Questionnaire validation in psychology: CFA, McDonald's omega, measurement invariance. Q1-standard methodology for theses and scientific articles.
Exploratory factor analysis (EFA) is used to discover the underlying structure of a scale when you have no clear prior hypothesis. Confirmatory factor analysis (CFA) tests whether a structure defined in advance — based on theory or a previous study — fits the data. For validating an instrument with an expected structure, CFA is the appropriate standard; if you are developing a scale from scratch, you usually start with EFA and confirm with CFA in an independent sample.
It depends on the number of items and factors and the complexity of the model, not on a single fixed rule. As a guide, several hundred participants are usually recommended for a robust CFA, but the exact figure is set from your design. In the free consultation I assess your case and tell you the realistic sample you need.
I report McDonald's omega and Cronbach's alpha for reliability, CFA fit indices (CFI, TLI, RMSEA, SRMR), measurement invariance across groups when relevant, and convergent/discriminant and criterion validity evidence. Everything is reported to the standard required by Q1/Q2 journals.
Yes. Measurement invariance (configural, metric and scalar) is essential before comparing groups or, in cross-cultural adaptations, before comparing scores across languages or countries. I run it and interpret it so your comparisons are valid.
Mainly R (lavaan, psych) and Mplus for CFA, SEM and invariance, and JASP or jamovi when a more visual workflow is preferred. The choice adapts to your design and to what your supervisor or target journal expects.
Yes. I support the statistical side of adapting and validating an instrument in a new language or culture: structure, reliability, measurement invariance against the original version, and the reporting required for publication.