17a.Accessing Data: Manipulating Variables in SPSS ®

17a. Accessing Data: ManipulatingVariables in SPSS®

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17a. Accessing Data: Manipulating Variables in SSPS®

Prerequisites• Recommended modules to complete before viewing

this module 1. Introduction to the NLTS2 Training Modules 2. NLTS2 Study Overview 3. NLTS2 Study Design and Sampling NLTS2 Data Sources, either

• 4. Parent and Youth Surveys or• 5. School Surveys, Student Assessments, and Transcripts

NLTS2 Documentation• 10. Overview• 11. Data Dictionaries• 12. Quick References

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Prerequisites• Recommended modules to complete before viewing

this module (cont’d) 13. Analysis Example: Descriptive/Comparative Using

Longitudinal Data Accessing Data

• 14a. Files in SPSS• 15a. Frequencies in SPSS

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Overview Purpose Modifying existing variables Creating new variables Summary Closing Important information

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NLTS2 restricted-use data

• NLTS2 data are restricted.• Data used in these presentations are from a

randomly selected subset of the restricted-use NLTS2 data.

• Results in these presentations cannot be replicated with the NLTS2 data licensed by NCES.

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Purpose

• Learn to Modify an existing variable Create a new variable Join/combine data from different sources


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Modifying existing variables• How to modify a variable.• It is necessary to create a new variable in SPSS to

Collapse categories Break a continuous variable into categories Recode a variable.

• Note about created variables in the NLTS2 database Our analyses were done in SAS, and this recoding step is usually not

necessary in SAS because of the external formats feature. Collapsed or recategorized variables do not necessarily exist in SAS or

SPSS files even if these items appear in published tables. There are many created variables in the NLTS2 database, but most of

them are not simply collapsed versions of an existing variable.

These results cannot be replicated with full dataset; all outputin modules generated with a random subset of the full data.


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Modifying existing variables• Syntax to recode into collapsed categories

RECODE np1B2a (MISSING=SYSMIS) (Lowest thru 1=1) (2 thru 5=2) (6 thru 10=3) (11 thru Highest=4) INTO np1B2a_Cat .



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Modifying existing variables• Syntax to assign a variable label to the new variable

*assign variable label to new categorical variable.VARIABLE LABELS np1B2a_Cat

'(np1B2a_cat) Age of youth when diagnosed categorized'.EXECUTE.

• Syntax to assign value labels* assign value labels to new categorical variable.VALUE LABELS np1B2a_Cat

1 "(1) 1 or younger" 2 "(2) 2 to 5 years of age" 3 "(3) 6 to 10 years of age" 4 "(4) 11 or older".



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Modifying existing variables• Menu

Transform: Recode into Different Variables Select the variable to be recoded from the list and click the

right-facing arrow. Give the new variable a name in the box under “Output

Variable.” Assign a label to the new variable in the “Label” box under

“Output Variable.” Click “Change.” Click on the box marked “Old and New Values,” and a new box

pops up. In the new box, under “Old Values” click the radio button

“System or User-missing,” click “System Missing” under “New Values,” and click “Add” next to “Old -- >New.”


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Modifying existing variables

• Menu (cont’d) For each old to new value(s)

• Under “Old Values,” click a radio button by an actual value or range of values box.

• Designate what the old values are, either actual or range of values, in the appropriate box.

• Assign a new code under “New Values” and click “Add.” When finished with values, click “Continue” to return to

the first box. In the original box, click “OK” or “Paste” to generate code.



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Modifying existing variables• Look at results.• New variable should appear at bottom of “Variable View.”• Specify formats so values are meaningful.

In variable view, click on the cell in the “Values” column to bring up a new box.

Enter a value in the “Value” box, a label for that value in the “Label” box, and click “Add.”

Do this for every value.• Look at frequency distribution.

Useful to look at a crosstab of the original by the new variable.



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Modifying existing variables: Example• Modifying a variable

Open Wave 3 parent/youth interview file. Collapse np3NbrProbs into new variable.

• 0-1• 2• 3• 4-6

Remember to• Label variable• Add value formats• Account for missing values• Paste your code.



