Article1990

Sequential item response models with an ordered response

223 citations0/0 files storedBritish Journal of Mathematical and Statistical Psychology

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Psychometric Methodologies and Testing Statistical Distribution Estimation and Applications Statistical Methods and Bayesian Inference

Abstract

A stepwise approach to the construction of latent trait models is outlined. As a special case of the derived general sequential model, a sequential Rasch model is considered. The derivation of the models is based on mechanisms of latent random variables. The unconditional maximum likelihood estimation is embedded in the framework of generalized linear models. An alternative estimation procedure which allows for ‘parameter separability’ is considered and its applicability is shown.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 223 citations exist upstream.

Cited by

2012IRTrees: Tree-Based Item Response Models of the GLMM Family 2015A generalized item response tree model for psychological assessments 2007Ordered Response Models 2011Road Maps for Learning: A Guide to the Navigation of Learning Progressions 2002A Monte Carlo Comparison of Parametric and Nonparametric Polytomous DIF Detection Methods 2012The Rasch Rating Model and the Disordered Threshold Controversy 1995Conceptual Notes on Models for Discrete Polytomous Item Responses 2001The Use of Restricted Latent Class Models for Defining and Testing Nonparametric and Parametric Item Response Theory Models

Imported from OpenAlex (CC0) — nothing here is generated.