NetCourseNow 251: Writing your own Stata commands

$325.00Self-paced

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Learn how to create and debug your own commands that are indistinguishable from the commands in Stata. You will be able to parse both standard and nonstandard Stata syntax using the intuitive syntax command, to manage and process saved results, to post your own saved results, to process by-groups, to create data management commands, to program your own maximum-likelihood estimator, and more. In short, learn to create commands that act just like the commands that ship with Stata.

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Discounts available for enrollments of two or more participants.

Prerequisites

Stata 19 or Stata 18, installed and working
Course content of NetCourse 151 or equivalent knowledge
Internet web browser, installed and working
(course is platform independent)

Course content

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Lesson 1: Parsing Stata syntax/Stata programming basics

Review of Stata’s programming features
Parsing
Parsing options
Parsing complicated syntax
Aside on subprograms

Lesson 2: Parsing Stata syntax, continued: Quotes, returned results, and subsamples

Quotes
Development continues
Temporary variables
Development continues
An aside concerning r()
Programming the formulas
Putting it together

Lesson 3: Using scalars and macros and introduction to low-level parsing

What you must learn
Scalars
Binary accuracy
Accuracy of macros versus scalars
Converting a program from macros to scalars
Handling by() options
Sorting
Low-level parsing
Programming immediate commands
Rewriting mytt in terms of mytti
Parsing new variables

Lesson 4: Returning results and writing estimation commands

Where are we?
Stored results
What can be returned in r()?
Referring to returned results in other programs
Referring to returned results in the program that sets them
Other types of returned values: s() and e()
S-class returned values
E-class returned results
Writing postestimation commands
Writing an estimation (e-class) command
An alternative estimation command outline
Writing estimation commands from first principles
Writing estimation commands via maximum likelihood

Lesson 5: List processing, controlling program output, and naming conventions

Restricting commands to the relevant subsample
Which is better: marksample or mark?
Programming by varlist:
Lists
Creating lists
Stepping through list elements one by one
Deleting elements from lists
Adding elements to lists
Macro vectors
Parsing revisited: gettoken
quietly blocks
The relation between capture and quietly
capture blocks
Naming conventions
Program-naming convention
Calling convention
Version control

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