A survey is given of papers which have influenced or have been influenced by the Growth Curve Model due to Potthoff & Roy (1964). The review covers, among others, methods of estimating parameters, the canonical version of the model, tests, extensions, incomplete data, Bayesian approaches and covariance structures.

High quality of teacher–student relationships is widely recognized as fundamental part of good education. Moreover, students’ self-efficacy beliefs, or their confidence to succeed within different domains at school, are important impact factors to achievement. Although there is support for an association between student-perceived teacher–student relationship quality and students’ self-efficacy judgements, which mediates achievement, no tool explores this association. This article suggests that two instruments, respectively measuring students’ perceptions of teacher–student relationship quality (TSR) and student’s self-efficacy (SSE), can be used in parallel for a multifaceted exploration of individual students’ perception of TSR quality, in relationship to their self-efficacy. Two well-established instruments were adopted, validated and their factor structures re-confirmed in a Swedish sample, using data from students in five schools (n=382). Factor analysis showed that models with three underlying dimensions of TSR and four underlying dimensions of SSE were the most appropriate. All sub-scales showed good-to-excellent reliability (Cronbach’s α = 0.75–0.94). Findings indicated a lack of multigroup invariance across gender and school level for the TSR-model. Substantial associations were found between student-perceived teacher support, and students’ self-efficacy for self-regulated learning and global academic success. We discuss utility and limitations, need of model improvement, and future potential.

Models that capture symmetries present in the data have been widely used in different applications, with early examples from psychometric and medical research. The aim of this article is to study a random effects model focusing on the covariance structure that is block circular symmetric. Useful results are obtained for the spectra of these structured matrices.

The aim of the paper is to determine maximum-likelihood estimation equations. Observations follow a multivariate normal distribution, , where , and describe the unknown covariance structure between rows and columns of , respectively. Imposing restrictions on and four types of covariance structures will be considered.