MockJurors {betareg} | R Documentation |

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.

data("MockJurors")

A data frame containing 104 observations on 3 variables.

- verdict
factor indicating whether a two-option or three-option verdict is requested. (A sum contrast rather than treatment contrast is employed.)

- conflict
factor. Is there conflicting testimonial evidence? (A sum contrast rather than treatment contrast is employed.)

- confidence
jurors degree of confidence in his/her verdict, scaled to the open unit interval (see below).

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`

.

Example 1 from Smithson and Verkuilen (2006) supplements.

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*Unpublished honors thesis*, The Australian National University, Canberra.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.

`betareg`

, `ReadingSkills`

, `StressAnxiety`

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

[Package *betareg* version 3.1-4 Index]