Linear Logistic Models with Relaxed Assumptions in R View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2013

AUTHORS

Thomas Rusch , Marco J. Maier , Reinhold Hatzinger

ABSTRACT

Linear logistic models with relaxed assumptions (LLRA) are a flexible tool for item-based measurement of change or multidimensional Rasch models. Their key features are to allow for multidimensional items and mutual dependencies of items as well as imposing no assumptions on the distribution of the latent trait in the population. Inference for such models becomes possible within a framework of conditional maximum likelihood estimation. In this paper we introduce and illustrate new functionality from the R package eRm for fitting, comparing and plotting of LLRA models for dichotomous and polytomous responses with any number of time points, treatment groups and categorical covariates. More... »

PAGES

337-344

References to SciGraph publications

Book

TITLE

Algorithms from and for Nature and Life

ISBN

978-3-319-00034-3
978-3-319-00035-0

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-00035-0_34

DOI

http://dx.doi.org/10.1007/978-3-319-00035-0_34

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1050261696


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