine results. Fit a linear model, logit model, Poisson model, multilevel model, survival model, or one of the many other supported models. Use themicommand, or let the Control Panel interface guide you through your enti...
OurYouTube channelis full of videos and short tutorials that can assist you and your class with using Stata. Browse all our video tutorial playlists bysubjecton the Stata website or bydisciplineon YouTube. Our freeReady. Set. Go Stata.webinar is a great way to introduce new users to Stata...
However, these recent advances have progressed quickly with a relative paucity of computational-oriented applied tutorials contributing to some confusion in the use of these methods among applied researchers. In this tutorial, we show the computational implementation of different causal inference estimators...
Expository papers that link the use of Stata commands or programs to associated principles, such as those that will serve as tutorials for readers first encountering a new field of statistics or a major new technique. Papers that go “beyond the Stata manual” in explaining key features or uses...
pandas.read_stata(filepath_or_buffer, *, convert_dates=True, convert_categoricals=True, index_col=None, convert_missing=False, preserve_dtypes=True, columns=None, order_categoricals=True, chunksize=None, iterator=False, compression='infer', storage_options=None) ...
This has changed, of course, with the introduction of the %>% forward-pipe operator. Stata 16 features a frame command that aims at allowing users to manipulate multiple datasets, hopefully in ways less clunky than the previous tricks and workarounds that all Stata users had to rely upon ...
IntroductionMultiple regression (an extension of simple linear regression) is used to predict the value of a dependent variable (also known as an outcome variable) based on the value of two or more independent variables (also known as predictor variables). For example, you could use multiple ...
IntroductionThe one-way analysis of variance (ANOVA) is used to determine whether the mean of a dependent variable is the same in two or more unrelated, independent groups. However, it is typically only used when you have three or more independent, unrelated groups, since an independent-...
The third edition of Regression Models for Categorical Dependent Variables Using Stata continues to provide the same high-quality, practical tutorials of previous editions. It also offers significant improvements over previous editions—new content, updated information about Stata, and updates to the autho...