deliberate

The deliberate function returns a jury verdict based on a simulation of deliberation
 as a modified tug-of-war between two verdict factions. Can be called directly, but is
 meant to be called many times to generate verdict probabilities based on g_votes and jury_n values.

Bundles functions used to analyze the harmfulness of trial errors in criminal trials.
Functions in the Scientific Analysis of Trial Errors ('SATE') package help users estimate the
probability that a jury will find a defendant guilty given jurors' preferences for a guilty
verdict and the uncertainty of that estimate. Users can also compare actual and hypothetical
trial conditions to conduct harmful error analysis. The relationship between individual jurors'
verdict preferences and the probability that a jury returns a guilty verdict has been studied
by Davis (1973) <doi:10.1037/h0033951>; MacCoun & Kerr (1988) <doi:10.1037/0022-3514.54.1.21>,
and Devine et el. (2001) <doi:10.1037/1076-8971.7.3.622>, among others.

Barry Edwards

sate

Scientific Analysis of Trial Errors (SATE)

deliberate function

<dl><dt>g_votes</dt>
<dd>Initial number of votes for guilty verdict (same as K value).</dd>
<dt>jury_n</dt>
<dd>Size of the jury (i.e. 4, 6, 8, 12, or 16).</dd></dl>

Arguments

Deliberation function — deliberate

<dl>

<dt>g_votes</dt>
<dd>Initial number of votes for guilty verdict (same as K value).</dd>


<dt>jury_n</dt>
<dd>Size of the jury (i.e. 4, 6, 8, 12, or 16).</dd>

</dl>

deliberate: Deliberation function

Description

Usage

Value

Arguments

Examples