Data and Analysis Unit: PLY034 (aka. PU012)
Description
Simulations investigating the
decision-boundary strategy analyses conducted in the COVIS
literature as reported in
Edmunds, Milton, Wills (accepted).
This DAU contains simulation files, functions, simulation output
and scripts to construct the tables, all in open cross-platform
formats (see the
file format notes).
Issues
2019-02-20: (open). Simulation 1, UD strategy, at
zero noise, sometimes returns an incorrect answer if run on more than 8
cores (the published simulations used 4-8 cores).
Resources
- R scripts for simulations and presentation of PLY34. You
will need R, plus
the following packages that are available on
CRAN:
ez, grt, mvtnorm, foreach, doParallel, parallel, mnormt,
ggplot2
- Simulation1stored.csv
- The output from Simulation 1. Column headings
are as follows:
- categoryStructure: Category structure simulation is
conducted on. II=Information-integration
- strategyType: The strategy type of the simulated responses.
UD=Unidimensional, CJ=Conjunction,
GLC=Diagonal (General linear classifier)
- perceptualNoise: The amount of perceptual noise
added to the participants' responses
- boundaryNoise: The amount of boundary noise added
to the participants' responses
- no_ppts: The number of stimulated participants that
were averaged on that row
- prop_UD: The proportion of participants that were
found to be best described by a unidimensional
strategy
- prop_GLC: The propotion of participants that were
found to be best described by a diagonal (GLC)
strategy
- prop_CJ: The proportion of participants that were
found to be best described by a conjunction
strategy
- prop_RND: The proportion of participants that were
found to be best described by a random strategy
- wBIC_UD: The averaged wBIC for participants who
were best described by a unidimensional strategy
- wBIC_GLC: The averaged wBIC for participants who
were best described by a diagonal (GLC) strategy
- wBIC_CJ: The averaged wBIC for participants who
were best described by a conjucntion strategy
- wBIC_RND: The averaged wBIC for participnats who
were best described by a random strategy
- Simulation2stored.csv -
The output from Simulation 2. The column headings are
identical to those in Simulation 1 above. The only
change is that categoryStructure is equal to
UD=Unidimensional
- Simulation3stored.csv -
The output from Simulation 3. Each row is a single
simulated participant. Column headings are as
follows:
- categoryStructure: Category structure simulation
is conducted on. II=Information-integration,
UD=unidimensional
- strategyType: The strategy type of the simulated
responses. UD=Unidimensional, CJ=Conjunction,
GLC=Diagonal(General linear classifier)
- perceptualNoise: The amount of perceptual noise
added to the participant's responses
- boundaryNoise: The amount of boundary noise added
to the participant's responses
- Accuracy: The proportion accuracy of that
participant
- UDX: Whether the participant was recovered as
using a unidimensional strategy on the x-axis: 0=no,
1=yes
- UDY: Whether the participant was recovered as
using a unidimensional strategy on the y-axis: 0=no,
1=yes
- GLC: Whether the participant was recovered as
using a diagonal (GLC) strategy: 0=no, 1=yes
- CJ: Whether the participant was recovered as
using a conjunction strategy: 0=no, 1=yes
- RND: Whether the participant was recovered as
using a random strategy: 0=no, 1=yes
- wBIC_UDX: The wBIC for the unidimensional
strategy on the x-axis
- wBIC_UDY: The wBIC for the unidimensional
strategy on the y-axis
- wBIC_GLC: The wBIC for the diagonal (GLC)
strategy
- wBIC_CJ: The wBIC for the conjucntion
strategy
- wBIC_RND: The wBIC for the random strategy