betareg (version 2.4-0)

MockJurors: Confidence of Mock Jurors in Their Verdicts

Description

Data with responses of naive mock jurors to the conventional conventional two-option verdict (guilt vs. acquittal) versus a three-option verdict setup (the third option was the Scottish 'not proven' alternative), in the presence/absence of conflicting testimonial evidence.

Usage

data("MockJurors")

source

Example 1 from http://psychology3.anu.edu.au/people/smithson/details/betareg/betareg.html

Details

The data were collected by Daily (2004) among first-year psychology students at Australian National University. Smithson and Verkuilen (2006) employed the data scaling the original confidence (on a scale 0--100) to the open unit interval: ((original_confidence/100) * 103 - 0.5) / 104.

The original coding of conflict in the data provided from Smithson's homepage is -1/1 which Smithson and Verkuilen (2006) describe to mean no/yes. However, all their results (sample statistics, histograms, etc.) suggest that it actually means yes/no which was employed in MockJurors.

References

Deady, S. (2004). The Psychological Third Verdict: 'Not Proven' or 'Not Willing to Make a Decision'? Unpublished honors thesis, The Australian National University, Canberra.

Smithson, M., and Verkuilen, J. (2006). A Better Lemon Squeezer? Maximum-Likelihood Regression with Beta-Distributed Dependent Variables. Psychological Methods, 11(7), 54--71.

See Also

betareg, ReadingSkills, StressAnxiety

Examples

data("MockJurors", package = "betareg")
library("lmtest")

## Smithson & Verkuilen (2006, Table 1)
## variable dispersion model
## (NOTE: numerical rather than analytical Hessian is used for replication,
##  Smithson & Verkuilen erroneously compute one-sided p-values)
mj_vd <- betareg(confidence ~ verdict * conflict | verdict * conflict,
  data = MockJurors, hessian = TRUE)
summary(mj_vd)

## model selection for beta regression: null model, fixed dispersion model (p. 61)
mj_null <- betareg(confidence ~ 1 | 1, data = MockJurors)
mj_fd <-   betareg(confidence ~ verdict * conflict | 1, data = MockJurors)
lrtest(mj_null, mj_fd)
lrtest(mj_null, mj_vd)
## McFadden's pseudo-R-squared
1 - as.vector(logLik(mj_null)/logLik(mj_vd))

## visualization
if(require("lattice")) {
  histogram(~ confidence | conflict + verdict, data = MockJurors,
    col = "lightgray", breaks = 0:10/10, type = "density")
}

## see demo("SmithsonVerkuilen2006", package = "betareg") for more details