I would like to apply Confirmatory Factor Analysis (CFA) to a Likert-type questionnaire data. It is supposed that this data is affected by response bias: some patients either overestimated or underestimated their symptoms when filling up the questionnaire (which might be somewhat similar to acquiescence bias and its opposite). So, if an answer to each questionnaire item ranges from 1 to 5 (where 1 = “strongly disagree”, and 5 - “strongly agree”), some patients tend to give higher scores and some tend to give lower scores regardless or their actual symptoms. The question is how to correct for such bias and keep data meaningful for Factor Analysis? And in particular: What are possible approaches? How to choose among them? Is there a common approach?