Understanding Variable Recoding and Transformation in SPSS

Learn how to change variable types, recode values, and transform data in SPSS to enhance analysis accuracy and efficiency. Discover techniques for handling various levels of measurement, creating new variables, and managing value labels effectively.

• SPSS
• Data Transformation
• Variable Recoding
• Data Analysis
• Measurement Levels

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1. CONCEPT TO BE INCLUDED Variables Values Recoding Ratio

2. CHANGING VARIABLE TYPES IN SPSS

3. AIM Changing levels of measurement of a variable in SPSS. Recoding (into different variables).

4. EXAMPLE: AGE Changing an age variable with 20 values (ratio scale, young people only) into a more manageable dichotomy using SPSS.

5. Menu or Data(matrix) (.sav) Output (.spv) Graph/table Syntax file (.sps)

6. Menu or Data(matrix) (.sav) Output (.spv) Syntax file (.sps)

7. Menu or PASTE Data(matrix) (.sav) Syntax file (.sps)

8. Variables Variable label Variable name V1 Age of the respondent 0 = 0 1 = 1 year 2 = 2 years 3 = 999 = no answer Value labels Value

9. WARNING 1 Changing a variable cannot be undone So, create a NEW variable, based on the old one and keep the old one too.

10. WARNING 2 Changing value labels, does not change the values Changing values, does not change the value labels 1 = 1 year 0 = 0 year 1 = 1 year 2 = 2 3 = 3 4 = 4 5 = 5 120 = 120 Change 0,1,2,3,4, and 5 into category 1 0-5 years 120 = 120

11. FIVE LEVELS OF MEASUREMENT SPSS terminology: Dichotomy / Dummy NOMINAL Nominal Ordinal ORDINAL Interval SCALE Ratio

12. Person 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Age 0 9 2 15 20 2 13 18 11 998 15 1 6 4 We want: 0-12 13-20 998 = 1 child = 2 youngster = missing

13. NOW SOME SPSS RECORDING Changing values and changing labels using recode into different variables

14. THIS MICROLECTURE Changing levels of measurement of a variable in SPSS. Recoding (into different variables). Variables Values Dichotomy Ratio