Let’s suppose that you received the following data set and were asked to
analyze the data.  You quickly notice that independent variable, group, is a string variable, but you want to try running an ANOVA anyway.

data list list / id * group (A8) score *.
begin data
1 "group 1" 57
2 "group 1" 65
3 "group 1" 70
4 "group 2" 45
5 "group 2" 80
6 "group 2" 81
7 "group 3" 66
8 "group 3" 60
9 "group 3" 70
10 "group 3" 80
end data.

oneway score by group.

Unhappily, you get an error message indicating that
the ANOVA cannot be run with group because group is a string variable (but
please see the note at the end of this page).  You can use the
autorecode command to change group from a string variable, such as group,
into a numeric variable with values corresponding to the groups. In other words,
all values of “group 1” will be coded as one in the new variable, which we will call
rcdgrp.  The into subcommand tells SPSS to put the recoded values into a new variable.  If this
subcommand is omitted,
the new values will overwrite the values in the original variable.

autorecode variables = group
 /into rcdgrp.

Let’s run a crosstab with the old variable,
group and the new variable, rcdgrp, to ensure that the recoding went as expected.

crosstabs tables = group by rcdgrp.

We can see that the recoding was done correctly, so now we can
conduct the ANOVA.

oneway score by rcdgrp.

Let’s take a moment to briefly describe how the
autorecode command works.  The autorecode command sorts the values of the variable to be
recoded and then assigns them numeric values.  By default, the values are assigned in ascending order.  User-defined missing values are recoded into
values higher than any nonmissing values.  System-missing values remain system-missing. 
(There are no system missing values in string variables; however, you can use
autorecode with numeric variables that do have system missing values.)  
In SPSS version 13, the blank subcommand was added.  This allows you
to specify how you would like missing values in a string variable to b handled
when autorecoded.  (Remember that in a string variable, a missing value is
a null, or empty, string; it is simply a blank or empty cell in the Data
Editor.)  The default option is valid, which means that the empty
string will be coded as a valid value in the new numeric variable.  You can
also use the missing option, causing blank string values to be autorecoded into a user-missing value
higher than the highest nonmissing value.

You may be wondering about the differences between the
autorecode and the recode commands.  The two commands are very similar.  The main difference is that
autorecode automatically assigns a numeric value to each unique string
value.  It also creates value labels for the new numeric values that are
the original string values.  With recode, you need to specify
the values for the new variable.  If you want to add value labels to the
numeric values, you need to do that in a separate step using the value labels
command.  Hence, autorecode is particularly useful when you have
numerous values that need to be converted. 

The examples below illustrate how you can autorecode multiple variables
at once.  Perhaps the most important thing to remember is that the variables must be positionally consecutive in the data set.  However, they do not need
to be numbered consecutively.  If the variables that you want to autorecode are not positionally consecutive, you can make them positionally consecutive
by using the save command with the keep subcommand, listing the variables
in the necessary order.

data list list / a1 (A1) a2 (A1) a3 (A1) a4 (A1) a5 (A1).
begin data.
a b c d e
f g h i j
end data.

We will use the print subcommand to print out the old values, the new
values and the labels of the new values.

autorecode a1 a2 a3 a4 a5 
/into newa newb newc newd newe 
/print.

                       A1          NEWA
                     Old Value   New Value  Value Label

                             a           1  a
                             f           2  f


                      A2          NEWB
                     Old Value   New Value  Value Label

                             b           1  b
                             g           2  g


                      A3          NEWC
                     Old Value   New Value  Value Label

                             c           1  c
                             h           2  h


                      A4          NEWD
                     Old Value   New Value  Value Label

                             d           1  d
                             i           2  i


                      A5          NEWE
                     Old Value   New Value  Value Label

                             e           1  e
                             j           2  j

The syntax above is equivalent to the syntax below.  Note that you can use the keyword to when specifying the variables to be autorecoded.

autorecode a1 a2 a3 a4 a5 /into new1 to new5.

The following examples illustrate what happens when the variables to be
autorecoded are not in positionally consecutive order.  Notice the addition of the variable
newvar.

data list list / a1  (A1) a2  (A1) a3  (A1) newvar  * a4   (A1) a5 (A1).
begin data.
a b c 9 d e
f g h 6 i j
end data.

With newvar located between a1 and a5, the following syntax will not work
and an error message will be issued.

autorecode a1 to a5 /into b1 to b5.

>Error # 17008
>The number of new variable names must equal the number of old variable
>names.
>This command not executed.

In order to make the above syntax work, you would need to
specify the variables before and after newvar to be autorecoded.  Although not shown here,
you can use the keyword to twice to specify the variables to be autorecoded (for example: a1 to a3 a4 to a5).

autorecode a1 to a3 a4 a5 /into b1 to b5.

NOTE:  While the oneway, anova,
manova and discrimiant commands require both the independent and the dependent
variables to be numeric, the glm command can be used with a string independent variable.