An Introduction to Stata Exercise 1

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1 An Introduction to Stata Exercise 1 Anna Folke Larsen, September Table of Contents 1 Introduction Initial options Reading a data set from a spreadsheet Descriptive statistics Save and load data Generate new variables... Error! Bookmark not defined. 1 Introduction Stata is a very useful statistical software package for conducting a wide range of econometric estimations. One major advantage of Stata is the possibility for users to write and share user-written procedures which make econometric estimations very easy. These notes work as an introduction to Stata and as a complement to the do-file E1_ex_ante.do. We will use data from a small survey which we conduct in the beginning of the class. Stata differs from many other programs that you work with because it is using and saving several files in different file formats. For instance, when you are working in word you usually work in a word file (maybe with the.docx file format) and you may even think of the file and the program as the same thing. However, in Stata it is important to keep track of the different types of files, what they are used for and how and where we save them. If you are new to Stata it is a good idea to have one folder where you keep all the files associated with Stata. Create a folder where you want to keep your Stata stuff. This will be your working directory. Within that folder, create three subfolders: data, dofiles and logs. You will eventually have four different types of files: The Excel file with the survey data (survey_class1_2.xls) The Stata do-file (Dofile_exercise1.do) The Stata data-file (mysurvey.dta) The log file (exercise1.log / exercise1.txt) 2 1 Based on an Introduction to Stata by Daniel le Maire, October 2012

2 The.xls file is the file with your raw data; the data you typed into the spreadsheet. We are not going to make changes to this data from Stata. In general, it is nice always to keep a copy of your raw data which you never work with, because if you make a mistake and delete or change something, you would like to be able to recover your raw data. The.do file is where you are doing the actual programming, that is, telling Stata what to do with the data. The nice thing about writing a program instead of clicking around in Stata is that we are able to stay organized about the order of the things we do and we can easily replicate it. You will be working with the do-file within the do-file editor as described below and you save the do-file within the do-file editor. This is very much like working with any other text file, you are just writing things in a different language. The.dta file is the data file in Stata format. Once we make changes to the data we imported from Excel, e.g. creating new variables or changing existing ones, we may want to save it to be able to use the altered data later on. We like to do that within the do-file with a save command (more about that below). If we click the save icon or use CTRL+S when we are in the output window, Stata will save the data (or ask if you want to overwrite the existing data if you already saved the data in.dta format). The reason why we prefer not to save the data from the output window is because we want to keep track of what we have done to the data before we save it. That is exactly what we can do within the do-file. If you make changes to the data in the do-file and do not save the data before closing down your Stata session, Stata will ask you if you want to save the changes you made to the data. If you would want to save it, you should have done it within the dofile. Otherwise, just close without saving. The.log (.txt) file is a file that contains everything you see in the output window. It is just plain text so you can open it with notepad or another text program and see the work you did, both the code from the do-file and the output Stata gives. This is useful for reviewing what you have done, and can also be useful for sharing your results with others. The log file is created within the do-file by opening a log (see below) and it is also saved within the do-file by closing the log in the very bottom of the do-file as explained below. Then you can find it as a text file in your working directory. Once you are a bit more experienced you may want to organize yourself differently. For now, it is convenient to stay organized this way. Within the Stata do-file we will be writing programming language. You can think about this as learning a new language. Be aware that as opposed to other language classes, spelling mistakes and commas in the right places are crucial for Stata to understand you! Everytime we want Stata to do something, we use a Stata command. Every command has its own syntax and most commands have different options you may want to use. These notes will not contain an exhaustive list of options which are possible to use in connection with each Stata command. There are two reasons for this. First of all, Stata s help is very user-friendly. Second of all, most of Stata s commands have the same following structure: 2 For some reason, you should use the file extension.log when you name a log file in Stata, and it will be saved in a.txt format.

