9,964 rated or chosen profiles from 1,000 respondents, in up to 5 tasks of 2 profiles varying on 7 attributes.
| Description | Criminal-opportunity conjoint: 1,000 adults from a national sample (country not stated in the deposit; payouts in dollars) each chose between two hypothetical criminal opportunities in 5 tasks, varying victim, co-offenders, completion time, payout, payout timing, arrest chance and punishment; forced choice. |
|---|---|
| Reference | Krajewski, A. T., Pickett, J. T., & Jacobs, B. A. (2025). How people choose between criminal opportunities. Criminology, 63(3), 639-660. |
| DOI | 10.1111/1745-9125.70006 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/8DCXQF |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 1,000 |
|---|---|
| Rows (one per respondent, task and profile) | 9,964 |
| Tasks per respondent (most) | 5 |
| Profiles per task | 2 |
| Attributes | 7 |
| Tasks with no profile chosen | 0 |
| Topic | crime justice policing |
|---|---|
| A profile represents | scenario |
| Country | unknown |
| Language shown | unknown |
| Language of stored levels | en |
| Randomization restrictions | unknown |
| Task order | inferred from row order |
| Profile position | inferred from row order |
Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.
Outcomes:
| choice | Criminal opportunity chosen (paraphrase) [choice, forced] |
|---|
attr_chanceofarrestattr_completiontimeattr_peopleinvolvedattr_possiblepunishmentattr_timeuntilpayoutattr_victimattr_yourpayoutchoicecov_attention_passcov_prior_offendingcov_selfcontrol_avgidprofiletask
The layout (one row per respondent, task and profile; choice/rating outcomes; attr_ columns holding each attribute level as displayed) is defined in the IRW conjoint standard. What the outcomes asked is under Design above.
Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("krajewski_2025_criminal_opportunities", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("krajewski_2025_criminal_opportunities", source="conj")
@article{Krajewski_2025, title={How people choose between criminal opportunities}, volume={63}, ISSN={1745-9125}, url={http://dx.doi.org/10.1111/1745-9125.70006}, DOI={10.1111/1745-9125.70006}, number={3}, journal={Criminology}, publisher={Wiley}, author={Krajewski, Andrew T. and Pickett, Justin T. and Jacobs, Bruce A.}, year={2025}, month=Aug, pages={639–660} }
| IRW version | v584 |
|---|---|
| Redivis dataset | irw_conjoint v4.2 |
| Redivis dataset DOI | 10.57761/qkye-q530 |
| Manifest pin for this IRW version | v4.2 |
| Metadata source | irw_meta v44.0 |