| mazeAbility {mazeGen} | R Documentation |
mazeAbility
Description
The ability function returns the weighted score of the individual given his raw score (i.e. the number of black dotes collected).
Usage
mazeAbility(nodePosition, dot = 2, model = "t2")
Arguments
nodePosition |
You need to calculate the nodePosition. |
dot |
This is the number of black dots. |
model |
There are 4 models to estimate ability (t1,t2,t3,t4). |
Details
This function calculates the weighted score of the participant given the number of dots collected. The function adopts 4 different models which follows the Davies & Davies (1965) paper. The formula for is Model 1:
log(2^{R}/U_{m})
where 2^R is the total number of paths and U_{m} is the paths through the specified number of dots. The formula for Model 2:
log(U_{\hat{m}}/U_{m})
where U_{\hat{m}} is the value with the maximum number of connected dots. The formula for Model 3:
log(2^{R}*s^{4}/U_{m})
where s^{4} is the saturation value. The formula for Model 4 is:
log(U_{\hat{m}}*s^{4}/U_{m})
We included all four models to calculate maze ability.
Value
An 'ab' class is created which will be used for other functions in the package.
Author(s)
Aiden Loe and Maria Sanchez
See Also
Examples
nodePosition <- np(rank=6,satPercent=0.5,seed=1)
mazeAbility(nodePosition,dot=3, model="t2")