3 command [varlist] [if exp] [in range] [weight] [, options] where the terms in brackets are not always required: varlist specifies the variables to be used by the specific command. If no variables are specified all variables will be used. if exp (expressions) are used to select the appropriate observations to be used by the command (if any). in range: Specifies the range of observations to be used (if any). weight: Specifies the weighting scheme to be used (if any). options are specific to the command (if any). Rather than listing all options etc. the reader is encouraged to check Stata s help. There are two ways of accessing Stata s help. From the menu one can select Help. Alternatively, one can use the command line to write help and enter. If one needs help for a specific command, say, summarize then write help summarize. Actually, when you are new to Stata, look at the help file every time you use a new command. That helps you get acquainted not only with the new command, but also with the structure of the help entries. This enables you to quickly learn about new commands. 2 Initial options It is possible to execute one command at a time by using the command line and this can sometimes be useful when developing the code. However, we can also write a program where we can execute all or part of the code. In Stata the program file is called a do-file. When opening Stata you can find the do-file editor under the icon or by selecting the Window menu and subsequently Do-file Editor or just use the short-cut key CTRL+8. You can also write doedit ( or doe) in the command line. Within the do-file editor you can run commands in different ways: You can click the Execute (do) icon, or you can use the short-cut CTRL+D (on mac: +SHIFT+D). If you want to run part of the code you can highlight it and click Execute or press CTRL+D. This is very useful when developing code. It is a good idea to start a do-file with your name and date and maybe also write down the purpose of the do-file. This becomes convenient when you have many do-files or share your do-files with others. It is always a good idea to clear the memory when we start a new do-file. clear all The main window of Stata is the Results window. Here you can see both the commands from the do-file and the output. We can save these results in a log file which is often times useful. Stata can only have one log file open at the same time. Therefore, we cannot create a new log without closing an existing log. Hence, it is a good idea to begin the do-file by closing any open log file. We do this by writing capture log close Next, we create the log file. We need to specify in which folder we want the log file saved. You can name the log file whatever you prefer, but you should use the extension.log. Finally, we need to tell Stata that every time we run the program the log file should be replaced.

4 log using "C:\Stata\logs\exercise1.log", replace However, if we are going to use a special folder for data and log files it is useful to specify such folder in order to avoid writing the whole path every time we want to read or write a file from this folder. We create a directory by writing cd (shorthand for change directory) and the particular folder. If you have difficulties finding the path for the folder, you can use click and play : File Change working directory Browse to find the folder where your data is stored and where you want to store the log file, click on it and click OK. Now Stata has changed the working directory. If you want to be able to do it again without clicking around, you can find the command in the command window. If you click it, you will get the command in the command line and from here you can copy it and paste it into your do-file editor. cd "C:\Stata\" Then, we can write log using "logs\exercise1.log", replace When using a log file we should end the do-file by closing the log, that is log close When running a Stata do-file or any Stata command the Results window will pause until you press a key in order to let you follow the stream of output as Stata performs the estimations. To avoid this you can write set more off In some cases Stata allows us to use a shorter notation. Therefore, let us repeat all the commands but in the short form. clear all cap log c cd "C:\Stata\" log using "logs\exercise1.log", replace set more off And then at the end of the do-file: log c By the way, the do-file editor uses colors to make things easier to read. commands are in dark blue *comments are in green "strings are in red" A final note before we get really started is on how Stata reads your code. Each line is considered a command. Sometimes you want to add comments in your own language to remember what the code is doing or to structure your do-file. This is actually a really good idea, because you often return to old code and it helps you understand what you are doing and why. There are different ways to make comments. You can either start the line with an asterix, then Stata will not read the line. Or you can write slash asterix /* then Stata will not execute what you are writing before you end the comment with asterix slash */. You can

5 also use double slash // to start a comment on the same line as a command, e.g. to describe the command. Each line is a command but sometimes the commands get really long and you want to split it into several lines for readability. Triple slash /// at the end of a line tells Stata to continue the command on the following line. 3 Reading a data set from a spreadsheet In order to import data to Stata from a spreadsheet, we first need to make sure that the spreadsheet file is saved in the.xls format. Next, we can either import it by click and play or using the do-editor. Using click and play, choose: File Import Excel spreadsheet. This opens a window where you browse to find the.xls file you want to import. Tick the option: Import first row as variable names. Then click OK. Now, we made Stata do what we wanted, but we would like to be able to replicate it. Luckily, Stata provides the command in the command window and we can copy and paste it into the do-file editor: import excel "data\firstsurvey.xls", sheet("sheet1") firstrow Having the code in the do-file editor allows us to simply execute the do-file to import the data from excel instead of doing the click and play over again. This is convenient if we want to import the data again. If we want import another data set from excel we can just change the file name in the code. To see the values in the data set we can from the toolbox just above the Results window select either the Data Editor or the Data Browser. Alternatively, we can write either edit or browse in the Command Line Window. It is only in very rare occasions that we wish to change the data without writing this as code and we certainly don t want to do it by mistake. So the Data Browser is the most attractive option. Furthermore, often it is only of interest to see a subset of variables and if we want to see for example the person id (pid), the name (name) and the age (age) we simply write in the command line browse pid name age A nice way to get a quick overview of the data is to simply write describe This yields an overview of the number of observations and variables and the format of the different variables. 4 Descriptive statistics We can display simple descriptive statistics with the use of the summarize function. If we want to see descriptive statistics for all of our variables we should just write summarize and as with some of the functions we just need to write su to invoke the summarize function. We can also specify a subset of variables for which summary statistics should be calculated su age

