Multidimensional scaling
Place cases on a map so that distances reflect how different they are.
When to use it
Use multidimensional scaling when you want a picture of cases, not a picture of variables. People who gave similar answers land near each other. Two dimensions is the usual map. This is not a factor analysis of the items.
Assumptions
Columns are numeric. Distance is Euclidean after listwise deletion. The request does not standardize the columns, so a column with a much larger scale dominates the distances. You need at least two more complete rows than the number of dimensions.
Running it in Tensr
Options
Prop
Type
Reading the output
Five scale items placed in two dimensions from their distances. Items that share the factor should sit nearer each other than a pure noise pair would.
Multidimensional scaling on 5 variables, n = 120. Multidimensional scaling on 5 variables, n = 120. Metrics: Stress = 5333; Dimensions = 2.
Reporting (APA 7)
Multidimensional scaling on 5 variables, n = 120. Report the estimate in the table. This procedure is not summarised by one p-value.
Coming from SPSS
Analyze → Scale → Multidimensional Scaling (PROXSCAL / ALSCAL). SPSS stress is usually scaled to a 0-to-1 range. Tensr reports the unscaled stress from the fit.