transition.matrix

Returns a (jury_n + 1) by (jury_n + 1) matrix of probabilities.
Columns represent current state and rows represent next state. Column values sum to 1.
Depending on use, you may want to transpose rows and columns.

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 conceptual framework is discussed
by Barry Edwards, A Scientific Framework for Analyzing the Harmfulness of Trial Errors,
UCLA Criminal Justice Law Review (2024) <doi:10.5070/CJ88164341> and Barry Edwards,
If The Jury Only Knew: The Effect Of Omitted Mitigation Evidence On The Probability Of A Death Sentence,
Virginia Journal of Social Policy & the Law (2025)
<https://vasocialpolicy.org/wp-content/uploads/2025/05/Edwards-If-The-Jury-Only-Knew.pdf>.
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)

transition.matrix function

<dl><dt>jury_n</dt>
<dd>The number of jurors.</dd></dl>

Arguments

Creates and Returns a Transition Probability Matrix for Deliberating Criminal Jury. — transition.matrix

<dl>

<dt>jury_n</dt>
<dd>The number of jurors.</dd>

</dl>

transition.matrix: Creates and Returns a Transition Probability Matrix for Deliberating Criminal Jury.

Description

Usage

Value

Arguments

Examples