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