The design and analysis of state-trace experiments. | Zendy

Melissa Prince | Zendy; Scott Brown | Zendy; Andrew Heathcote | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

The design and analysis of state-trace experiments.

Author(s) -

Melissa Prince,

Scott Brown,

Andrew Heathcote

Publication year - 2011

Publication title -

psychological methods

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 6.981

H-Index - 151

eISSN - 1939-1463

pISSN - 1082-989X

DOI - 10.1037/a0025809

Subject(s) - trace (psycholinguistics) , latent variable , latent variable model , statistical analysis , statistics , computer science , bayes' theorem , econometrics , variable (mathematics) , statistical model , state variable , machine learning , artificial intelligence , bayesian probability , mathematics , mathematical analysis , philosophy , linguistics , physics , thermodynamics

State-trace analysis (Bamber, 1979) addresses a question of interest in many areas of psychological research: Does 1 or more than 1 latent (i.e., not directly observed) variable mediate an interaction between 2 experimental manipulations? There is little guidance available on how to design an experiment suited to state-trace analysis, despite its increasing use, and existing statistical methods for state-trace analysis are problematic. We provide a framework for designing and refining a state-trace experiment and statistical procedures for the analysis of accuracy data using Klugkist, Kato, and Hoijtink's (2005) method of estimating Bayes factors. The statistical procedures provide estimates of the evidence favoring 1 versus more than 1 latent variable, as well as evidence that can be used to refine experimental methodology.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research