Scaling Unidimensional Models with Multiple Correspondence Analysis

Multivariate analysis of psychological data - ou

When compliments do not hit but critiques do: an fMRI study into self-esteem and self-knowledge in processing social feedback

FSW - Self-regulation models for health behavior and psychopathology - oudMultivariate analysis of psychological dat

Stuck in a negative me: fMRI study on the role of disturbed self-views in social feedback processing in borderline personality disorder

Stress and Psychopatholog

Multilevel latent class analysis for large-scale educational assessment data: Exploring the relation between the curriculum and students' mathematical strategies

A first application of multilevel latent class analysis (MLCA) to educational large-scale assessment data is demonstrated. This statistical technique addresses several of the challenges that assessment data offers. Importantly, MLCA allows modeling of the often ignored teacher effects and of the joint influence of teacher and student variables. Using data from the 2011 assessment of Dutch primary schools’ mathematics, this study explores the relation between the curriculum as reported by 107 teachers and the strategy choices of their 1,619 students, while controlling for student characteristics. Considerable teacher effects are demonstrated, as well as significant relations between the intended as well as enacted curriculum and students’ strategy use. Implications of these results for both more theoretical and practical educational research are discussed, as are several issues in applying MLCA and possibilities for applying MLCA to different types of educational data.Development Psychopathology in context: schoo

Seriation and Multidimensional Scaling: A Data Analysis Approach to Scaling Asymmetric Proximity Matrices

A number of model-based scaling methods have been developed that apply to asymmetric proximity matrices. A flexible data analysis approach is pro posed that combines two psychometric procedures— seriation and multidimensional scaling (MDS). The method uses seriation to define an empirical order ing of the stimuli, and then uses MDS to scale the two separate triangles of the proximity matrix defined by this ordering. The MDS solution con tains directed distances, which define an "extra" dimension that would not otherwise be portrayed, because the dimension comes from relations between the two triangles rather than within triangles. The method is particularly appropriate for the analysis of proximities containing temporal information. A major difficulty is the computa tional intensity of existing seriation algorithms, which is handled by defining a nonmetric seriation algorithm that requires only one complete itera tion. The procedure is illustrated using a matrix of co-citations between recent presidents of the Psychometric Society.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Commemorating the 80th anniversary of the founding of Psychometrika: Introduction by the guest editors

Multivariate analysis of psychological dat

Parallel factor analysis with constraints on the configurations: An overview

Datatheorie voor analyse van individuele verschille