This study is an investigation of the values of 346 secondary students, using Latent Class Analysis (LCA) and Cluster Analysis (CA). It answers the following questions: 1) Are there differences in the mean values of senior secondary students associated with gender, family variables, academic achievement, peer relations, and teacher qualification? 2) What is the typology or classification of students according to their values, based on LCA and CA, respectively?
The study revealed that students attach varying degrees of importance to values about self with gender, family structure, academic achievement, peer relations and their teachers' qualification tending to influence the values' importance.
LCA yielded a latent variable, Self Worth, and three latent classes while CA classified the respondents into three clusters. LCA can be applicable in understanding student values; it is accurate and efficient in analyzing categorical data. CA is accurate in classifying students based on interval data.