Analysing data from a questionnaire:Analysing data from a questionnaire:Reliability and PCAReliability and PCA

Topics

Coding item scoresReliability of a straightforward scale

Tests measuring more than one constructPresenting the results

Recoding negative itemsRecoding negative items

Masculinity questionnaire: I agree that blue is a lovely colour I agree that pink is a delicious colour

Recode as (max + min) – score

e.g. scale is 1—7 , recode as 8 – score

Or scale is 0 – 7, recode as 7 – score

Reliability of a scale measuring one construct

Split-halfCronbach's alpha

For example

Warwick sweetness scale

Scale measuring more than one construct

PCACorrelations among items

Extraction / RotationPCA / varimax

Other extraction (FA) if components are correlated (e.g. anxiety & depression)

In action...

Note...

Try different solutions, forcing the number of dimensions

Eigenvalues v. scree plot

Loadings; cut-off

“Simple structure” is preferred

Component scores

Give each person an”overall” score for Size or Smart: but how

Chess + IQ + Alevel (?)

Give more weight to the ones withbiggest loadings

PCA and scales with 1-d

Check that it is1-DCalculate overall scores?

Standardised tests

Do I need to check?

-You must!

Presentation of reliability analysisMethod v. Results?

Give value of coefficientp-value is generally irrelevant

PCA – report Eigenvalues or % variance explained for each component

Explain how you selected the solution you preferred

Provide a table of loadings (use a cut-off to simplify)

Table of loadings

C1 C2

Height .93 -Weight .94 -Shoe .94 -Chess - .89IQ -.49 .85Maths - .96

Further reading

Dunbar (1998) Data analysis for psychology. London: Arnold. Ch6 pp85-88; Ch11

Klein, P. (1994) An easy guide to factor analysis. New York, Routledge.

Vowles et al. (2008) The chronic pain acceptance questionnaire.... Pain, 140, 284-291