SPSS ALTER TYPE command is mainly used for converting string variables to numeric variables. However, it has other interesting applications as well. This tutorial quickly walks you through those, pointing out some pitfalls, tips and tricks along the way.
You can follow along by downloading and opening holidays.sav but you do need SPSS version 16 or higher for using ALTER TYPE.

SPSS ALTER TYPE Pitfall

Although ALTER TYPE is a great option for getting many things done fast, it has one major shortcoming: if it fails to convert one or more values, it returns system missing values without throwing any warnings or errors.
If this goes undetected, it may severely damage your data and bias research outcomes. And even if you do notice system missing values resulting from ALTER TYPE, it will be hard to track down what (if anything) went wrong because the original values are overwritten.

Playing it Safe

We propose two basic strategies for playing it safe:

• Always copy your variables before converting them. A great tool for cloning many (or all) variables in your data is freely downloadable from Clone Variables.
• Just run ALTER TYPE on your original variables but check the results for system missings immediately afterwards. If they are present and you don't know why, close your data, rerun you syntax up to the suspicious ALTER TYPE command and inspect what values could cause the problem.

SPSS ALTER TYPE - String to Numeric

We'd like to know the average age of our participants but we can't calculate it because age is a string variable in our data. The syntax below first copies and converts it to a numeric variable. We can see that no missing values occur in the result by running DESCRIPTIVES; n is equal to the number of cases in our data.

SPSS ALTER TYPE Syntax Example 1

SPSS ALTER TYPE - String to Date

We now turn to birthday. This is a string variable and we wish to convert it to a date variable. Now, SPSS date variables are numeric variables holding numbers of seconds that are displayed as normal dates. They have several display options, a quick overview of which is found under date format. Note that the string values in birthday correspond to what date values look like if their format is set to DATE11. We therefore must specify DATE11 in ALTER TYPE (step 3 below) for converting birthday to a date variable.

SPSS ALTER TYPE Syntax Example 2

SPSS ALTER TYPE - String to Date

Note that start and end are also string variables. Their values look like date values displayed as EDATE10. We'll copy and convert both of them to date variables by the syntax below.

System Missing Values from ALTER TYPE

Note that ALTER TYPE resulted in a system missing value without any warning or error. Fortunately, we copied our variables before converting them and copy_start tells us that the day and month were reversed for one case. Because cases have unique id values, we can easily correct the problem by combining DATE.DMY and IF as shown in the next syntax example.

SPSS ALTER TYPE - Filter

An interesting but little known feature of ALTER TYPE is converting all variables having a given format. We can do so by specifying an input format, which then acts as a filter: ALTER TYPE affects only variables whose formats match this input format. The example below first addresses all variables but only converts those having an EDATE format.

SPSS ALTER TYPE - Change String Lengths

ALTER TYPE can change the lengths of string variables. For example, the last respondent in our data got married and changed her last name to “Hernandez-Garcia”. We can't readily correct this: as we can see in variable view, last_name has an A9 format and can thus hold up to 9 characters.

The syntax below solves this by increasing its length with ALTER TYPE.

Value Labels of Numeric Variable to String Variable

Note that first_name is a numeric variable in our data. We can change it to a string variable with ALTER TYPE but this will convert the values (1 through 10) instead of the last names, which are in the value labels. The solution is using VALUELABEL but the entire process requires some manual steps outlined in the syntax below.

SPSS ALTER TYPE - Minimize String Lengths

A nice ALTER TYPE trick is minimizing the lengths of all string variables in the data. We can do so by setting all A formats to AMIN: a special ALTER TYPE keyword denoting the minimum length for each string variable.
In the previous examples, we guessed that 30 characters would be enough for first_name and last_name. These lengths are actually longer than necessary, causing the size of the data file to increase. We can easily minimize all string lengths by using the aforementioned filter feature: alter type all(a = amin).

As we see from the result, the minimal required lengths for first_name and last_name are 9 and 16.