Use vl move to move variables among classifications. To vlcategorical, vlcontinuous, or vlother. If there are any variables in vluncertain, you can reallocate them Type vl list vlcategorical and type vl list vlcontinuous.Ģ. Review contents of vlcategorical and vlcontinuous to ensure they areĬorrect. $vlother | 0 all missing or constant variablesġ. $vluncertain | 7 perhaps continuous, perhaps categorical variables To begin using variable lists, vl set must be run. For example, to calculate the average difference in price between foreign and domestic cars 16: You can save any piece of it using a macro. However, as soon as you run another r-class command, you lose access to the first one. So if you run a summarize command, then do a bunch of n-class calls ( gsort for example), the return list call will still give you the returns for that first summarize. Rather than try and keep track of what gets stored where, if you look at the very bottom of any help file, it will say something like “ summarize stores the following in r():” or “ mean stores the following in e():”, corresponding to return and ereturn respectively.Īlong with the One Data principal, Stata also follows the One _-class principal - meaning you can only view the return or ereturn for the most recent command of that class. On the other hand, mean (which we haven’t discussed, but basically displays summary statistics similar to summarize but provides some additional functionality) is an e-class command, storing its results in ereturn: Here, summarize is a r-class command, so it stores its returns in “return”. The distinction between the two is inconsequential, besides that they store their “returns” in different places. The two common ones are e-class and r-class. Some are c-class, which are only used by programmers and rarely useful elsewhere.
Some commands are n-class, which means they don’t return anything. One major aspect of the type is what the command “returns”. The differences between including and excluding the = are mostly unimportant, so I recommend sticking with the = unless you specifically need the other version.Įvery command in Stata is of a particular type.
You may occasionally see code that excludes the = in defining a macro (e.g. You can use display to print the content of macros to the output to preview them. Local pricelab = "Price (in dollars) at Time Point" Label variable price2 "Price (in dollars) at Time Point 2" Label variable price1 "Price (in dollars) at Time Point 1"
If your macro contains text that should be quoted, you still need to quote it when accessing. Important: Local macros are deleted as soon as code finishes executing! That means that you must use them in a do-file, and you must run all lines which create and access the macro at the same time, by highlighting them all. Stata immediately replaces `vars’ with var1 var2 var3 var4 var5, then executes Whenever it is referred to, wrapped in a backtick (to the left of the 1 key at the top-left of the keyboard) and a single quote, Stata replaces it with the original text. The first command, local, defines what is known as a “local macro” 15. Instead, we can store the list of variables (strictly speaking, the string which contains the list of variables) in a shorter key string, and refer to that instead! You could copy and paste a lot, but even that takes a lot of effort. This can get extremely tedious as the number of variables and commands increases. Label values var1 var2 var3 var4 var5 mylab Imagine the following scenario: You have a collection of 5 variables that you want to perform several different operations on. While variables stored as strings aren’t of much use to us, strings stored as other strings can be quite useful. 5.8.2 Converting strings into labeled numbers.5.8.1 Converting between string and numeric.5.8 Working with strings and categorical variables.3.6.1 Temporarily preserving and restoring data.3.5.3 Importing from a file not supported directly by Stata.