mazeGen (version 0.1.3)

mazeAbility: 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).

Value

An 'ab' class is created which will be used for other functions in the package.

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.

See Also

mazeDiff, np

Examples

# NOT RUN {
 nodePosition <- np(rank=6,satPercent=0.5,seed=1)
 mazeAbility(nodePosition,dot=3, model="t2")
# }