SDT probit models for deception research - R

Mircea Zloteanu

SDT probit models for deception research - R

Mircea Zloteanu

Faculty of Business and Social Sciences (FBSS)

Research output: Software/Web development

Abstract

An R script for analysing veracity data (truth/lies) using a Bayesian generalized linear model with a Bernoulli probability distribution and a probit link function, aka. a Probit mixed-effects model, aka. a Signal Detection Theory (SDT) model. The script provides information on running the model, assessing convergence, conducting "post hoc" comparisons, and assessing model fit (and selecting the "best" model).

Original language	English
Publication status	Published - 18 Oct 2022

Bibliographical note

For more details on the methods proposed in the script and a theoretical explanation of its utility, see the accompanying conference presentation 'Stop aggregating veracity judgements! The benefits and necessity of proper data analysis' (see Related Records)

Keywords

R script
SDT
probit model
mixed effects model
analysis
Bayesian

Access to Document

https://doi.org/10.17605/OSF.IO/ABTS4

Stop aggregating veracity judgements! The benefits and necessity of proper data analysis
Zloteanu, M., 18 Oct 2022.
Research output: Contribution to conference › Paper › peer-review

Cite this

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abstract = "An R script for analysing veracity data (truth/lies) using a Bayesian generalized linear model with a Bernoulli probability distribution and a probit link function, aka. a Probit mixed-effects model, aka. a Signal Detection Theory (SDT) model. The script provides information on running the model, assessing convergence, conducting {"}post hoc{"} comparisons, and assessing model fit (and selecting the {"}best{"} model).",

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PY - 2022/10/18

Y1 - 2022/10/18

N2 - An R script for analysing veracity data (truth/lies) using a Bayesian generalized linear model with a Bernoulli probability distribution and a probit link function, aka. a Probit mixed-effects model, aka. a Signal Detection Theory (SDT) model. The script provides information on running the model, assessing convergence, conducting "post hoc" comparisons, and assessing model fit (and selecting the "best" model).

AB - An R script for analysing veracity data (truth/lies) using a Bayesian generalized linear model with a Bernoulli probability distribution and a probit link function, aka. a Probit mixed-effects model, aka. a Signal Detection Theory (SDT) model. The script provides information on running the model, assessing convergence, conducting "post hoc" comparisons, and assessing model fit (and selecting the "best" model).

KW - R script

KW - SDT

KW - probit model

KW - mixed effects model

KW - analysis

KW - Bayesian

M3 - Software/Web development

ER -

SDT probit models for deception research - R

Abstract

Bibliographical note

Keywords

Access to Document

Fingerprint

Research output

Stop aggregating veracity judgements! The benefits and necessity of proper data analysis

Cite this