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Modifying existing variables: Example



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Modifying existing variables: Example



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Creating new variables• How to create a new variable.• The values in the new variable can be the results of

calculations, assignments, or logic.• A new variable can be created from an existing

variable or from multiple variables, including variables from other sources and/or waves. Variables from other sources/waves must be added to the

active data file before the new variable is created.



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Creating new variables• Be aware of any coding differences between the

variables when combining values.• Decide what to do with missing values.• Example: Create a variable using parent interview

data from Waves 1, 2, and 3. Has a student been suspended and/or expelled in any

wave?



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Creating new variables• Syntax

IF (np1D7h=0 and np2D5d=0 and np3D5d=0 and np4D5d=0) np4D5d_ever=0.

IF (np1D7h=1 or np2D5d=1 or np3D5d=1 or np4D5d=1) np4D5d_ever = 1.

IF (np1D7h=1 and np2D5d=1 and np3D5d=1 and np4D5d=1) np4D5d_ever = 2.

IF (MISSING(np1D7h) or MISSING(np2D5d) or MISSING(np3D5d) or MISSING(np4D5d)) np4D5d_ever = -999 .EXECUTE .

• This code will result in a variable that Requires a value for every wave Is 0 if never suspended/expelled Is 1 if suspended/expelled in any wave Is 2 if suspend/expelled in all three waves.



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Creating new variables



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Creating new variables• Menu

Transform: Compute Enter a variable name under “Target Variable.” Click “Type & Label” and assign a label. If applicable, find and select the source variable(s) and click the right-facing

arrow to move the variable name into the “Numeric Expression” box. Enter functions/operations from the keypad boxes or select from the list of

functions. For logical conditions, click “If…” and build the condition in the pop-up box. Click “OK” or “Paste.” For multiple conditions (i.e., if-then-else), repeat all steps.

• Specify conditions in order of overriding conditions.• If true, each subsequent condition will override the previous condition.



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Creating new variables: Example• Creating a new variable

Open the Wave 4 parent/youth interview file. Bring in np1F7 from Wave 1, np2P8_J4 from Wave 2, and

np3P8_J4 from Wave 3 interview files. Create a new variable np4P8_J4_ever (ever done volunteer

or community service). Initialize value to “0” if any value in np1F7, np2P8_J4,

np3P8_J4, or np4P8_J4 is “0.” Reassign to “1” if any value in np1F7, np2P8_J4, np3P8_J4,

or np4P8_J4 is “1.”



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Creating new variables: Example

• Creating a new variable (cont’d) Assign variable label and value labels. Run a frequency of np4P8_J4_ever. Run a crosstabulation of np4P8_J4_ever by

np4P8_J4.



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Creating new variables: Example• Code for example

IF (np1F7=0 or np2P8_J4 = 0 or np3P8_J4=0 or np4P8_J4=0) np4P8_J4_ever = 0 .

IF (np1F7=1 or np2P8_J4=1 or np3P8_J4=1 or np4P8_J4=1) np4P8_J4_ever = 1 .



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Summary• Be aware of differences in coding between similar variables when

building composite variables.• Missing values must be considered.

Know how missing values are being coded, particularly when using more than one variable to create another.

Joined data are more likely to have missing values.• Weights

Generally, the analysis weight should be the weight from the smallest sample when combining data.

When filling in values for a variable in an active file with values from another, it is OK to use the weight in the active file.

• Strongly recommended: Paste your code when creating variables.


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Summary

Know the values, mind the missing, and watch your weights!


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Closing

• Topics discussed in this module Modifying existing variables Creating new variables Summary

• Next module 18a. Complex Samples Procedures in SPSS

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Important information NLTS2 website contains reports, data tables, and other

project-related information http://nlts2.org/

Information about obtaining the NLTS2 database and documentation can be found on the NCES website http://nces.ed.gov/statprog/rudman/

General information about restricted data licenses can be found on the NCES website http://nces.ed.gov/statprog/instruct.asp

E-mail address: [email protected]

http://nlts2.org/

http://nces.ed.gov/statprog/rudman/

http://nces.ed.gov/statprog/instruct.asp

17a.Accessing Data: Manipulating Variables in SPSS ®

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