What does it tell you about age that it is never missing? What is a level one unit in this data set? What is a level two unit? Which variables are level one variables?
Which are level two variables? Most of the techniques we learned for working with individuals in household carry over directly to panel data. For example, to find the total income earned during the study period, run:. But what if you wanted to know their income the first time they appear in the study? Recall that income[1] means "the value of income for the first observation. You need to be careful because Stata's default sorting algorithm is not stable.
This means it will put ties in whatever order will make it run fastest. So if you run sort id , or bysort id: , the observations for each person could be in any order. In practice, if the data are already sorted or mostly sorted the order that will make the sort run fastest is usually to leave things alone.
But you can't count on that. So if you're going to run code that depends on the sort order, be sure the data are actually in the right order. Exercise: Create endingIncome , the subject's income the last time they appear in the study. Sometimes you need to carry out calculations that take into account not just the current observation, but neighboring observations. The edu variable is missing for years where the subject was not interviewed.
In many cases the subject's level of education is the same before and after the gap and it would be safe to fill in those values. We'll start by filling them in "forwards", meaning that value of edu before the gap is carried forward to fill in the missing values. Make a copy of the variable so we can compare the new version with the original:.
The alternative is to fill edu in "backwards", meaning that the value of edu after the gap is carried backwards. However, that won't work because of the order in which Stata carries out a replace command. In carrying out a replace command, Stata updates the observations in order starting from the first observation. Imagine a hypothetical subject who has observed values for edu in year one and year four, but not years two and three. When filling in "forwards", Stata first sets edu for year two to the value of edu for year one, then sets edu for year three to the value of edu for year two, which was carried forward from year one.
If you tried to fill in "backwards" in the same way, edu for year two would be set to the value of edu for year three, which is missing.
Then edu for year three be set to the value of edu for year four, but at that point it's too late to fill in the value for year two. This does not mean it's impossible to fill in "backwards. The gsort "generalized sort" command will sort observations in descending order rather than ascending order if you put a minus sign in front of the variable name.
Thus this code puts the observations for each subject in reverse chronological order, fills in the eduBackward variable, and then puts them back in chronological order. In most cases eduForward and eduBackward are the same, but subject number 1 is an exception: because subject 1 was never observed after , eduForward fills in 12th grade for all the remaining years, while eduBackward still has missing values.
Subject number 23 illustrates a different problem: they reported 3 years of college in , then were lost until when they reported 6 years of college. Some time during the seven years in between they attended three years of college. The safe thing is to only use filled in values when edu is the same before and after the gap, and thus eduForward is the same as eduBackward :. Exercise: create an indicator for "the subject attended school this year.
The variable should be missing if edu is missing for the current year or the year before. This will also lead to the indicator variable being missing for the first observation for each subject This makes sense, but how did Stata know to do it? Many languages would give an error message like "index out of bounds" at this point. This highlights the reason we need by id: for this command. If we did not have it, Stata would try to determine if a subject attended school in by comparing their education level in to the previous subject's education level in Having by id: in front of the command ensures each subject is handled separately.
Often with panel data you'll need to identify particular events or sequences of events. For example, suppose you need to identify the year in which each subject graduated from high school. A subject graduated from high school in a given year if they have 12 years of education in that year and less than 12 years of education the year before:.
So a one for grad technically means "We know the person graduated this year" while a zero means "We don't know that the person graduated this year. When an indicator variable indicates that an event happened, the total of that variable is the number of times the event happened. To check your work, determine how many times each subject graduated from high school:. Many subjects graduated zero times, but this is not surprising: either they really didn't graduate, or they graduated outside the study period, or missing data prevented you from identifying the year in which they graduated.
Fortunately, no one graduated more than once. This could happen due to a data entry or reporting error and then you'd have to fix it. Next create an indicator for "subject took a break from college. Now, create an indicator variable to identify people who took a break from college at some point in the study:.
To see the results, run browse id year edu break tookBreak if tookBreak. Exercise: Our current definition of taking a break from college includes dropping out of college permanently. Create a person-level indicator variable for "this person finished college" i.
Then modify the above commands so that only people who finish college are counted as taking a break from college. Suppose you are interested in the effect of taking a break from college on subsequent outcomes, so you need to identify all the years after a subject took a break from college. Do so with:. Remember, the construction if indicatorVariable only works properly if indicatorVariable has no missing values.
It asks for the value of break for the observation before the first observation, which does not exist. Now suppose you need to know the number of "break" years the subject has taken, as of the current year. This will be the running sum of the break variable, where a running sum is the sum of all the observations up to and including the current observation.
The sum function calculates running sums, and is very useful any time you need to calculate how many times a subject has experienced an event. You might expect sum to be an egen function since it acts across observations, but in fact it's a standard function since it only needs to look at prior observations. Exercise: Create an indicator variable that identifies those years that come after a break but before the subject graduates from college, meaning that edu is less than This same result as above can be achieved using the foreach command.
The example below illustrates how to compute the quarterly income variables incqtr1-incqtr4 using the foreach command. In this example, instead of cycling across variables, the foreach command is cycling across numbers, 1, 2, 3 then 4 which we refer to as qtr which represent the 4 quarters of variables that we wish to create.
The trick is the relationship between the quarter and the month numbers that compose the quarter and to create a kind of formula that relates the quarters to the months. This is what the statements below from the foreach loop are doing.
They are relating the quarter to the months. Then, imagine all of those values being substituted into the following statement from the foreach loop. In this example, with only 4 quarters of data, it would probably be easier to simply write out the 4 generate statements manually, however if you had 40 quarters of data, then the foreach loop can save you considerable time, effort and mistakes.
The foreach command can also be used to identify patterns across variables of a dataset. To obtain this information, dummy indicators can be created to indicate in which months this occurred. Note that only 11 dummy indicators are needed for a 12 month period because the interest is in the change from one month to the next. This program is illustrated below note for simplicity we assume no missing data on income. In the above example, if I type. For online help, type help order in Stata, or see [D] order.
Checkout Continue shopping. Stata: Data Analysis and Statistical Software. Go Stata. Purchase Products Training Support Company. How can I list, drop, and keep a consecutive set of variables without typing the names individually?
Title Shortcuts to refer multiple variables Author Paul Lin, StataCorp Understand that whenever Stata wants a varlist it can be a list of variables, such as.
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