Random Intercept and Random Slope 2-Level Multilevel Models

Random Intercept and Random Slope 2-Level Multilevel Models

Random intercept model and random intercept & random slope model carrying two-levels of hierarchy in the population are presented and compared with the traditional regression approach. The impact of students’ satisfaction on their grade point average (GPA) was explored with and without controlling teachers influence. The variation at level-1 can be controlled by introducing the higher levels of...

Random intercept item factor analysis.

The common factor model assumes that the linear coefficients (intercepts and factor loadings) linking the observed variables to the latent factors are fixed coefficients (i.e., common for all participants). When the observed variables are participants' observed responses to stimuli, such as their responses to the items of a questionnaire, the assumption of common linear coefficients may be too ...

Bayesian model selection for logistic regression models with random intercept

Data, collected to model risk of an interesting event, often have a multilevel structure as patients are clustered within larger units, e.g. clinical centers. Risk of the event is usually modeled using a logistic regression model, with a random intercept to control for heterogeneity among clusters. Model specification requires to decide which regressors have a non-negligible effect, and hence, ...

Random intercept selection in structured additive regression models

Random Coefficient Models for Multilevel Analysis

We propose a possible statistical model for both contextual analysis and slopes as outcomes analysis. These techniques have been used in multilevel analysis for quite some time, but a precise specification of the regression models has not been given before. We formalize them by proposing a random coefficient regression model, and we investigate its statistical properties in some detail. Various...