WeatherTask | R Documentation |
In this study participants were asked to judge how likely Sunday is to be the hottest day of the week.
data("WeatherTask", package = "betareg")
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.
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:
[What is the probability that] the temperature at Canberra airport on Sunday will be higher than every other day next week?
[What is the probability that] the highest temperature of the week at Canberra airport will occur on Sunday?
For eliciting
the instructions were if
to assign a probability estimate,
to assign a lower and upper probability estimate.
Taken from Smithson et al. (2011) supplements.
Smithson M, Merkle EC, Verkuilen J (2011). Beta Regression Finite Mixture Models of Polarization and Priming. Journal of Educational and Behavioral Statistics, 36(6), 804–831. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3102/1076998610396893")}
Smithson M, Segale C (2009). Partition Priming in Judgments of Imprecise Probabilities. Journal of Statistical Theory and Practice, 3(1), 169–181.
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))
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