6 If we want to summarize several variables it is sometimes nice to use a variable list. A list can simply be the names of the variables with a space in between as above, but we can also do the following su age-height Now we summarize all variables between age and height. We can also use the wildcard * which can be used in the beginning, middle or end of a variable name. su h* The summarize command is not well suited for all kinds of variables. We some from using the describe command that some variables are string variables: the storage type is str# meaning that stata understands the variable as text (with max # letters). For instance, it doesn t really make sense to calculate the mean and standard deviation of the name. Instead we can use the codebook command codebook name For the categorical variables such as house and location summarize is also not the best way to look at them. Rather we would want to tabulate the different options people chose. We can do that easily tabulate house tabulate location If we wanted to that write that shorter, we could use the tab instead of tabulate. When we want to tabulate several variables we can use the tab1 command: tab1 house location If we write two variables in the tab command, Stata will make a cross-tabulation. This would be useful if we were interested in knowing what type of housing is common in different parts of Copenhagen. tab house location If we do not have many observations we can also simply just list a variable. This corresponds to looking at the variable in the data browser (using the command browse or shorthand br), but the virtue of the list command is that we get the listed data into the log file. That can be nice if we want to have one single log file with all the important information inside. list house When we look at the variables, we currently need to look at the questionnaire to remember what the variables are. Instead, we can also add labels in Stata so the data is more self-explanatory. First, we assign the label Type of housing to the variable house label var house "Type of housing" Then we may also want to assign a value label to the values of the categorical variable, such that we can remember which number refers to which type of housing. First we have to define the value label label define HOUSE_VAL 1 "Apartment" 2 "Dorm" 3 "House" 4 "Other"

7 I use capital letters for the name of the value label (HOUSE_VAL) in order not to mix it up with variable names where I usually use lower case letters. Next we need to assign the value label to the variable house. label values house HOUSE_VAL When you tabulate house or look at the variable in the data editor (browse) you now see the labels. 5 Save and load data We can save the data set in a Stata format by writing save mysurvey.dta, replace As Stata data sets have the extension.dta this will create a Stata data set. It is saved in the folder we chose in the beginning using the cd command. In order to save it in a different folder, we need to specify the path within a string, e.g. save C:\Different folder\mysurvey.dta, replace If there are spaces in the path we have to use the quotation marks "" to tell Stata that it is a string. But even though there are no spaces it is nice to use them because they change the string into red which makes the code easier to read. 6 Keeping and dropping It is always possible to throw away observations or variables by using keep or drop. Now that we just saved the data set we can have fun throwing away observations or variables. Here we drop the two variables roomsize and location (recall, these are columns in the data). drop roomsize location If we want to drop many variables, maybe it is easier just to write the few variables that we are interested in keeping: keep pid age wc Maybe we also want to drop some observations (rows in the data). Say, we are not interested in informants who do not have their own toilet drop if wc==2 Note, that after the if statement we use two equality signs. Only using one equality sign is a typical mistake. Here is a small useful scheme for if statements:

8 After if (logical operators) Combining several if statements Equal to == And & Not equal to!= Or Var larger than # Var># house>2 Var smaller than # Var<# house<2 Var larger than or equal to # Var>=# House>=2 Var smaller than or equal to # Var<=# House<=2 Example of how to combine two if statements: drop if wc==2&house!=1 When using & in this case we are only dropping observations who share a toilet and do not live in an apartment. If we did it in two statements we would also drop those who share a toilet in an apartment: drop if wc==2 drop if house!=1 If statements can be tricky, so always check be browsing or tabulating whether you dropped or kept the observations you wanted. Now that we have dropped most variables and observations, let s read the data into Stata again. As we can only have one data set in memory we will clear the memory before reading the data clear all By using the Data Browser you can verify that there no longer is data in memory. If we want to read a stata dataset such as mysurvey.dta, we simply write use mysurvey.dta, clear If we saved the file in a different folder, we should of course specify the path. When we use the clear option we did not have to use the clear all statement before reading the data.

9 There is also a click and play way to open a new data set. If you go to the output window and then click File Open you can browse to find the.dta file you want to open. If you have not cleared the work space first, and you have made changes to the data set which is open Stata will warn you that you are about to lose unsaved data. Saying yes, corresponds to the clear option in the use command.