Partition-primed Probability Judgement Task for Car Dealership
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.
A data frame with 155 observations on the following 3 variables.
a factor with levels
Salespersonindicating the condition.
a numeric vector of the estimated probability.
a numeric vector of the NFCC scale.
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.
task the questions were:
What is the probability that a customer trades in a coupe?
What is the probability that a customer buys a car from Carlos?
Smithson, M., Merkle, E.C., and Verkuilen, J. (in press). Beta Regression Finite Mixture Models of Polarization and Priming. Journal of Educational and Behavioral Statistics.
Smithson, M., and Segale, C. (2009). Partition Priming in Judgments of Imprecise Probabilities. Journal of Statistical Theory and Practice, 3(1), 169–181.
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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))