CBS_RC {CBSr}

CBS_RC

Description

Fit either a 1-piece or 2-piece CBS latent utility function to binary risky choice data.

Usage

CBS_RC(choice, Amt1, Prob1, Amt2, Prob2, numpiece, numfit = NULL)

Arguments

choice

Vector of 0s and 1s. 1 if the choice was option 1, 0 if the choice was option 2.

Amt1

Vector of positive real numbers. Reward amount of choice 1.

Prob1

Vector of positive real numbers between 0 and 1. Probability of winning the reward of choice 1.

Amt2

Vector of positive real numbers. Reward amount of choice 2.

Prob2

Vector of positive real numbers between 0 and 1. Probability of winning the reward of choice 2.

numpiece

Either 1 or 2. Number of CBS pieces to use.

numfit

Number of model fits to perform from different starting points. If not provided, numfit = 10*numpiece

Details

The input data has n choices (ideally n > 100) between two reward options. Option 1 is receiving Amt1 with probability Prob1 and Option 2 is receiving Amt2 with probability Prob2 (e.g., $40 with 53% chance vs. $20 with 90% chance). One of the two options may be certain (i.e., prob = 1; e.g., $40 with 53% chance vs. $20 for sure). choice should be 1 if option 1 is chosen, 0 if option 2 is chosen.

Value

A list containing the following:

• type: either 'CBS1' or 'CBS2' depending on the number of pieces

• LL: log likelihood of the model

• numparam: number of total parameters in the model

• scale: scaling factor of the logit model

• xpos: x coordinates of the fitted CBS function

• ypos: y coordinates of the fitted CBS function

• AUC: area under the curve of the fitted CBS function. Normalized to be between 0 and 1.

Examples

# Fit example Risky choice data with 2-piece CBS function.
# Load example data (included with package).
# Each row is a choice between option 1 (Amt with prob) vs option 2 (20 for 100%).
Amount1 = RCdat$Amt1
Prob1 = RCdat$Prob1
Amount2 = 20
Prob2 = 1
Choice = RCdat$Choice

# Fit the model
out = CBS_RC(Choice,Amount1,Prob1,Amount2,Prob2,2)

# Plot the choices (x = Delay, y = relative amount : 20 / risky amount)
plot(Prob1[Choice==1],20/Amount1[Choice==1],type = 'p',col="blue",xlim=c(0, 1), ylim=c(0, 1))
points(Prob1[Choice==0],20/Amount1[Choice==0],type = 'p',col="red")

# Plot the fitted CBS
x = seq(0,1,.01)
lines(x,CBSfunc(out$xpos,out$ypos,x))