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Cross-cultural comparison of attitudes using rating scales may be seriously biased by response styles. This paper deals with statistical methods for detection of and correction for extreme response style (ERS), which is one of the well-documented response styles. After providing an overview of available statistical methods for dealing with ERS, we argue that the latent class factor analysis (LCFA) approach proposed by has several advantages compared to other methods. Moors' method involves defining a latent variable model which, in addition to the substantive factors of interest, contains an ERS factor. In LCFA the observed ratings can be treated as nominal responses, which is necessary for modeling ERS. We find strong evidence for the presence of ERS and, moreover, find that the groups differ not only in their attitudes but also in ERS. These findings underscore the importance of controlling for ERS when examining attitudes in cross-cultural research. [ABSTRACT FROM AUTHOR]