# WeatherTask: Weather Task With Priming and Precise and Imprecise... In betareg: Beta Regression

## Description

In this study participants were asked to judge how likely Sunday is to be the hottest day of the week.

## Usage

 `1` ```data(WeatherTask) ```

## Format

A data frame with 345 observations on the following 3 variables.

`priming`

a factor with levels `two-fold` (case prime) and `seven-fold` (class prime).

`eliciting`

a factor with levels `precise` and `imprecise` (lower and upper limit).

`agreement`

a numeric vector, probability indicated by participants or the average between minimum and maximum probability indicated.

## Details

All participants in the study were either first- or second-year undergraduate students in psychology, none of whom had a strong background in probability or were familiar with imprecise probability theories.

For `priming` the questions were:

two-fold

[What is the probability that] the temperature at Canberra airport on Sunday will be higher than every other day next week?

seven-fold

[What is the probability that] the highest temperature of the week at Canberra airport will occur on Sunday?

For `eliciting` the instructions were if

precise

to assign a probability estimate,

imprecise

to assign a lower and upper probability estimate.

## References

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.

## Examples

 ```1 2 3 4 5 6``` ```data("WeatherTask", package = "betareg") library("flexmix") wt_betamix <- betamix(agreement ~ 1, data = WeatherTask, k = 2, extra_components = extraComponent(type = "betareg", coef = list(mean = 0, precision = 2)), FLXconcomitant = FLXPmultinom(~ priming + eliciting)) ```

betareg documentation built on May 29, 2017, 11:30 a.m.