Latent class analysis has been widely used in the measurement models. Models based on latent variables have a wide range of applications in the presence of repeated ob-servations, longitudinal data, and multilevel data. In this paper we present and apply log-linear analysis as a method for the analysis of multi-way tables. We also present a latent variable model based on a variable that is not directly observed. The basic model postulates an underlying categorical latent variable; within any category of the latent variable the manifest or observed categorical variables are assumed independent of one another (axiom of conditional independence). In this paper we present the results of a survey research based on categorical data and the author`s questionnaire. We present the results of the latent class analysis in the classification of respondents into clusters characterized by similar attitudes and features in economic research. We also conduct a prior log-linear analysis for a multi-way contingency table. All the calculations are conducted in R.