The objective of TStat Training’s more advanced course is to provide participants with the programming commands and options required to autonomously develop and modify Stata ADO files. The opening session offers a quick overview of the fundamental concepts and commands (macros, vectors, scalers, looping, branching, temporary objects, foreach, forvalues) intrinsic to successful programming development. Session two moves on to illustrate the most effective way to develop a Stata ADO fi le, introducing participants to more specific programming concepts (such as arguments, local subroutines and the temporary storing of results) and Stata’s programming commands tokenize, macro shift, marksample and markout “byable” and sortpreserve. In section three participants are introduced to Stata’s inbuilt matrix capabilities, before moving on in the final session to developing their own programs for linear and maximum likelihood estimators.
In common with TStat’s course philosophy, each session is composed of both a theoretical component (in which the programming techniques are fully explained via a series of course specific developed examples), and an applied (hands-on) segment, during which participants have the opportunity to implement the techniques under the watchful eye of the course tutor.
At the end of the course, it is expected that participants will be able to independently implement both the techniques learnt and personalize the ADO program templates specifically developed during the course in order to enhance the effectiveness of their research.
Researchers or professionals with a good knowledge of the introductory programming skills covered on our A Little bit of Programming goes an Awfully Long Way.. wising to take their Programming skills to the next level in order to be able to program their only Stata ADO files for data analysis and data management and to develop Stata commands for least squares and maximum-likelihood estimators.
It is assumed that participants have a sound working knowledge of Stata and are familiar with the concepts and Stata commands treated in our introductory Stata Programming course: A Little bit of Programming goes an Awfully Long Way..
SESSION I: PROGRAMMING BASICS | A QUICK REVIEW
Macros
Global macros
Local macros
Scalars and matrices
Temporary objects
Looping
Branching
SESSION II: WRITING STATA PROGRAMS
Programming in Stata
Do-files and ADO-files
Writing and modifying a Stata programs
Programs without arguments
Programs with positional arguments
Programs with named positional arguments
Storing and retrieving program results
Programs with arguments using the “syntax” construct
Using tokenize and macro shift
ADO-files
Implementing program options
The return statements
Sample restriction with marksample and markout
Making a command “byable”
The use of sortpreserve
Writing an rclass ADO-file
Implementing program options
Sample restrictions with marksample
The usefulness of markout
Make a program “byable”
The use of sortpreserve
Writing an eclass ADO-file
More on storing results in e()
A eclass program template
Temporarily destroying the data in memory
Local sub-routines
SESSION III: STATA MATRIX CAPABILITIES
Stata matrix commands
Stata matrix input and output
Matrix input from Stata estimation results
Stata matrix subscripts and combining matrices
Matrix operators
Matrix functions
Defining a macro by a matrix function
Matrix accumulation commands
SESSION IV: PROGRAMMING ESTIMATORS
Programming Linear Least Squares estimation
Programming Maximum Likelihood estimation
Some examples
COURSE REFERENCES
An Introduction to Stata Programming, Christopher F. Baum, Second Edition, StataPress 2016
We are currently putting the finishing touches to our 2024 training calendar. We therefore ask that you re-visit our website periodically or contact us at training@tstat.it should the dates for the course which you are interested in following not yet be published. You will then be contacted via email as soon as the dates are available.
ONLINE FORMAT
The objective of TStat Training’s more advanced course is to provide participants with the programming commands and options required to autonomously develop and modify Stata ADO files.