Recoding and Computing Variables in SPSS

Recode into Different Variables vs Recode into Same Variables

SPSS gives you two recode options under Transform, and only one of them is safe by default. Recode into Different Variables creates a new column and leaves your original data untouched. Recode into Same Variables overwrites the original column permanently, with no built-in undo once you’ve saved. Use “Into Different Variables” as your default; only use “Into Same Variables” when you’re certain you’ll never need the raw values again.

Using Compute Variable to Build Composite Scores

Transform > Compute Variable lets you build a new variable from a formula applied to existing ones, most commonly used to create a composite or index score by summing or averaging several scale items into one overall variable (e.g. averaging ten satisfaction items into a single “Satisfaction” score). Name the target variable, build the expression using the function list and existing variables, and click OK. The new variable appears as a normal column, ready for further analysis.

Reverse-Scoring Negatively Worded Items Before Reliability Analysis

Scales frequently mix positively and negatively worded items on purpose, to reduce response-pattern bias. Before you sum or average items into a composite score, and specifically before running reliability analysis, every negatively worded item needs to be reverse-scored so a high number means the same thing across every item in the scale.

The formula is straightforward: reverse-scored value = (max + min) − original value. On a standard 1–5 scale, a response of 1 becomes 5, 2 becomes 4, 3 stays 3, and so on. Do this with Recode into Different Variables, never overwriting the original item, so you can verify the recode was applied correctly before it feeds into anything else.

Skipping this step is one of the most common reasons a Cronbach’s alpha comes back unexpectedly low, or even negative. See the full reliability analysis guide for how reverse-scoring feeds directly into that test, or the survey and questionnaire data coding guide for the broader data-setup process this fits into.

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