- Title
- Improving the validity, reliability, and usability of evidence accumulation models
- Creator
- Kuhne, Caroline
- Relation
- University of Newcastle Research Higher Degree Thesis
- Resource Type
- thesis
- Date
- 2024
- Description
- Research Doctorate - Doctor of Philosophy (PhD)
- Description
- Estimating quantitative cognitive models from data is a staple of modern psychological science, but can be difficult and inefficient. This thesis is comprised of three distinct sections with different aims and implications, but all are underpinned by the broader goal to increase confidence in the application of Evidence Accumulation models. In the first part of the thesis, I investigate the validity of the LBA through a series of three selective influence studies. I find mixed evidence of validity and provide suggestions for future research and model developments that might further increase the validity of the linear ballistic accumulator (LBA). In the second section of this thesis, I address the issue of reliability in model estimation and marginal likelihood estimation by developing methods that can be used to reduce estimation noise. I build an open access database of 17 experiments, 619 participants, and over 1000 individual subject level fits for the LBA and the Ratcliff diffusion model. I fit an example multivariate prior for the LBA and make the repository available for other researcher to fit their own informed prior which can then be used in hierarchical Bayesian estimation to reduce estimation noise. In the final section of this thesis, I contribute to the usability of implementing evidence accumulation models by providing a detailed tutorial on how to estimate cognitive models using the pmwg R package for which I am a co-author. The work in this thesis the potential to move the field of psychology ahead in new and interesting directions, and to resolve questions that were once too hard to answer when data is scarce or the experiment, or the model is very complex.
- Subject
- quantitative cognitive models; evidence accumulation models; decision making; linear ballistic accumulator; selective influence studies; reliability model estimation; estimation noise reduction; hierarchical Bayesian estimation; pmwg R package; informed prior; tutorial on cognitive model estimation
- Identifier
- http://hdl.handle.net/1959.13/1512007
- Identifier
- uon:56577
- Rights
- Copyright 2024 Caroline Kuhne
- Language
- eng
- Full Text
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| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | ATTACHMENT01 | Thesis | 8 MB | Adobe Acrobat PDF | View Details Download | ||
| View Details Download | ATTACHMENT02 | Abstract | 284 KB | Adobe Acrobat PDF | View Details Download |