I am working on a research project about Human Welfare Indicators for Indigenous Peoples, I dispose of more than 100 variables list and sample of 156 subjects. Now I must establish the statistical method for analysing the information. I would like to know which method is more suitable if the method of principal component analysis or factor analysis and why.
Please add your answers in english, spanish or french.
Thanks
Initially I have 20 subjects. I could increase the sample until 156.
To help you choose between PCA and EFA, consider Preacher and MacCallum's classic paper: http://quantpsy.org/pubs/preacher_maccallum_2003.pdf
Principal component analysis and Common Factor analysis differ in their assumptions and mathematically. Component analysis includes all the three types of variance (common, specific and error) while common factory analysis accounts only for common or shared variance. However, it is frequently reported that the resulting solution from both approaches are similar. please, refer to the following paper for more details
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