betareg (version 3.2-1)

CarTask: Partition-Primed Probability Judgement Task for Car Dealership

Description

In this study participants were asked to judge how likely it is that a customer trades in a coupe or that a customer buys a car form a specific salesperson out of four possible salespersons.

Usage

data("CarTask", package = "betareg")

Format

A data frame with 155 observations on the following 3 variables.

task

a factor with levels Car and Salesperson indicating the condition.

probability

a numeric vector of the estimated probability.

NFCCscale

a numeric vector of the NFCC scale.

Details

All participants in the study were undergraduate students at The Australian National University, some of whom obtained course credit in first-year Psychology for their participation in the study.

The NFCC scale is a combined scale of the Need for Closure and Need for Certainty scales which are strongly correlated.

For task the questions were:

Car

What is the probability that a customer trades in a coupe?

Salesperson

What is the probability that a customer buys a car from Carlos?

References

Smithson, M., Merkle, E.C., and Verkuilen, J. (2011). Beta Regression Finite Mixture Models of Polarization and Priming. Journal of Educational and Behavioral Statistics, 36(6), 804--831. tools:::Rd_expr_doi("10.3102/1076998610396893")

Smithson, M., and Segale, C. (2009). Partition Priming in Judgments of Imprecise Probabilities. Journal of Statistical Theory and Practice, 3(1), 169--181.

Examples

data("CarTask", package = "betareg")
library("flexmix")
car_betamix <- betamix(probability ~ 1, data = CarTask, k = 3,
  extra_components = list(extraComponent(type = "uniform", coef = 1/2,
  delta = 0.01), extraComponent(type = "uniform", coef = 1/4, delta = 0.01)),
  FLXconcomitant = FLXPmultinom(~ task))