Amanote Research

Amanote Research

    RegisterSign In

Modeling Psychophysical Data at the Population-Level: The Generalized Linear Mixed Model

Journal of Vision - United States
doi 10.1167/12.11.26
Full Text
Open PDF
Abstract

Available in full text

Categories
OphthalmologySensory Systems
Date

October 25, 2012

Authors
A. MoscatelliM. MezzettiF. Lacquaniti
Publisher

Association for Research in Vision and Ophthalmology (ARVO)


Related search

Predictive Modeling of Microbiome Data Using a Phylogeny-Regularized Generalized Linear Mixed Model

Frontiers in Microbiology
Microbiology
2018English

The Effects of Model Misspecification When Fitting Generalized Linear Mixed Models

English

Correlated Spatiotemporal Data Modeling Using Generalized Additive Mixed Model and Bivariate Smoothing Techniques

Science Journal of Applied Mathematics and Statistics
2018English

Generalized Linear Mixed Models

2018English

Generalized Linear Mixed Models

Wiley Series in Probability and Statistics
2005English

Power Difference in a Χ2 Test vs Generalized Linear Mixed Model in the Presence of Missing Data – A Simulation Study

BMC Medical Research Methodology
EpidemiologyHealth Informatics
2020English

Constrained Statistical Inference in Generalized Linear, and Mixed Models With Incomplete Data

English

Table S7: The Results From the Linear Mixed Effects Model for Activity Data

English

Figure S3: Mantel Tests for the Full Generalized Linear Mixed Model With Negative Binomial Distribution

English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2026 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy