# Why can exploratory factor analysis (EFA) suggest a single factor, yet a 1-factor confirmatory factor analysis (CFA) model not fit?

I know I previously saw a thread on this topic, but I cannot locate it. So, please forgive my redundancy.

I have an 8-item questionnaire administered to a (small) sample of 59 patients. The data consist of 7-day means of ordinal responses on a 0-10 scale (e.g., 0="No pain", 10="Worst Possible Pain"). Reliability is decent: Cronbach's alpha is 0.87. A parallel analysis (using the fa function in R's psych package) suggests that one factor underlies the responses. However, confirmatory factor analysis (using the cfa function in R's lavaan package) suggests that a 1-factor model is inappropriate (CFI=0.687, RMSEA=0.297).

Aside from the small sample size, are there any explanations for this discrepancy? If you know of any journal articles that address this issue, that would be most helpful.

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