Examples Of Spss Data Files
RECODE replaces data values with different values. It comes in handy for merging categories, dichotomizing continuous variables and some other tasks. This tutorial walks you through its main options, best practices and pitfalls. SPSS Recode Example 1 For quickly getting very proficient with RECODE it's recommended you follow along with the examples. You'll soon notice that recoding from is very simple and way, way faster than from the GUI.
All examples use. Merge Categories of One Variable In this example we'll merge categories 1 and 2 of a variable v1. We'll do this by changing all values of 1 into 2. This is as simple as recode v1 (1 = 2).The screenshot illustrates the effect.
Downloadable Sample SPSS Data Files. Data Quality Ensure that required fields contain data. Ensure that the required homicide (09A, 09B, 09C) offense segment data fields are complete. Ensure that the required homicide (09A, 09B, 09C) victim segment data fields are complete. Ensure that offenses coded as occurring. Most of the sample files are listed down on this link IBM Knowledge Center while you can get individual files from their sources literature for replications like the Auto_Car.sav is available for replications and linked here: and I recommend to use some related and.
All values that are not 1 are left unaltered. We'll run right before and after recoding so we can check the results. SPSS Recode Syntax Example 1. Get values and value labels in output and inspect frequencies. Set tnumbers both.
Recode v1 and correct value labels. Recode v1 (1=2). Add value labels v1 2 'Not at all or a bit' 1 '. Check with previous frequency table. Note that after recoding the are no longer correct. For more on this, see. We therefore adjust the value label for 2 and remove the label for 1.
Dichotomize Multiple Variables SPSS Recode Example 2 We'll dichotomize variables v4 to v6 by changing values 1, 2 and 3 into 0 and values 4 and 5 into 1 as implied by recode v4 to v6 (1,2,3 = 0)(4,5 = 1).Value 6 is is left unaltered. After recoding we must respecify the value labels for all three variables. The reason why we need two quotes in don't know is explained in. O p gauba political theory pdf file.
SPSS Recode Syntax Example 2. Inspect frequencies. Freq v4 to v6. Recode and apply new value labels. Recode v4 to v6 (1,2,3 = 0)(4,5 = 1). Value labels v4 to v6 0 'Bottom three' 1 'Top two' 6 'Don't know'.
Check against previous frequencies. Freq v4 to v6. Merge Categories into New Variable In the previous examples the original values were overwritten by the recoded values. An alternative is creating a new variable holding the recoded values. This is done by using the INTO keyword like so recode v2 (1=2) into recv2.However, this doesn't tell which values recv2 should hold if v2 is not 1, resulting in lots of.
Here we can use ELSE, which means “all values that were not previously addressed”. For copying them from v2 into recv2 we'll use (ELSE = COPY). SPSS Recode Syntax Example 3. Recode v2 into recv2. Recode v2 (1=2)(else=copy) into recv2. Cross old with new values as check.
Crosstabs v2 by recv2 /cells count /missing include.Note: recv2 doesn't have labels or missing values defined yet. A crosstab confirms that categories 1 and 2 have been merged into 2. This example shows some disadvantages of recoding into new variables.
First, note that the new variables don't have any information at all. Second, the new variables are appended to the end of the.
Sample Of Spss Data Files
Therefore, you can't adddress a range of original and recoded variables by using the keywords. However, an easy way to is using. Dichotomize Multiple Variables into New Variables Recoding several variables into several new variables is straightforward: simply fill in multiple input variable names after RECODE and multiple output variable names after INTO.
Just make sure that the number of input variables matches the number of output variables. This example uses LO THRU 3 which means “the lowest value through 3”. In a similar vein, HI can be used for the highest value. Optionally, users who have the installed can generate the crosstabs in a loop as shown in step 3B. SPSS Recode Syntax Example 4. Check frequencies.
Freq v7 to v9. Recode v7 to v9 (lo thru 3 = 0)(4,5 = 1)(else = 2) into recv7 to recv9. Check against original values.
Crosstabs v7 by recv7 /cells count /missing include. Crosstabs v8 by recv8 /cells count /missing include. Crosstabs v9 by recv9 /cells count /missing include. Alternative for 3A - have Python generate crosstabs. Set mprint on. Begin program. Import spss for suff in range(7,10): spss.Submit('crosstabs v%(suff)d by recv%(suff)d /cells count /missing include.'
%locals) end program. Recode Continuous into Discrete Variable Values are recoded only once by RECODE. The old and new value pairs are read from left to right and an old value that's already been addressed will be ignored if it's addressed again.
This is also the reason that there's no point in specifying any old values after the ELSE keyword. This feature is sometimes used when discretizing continuous variables: you can use LO (the lowest value that hasn't been previously addressed) as the lower boundary for each category. The syntax below looks a bit awkward but is not unusual. As demonstrated, a descriptives by category table is a nice way to inspect these results. Finally, note that offers an alternative for discretizing variables. SPSS Recode Syntax Example 5.
Recode income into income classes. Recode income (lo thru 2000 = 1)(lo thru 2500 = 2)(lo thru 3000 = 3)(lo thru 3500 = 4)(lo thru hi = 5) into incomeclass. Check income descriptives per income class. Means income by incomeclass /cells count min mean max. Clone a Variable A disadvantage of recoding into new variables is they don't have any dictionary information by default. However, we can clone a variable with its dictionary information by combining RECODE with APPLY DICTIONARY. This is basically what our does for many variables at once.
The tool also checks whether input variables are. If so, it automatically declares the new string variables with the correct lengths that are needed for recoding into. After cloning, we can safely recode into the same variables, leaving the variable order intact and minimizing the need for dictionary modifications after recoding. In case of doubt we can always check the recoded variable against its clone and if necessary delete it and start over from a new clone. SPSS Recode Syntax Example 6. Clone values into new variable.
Recode v10 (else = copy) into recv10. Clone dictionary onto new variable. Apply dictionary from. /source variables = v10 /target variables = recv10. Crosstabs v10 by recv10 /cells count /missing include.
Recode String to Numeric Variable In some cases you may want to recode a variable into a numeric one. This holds especially when you want to do calculations on variables under the. Note that we can't use here because we don't want our values to follow the alphabetical order of our string values. Keep in mind that you can RECODE and apply to many variables at once.
Unfortunately, copying the from the old to the new variables requires some more work but this can be automated with if desired. SPSS Recode Syntax Example 7. Create mini dataset. Data list free / s1(a10). Begin data 'Very bad' 'Bad' 'Neutral' 'Good' 'Very good' end data. Recode string into numeric variable.
Recode s1 ('Very bad' = 1)('Bad' = 2) ('Neutral' = 3)('Good' = 4)('Very good' = 5) into n1. Apply value labels. Value labels n1 1 'Very bad' 2 'Bad' 3 'Neutral' 4 'Good' 5 'Very good'. Final Notes This tutorial didn't cover some more exotic RECODE options. The reason is that we rarely see these in practice and we didn't want to go into detail any further than we already did. Some more options than described here are covered by the.