Package: sate 3.1.1

Barry Edwards

sate: Scientific Analysis of Trial Errors (SATE)

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.

Authors:Barry Edwards [aut, cre]

sate_3.1.1.tar.gz
sate_3.1.1.tar.gz(r-4.7-any)sate_3.1.1.tar.gz(r-4.6-any)
sate_3.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
sate/json (API)

# Install 'sate' in R:
install.packages('sate', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.92 score 42 scripts 511 downloads 1 mentions 22 exports 12 dependencies

Last updated from:ddfb1ba58d. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK152
source / vignettesOK201
linux-release-x86_64OK139
wasm-releaseOK161

Exports:as.jury.pointas.jury.statsbasic.plot.gridcompact_harm_plotcompare.juror.statscompare.jury.statsdeliberatedeliberate.civilencode.cloud.respondent.variablesget_pG_by_kgraph.effect.defendantgraph.estimateprob_ord_from_poolprob.ordered.verdictsselect.with.strikessim.as.jury.statssim.compare.jury.statsstate.demographic.infotarget.population.demographicstransition.matrixtransition.matrix.orderedweights_for_population

Dependencies:DBIellipselatticeMASSMatrixminqamitoolsnumDerivRcppRcppArmadillosurveysurvival

Readme and manuals

Help Manual

Help pageTopics
Calculates probability a jury will find defendant guilty based on juror preferencesas.jury.point
Calculates probability a jury will find defendant guilty based on juror preferences, with standard error and confidence intervalas.jury.stats
Creates the shell of a plot showing relationship between jury pool preferences and jury verdict probabilitiesbasic.plot.grid
Creates the shell of a plot used to display estimate of harm relative to harm thresholdcompact_harm_plot
Estimates juror-level differences based on sample statistics (from survey)compare.juror.stats
Estimates jury-level differences based on juror-level statistics with inferential statisticscompare.jury.stats
Deliberation functiondeliberate
Deliberation function for civil trials (proposed)deliberate.civil
Encodes Cloud Research respondent information in form suitable for calculating sampling weightsencode.cloud.respondent.variables
Calculates vector of probabilities that jury with jury_n will return a guilty verdictget_pG_by_k
Plots jury-level differences based on juror-level statistics with effect-on-defendant displayedgraph.effect.defendant
Plots probability of a guilty verdict with confidence interval based on juror-level statisticsgraph.estimate
Dataset of Observed Deliberationsobserved.deliberations
verdict probabilities based on jury pool sentiment for ordered verdict options.prob_ord_from_pool
Absorption probabilities for ordered-category jury modelsprob.ordered.verdicts
Generates the distribution of initial votes for guilty verdict on juriesselect.with.strikes
Estimates jury-level probability of guilty verdict based on juror-level statistics based on empirical datasim.as.jury.stats
Estimates jury-level differences based on juror-level statistics using simulations based on empirical datasim.compare.jury.stats
State Demographic Informationstate.demographic.info
Looks up and returns key demographic statistics for target state to be used for calculating sample weightstarget.population.demographics
Creates and Returns a Transition Probability Matrix for Deliberating Criminal Jury.transition.matrix
Build column-stochastic transition matrix for ordered verdict optionstransition.matrix.ordered
Calculates survey weights given respondent information and target population demographicsweights_for_population