#STATA IF ELSE HOW TO#

Changing the contents of the macro age at a later time does not change the contents of the macro controls. Stata sees that it includes the macro age and substitutes the current value of age. For example if you define local controls `age' income education. If a macro includes macro evaluations, these are resolved at the time the macro is created, not when it is evaluated. Note that the first occurrence of age here is the name of the macro and the second is the name of a variable. This also makes it easier to change the representation of age if you later decide to use linear and quadratic terms instead of the six dummies all you do is define local age 'age agesq' and rerun your models. Which is not only shorter and more readable, but also closer to what you intend, which is to regress ceb on вЂњageвЂќ, which happens to be a bunch of dummies. Define a macro local age 'age20to24 age25to29 age30to34 age35to39 age40to44 age45to49'ДЄnd then in your regression models use something like regress ceb `age' urban Suppose you are working with a demographic survey where age has been grouped in five-year groups and ends up being represented by seven dummies, say age15to19 to age45to49, six of which will be used in your regressions. But you always check your output, right? Example: Managing Dummy Variables Either way, the regression will run without any controls. The same would happen if you type `control' because macro names cannot be abbreviated the way variable names can. If you type regress outcome treatment `contrls', Stata will read regress outcome treatment, because the macro contrls does not exist. So be careful to spell macro names correctly. Warning: Evaluating a macro that doesnвЂ™t exist is not an error it just returns an empty string. This approach also has the advantage that if later you realize that you should have used log-income rather than income as a control, all you need to do is change the macro definition at the top of your do file, say to read logincome instead of income and all subsequent models will be run with income properly logged (assuming these variables exist). If thereвЂ™s only one regression to run you havenвЂ™t saved anything, but if you have to run several models with different outcomes or treatments, the macro saves work and ensures consistency. Which in this case is exactly equivalent to typing regress outcome treatment age agesq education income. You then type commands such as regress outcome treatment `controls' The smart way is to define a macro local controls age agesq education income You could, of course, type these names in each equation, or you could cut and paste the names, but these alternatives are tedious and error prone. You need to run a bunch of regression equations that include a standard set of control variables, say age, agesq, education, and income. Example: Control Variables in Regression. The text is often enclosed in quotes, but it doesnвЂ™t have to be. The first variant, without an equal sign, is used to store arbitrary text of up to ~64k characters (up to a million in Stata SE). (Note the use of a backtick or left quote.) You define a local macro using local name text and you evaluate it using `name'. Local macros have names of up to 31 characters and are known only in the current context (the console, a do file, or a program).

4.1 MacrosДЄ macro is simply a name associated with some text. Other resources were listed in Section 1 of this tutorial.

Nick CoxвЂ™s regular columns in the Stata Journal are a wonderful resource for learning about Stata. You may also find useful Chapter 18 in the UserвЂ™s Guide, referring to the Programming volume and/or the online help as needed. To learn more about programming Stata I recommend Kit BaumвЂ™s An Introduction to Stata Programming, now in its second edition, and William GouldвЂ™s The Mata Book. Your efforts here will not be wasted, however, because the options are complementary to, not a complete substitute for, classic Stata programming. All of these languages are beyond the scope of this introductory tutorial. In addition, it is possible to write Stata plugins in C or Java. Stata 9 introduced a new and extremely powerful matrix programming language called Mata, and Stata 16 expanded the choice of languages by integrating Python. However, the material covered will help you use Stata more effectively. This is a large subject and all I can hope to do here is provide a few tips that hopefully will spark your interest in further study.

#STATA IF ELSE HOW TO#

I discuss macros and loops, and show how to write your own (simple) programs. This section is a gentle introduction to programming Stata. Introduction Data Management Graphics Programming 4 Programming Stata

Stata if else