Mixed model analysis of trial history in naming experiments (Book, 2015) [WorldCat.org]
skip to content
New WorldCat.org coming soon
Mixed model analysis of trial history in naming experiments
Checking...

Mixed model analysis of trial history in naming experiments

Author: Maximilian Michael Rabe; Reinhold Kliegl
Publisher: Potsdam 2015
Dissertation: Bachelorarbeit Universität Potsdam, Humanwissenschaftliche Fakultät 2015.
Edition/Format:   Thesis/dissertation : Document : Thesis/dissertation : eBook   Computer File : English
Summary:
Several authors highlighted that the time course of an experiment itself could have a substantial influence on the interpretability of experimental effects. Since mixed effects modeling had enabled researchers to investigate more complex problems with more precision than before, two naming experiments were conducted with college students, with and without non-words intermixed, and analyzed with regard to frequency,  Read more...
Subjects
More like this

Find a copy online

Links to this item

Find a copy in the library

&AllPage.SpinnerRetrieving; Finding libraries that hold this item...

Details

Genre/Form: Hochschulschrift
Material Type: Document, Thesis/dissertation, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Maximilian Michael Rabe; Reinhold Kliegl
OCLC Number: 989871916
Description: 1 Online-Ressource (vii, 33 Seiten, 5558 KB) Illustrationen, Diagramme
Other Titles: Experimentalverlaufsanalyse mit gemischten Modellen in Naming-Experimenten
Responsibility: Maximilian Michael Rabe, Universität Potsdam.

Abstract:

Several authors highlighted that the time course of an experiment itself could have a substantial influence on the interpretability of experimental effects. Since mixed effects modeling had enabled researchers to investigate more complex problems with more precision than before, two naming experiments were conducted with college students, with and without non-words intermixed, and analyzed with regard to frequency, quality, interactive and trial-history effects. The present analyses build on and extend the Bates, Kliegl, Vasishth, and Baayen (2015) approach in order to converge on a parsimonious model that accounts for autocorrelated errors caused by trial history. For three of four cases, a history-sensitive model improved the model fit over a history-naïve model and explained more deviance. In one of these cases, the herein presented approach helped reveal an interaction between stimulus frequency and quality that was not significant without a trial history account. Main and joint effects, limitations, as well as directions for furt...

Reviews

Retrieving GoodReads reviews...
Retrieving DOGObooks reviews...

Confirm this request

You may have already requested this item. Please select Ok if you would like to proceed with this request anyway.

Close Window

Please sign in to WorldCat 

Don't have an account? You can easily create a free account.