Needs Assessment for Literacy Development by Hierarchical Generalized Linear Modeling

Modeling local item dependence with the hierarchical generalized linear model.

Local item dependence (LID) can emerge when the test items are nested within common stimuli or item groups. This study proposes a three-level hierarchical generalized linear model (HGLM) to model LID when LID is due to such contextual effects. The proposed three-level HGLM was examined by analyzing simulated data sets and was compared with the Rasch-equivalent two-level HGLM that ignores such a...

Double hierarchical generalized linear models

We propose a class of double hierarchical generalized linear models in which random effects can be specified for both the mean and dispersion. Heteroscedasticity between clusters can be modelled by introducing random effects in the dispersion model, as is heterogeneity between clusters in the mean model.This class will, among other things, enable models with heavy-tailed distributions to be exp...

Advantages of Hierarchical Linear Modeling. - Practical Assessment, Research & Evaluation

Hierarchical, or nested, data structures are common throughout many areas of research. However, until recently there has not been any appropriate technique for analyzing these types of data. Now, with several user-friendly software programs available, and some more readable texts and treatments on the topic, researchers need to be aware of the issue, and how it should be dealt with. The goal of...

Generalized Linear Modeling

Generalized Secret Sharing with Linear Hierarchical Secrets

Generalized secret sharing is a method of constructing secret sharing from the perspective of access structure. In this paper, we propose a novel solution for achieving generalized secret sharing with linear hierarchical secrets. We use a matrix to model the relationship related to the access structure and transfer the matrix to modular arithmetic, which is calculated by Chinese Remainder Theor...