228,070 responses from 53,608 respondents to 3 items.
One of 5 tables from the same source; this one is the immigration table. The others are listed under Related tables.
| Description | London Bridge Attack 2017 panel survey; immigration policy support items (imm1–imm3); N≈53608; 1–5 Likert; wave=pre/during/post attack |
|---|---|
| Reference | Germann, M., Godefroidt, A., & Mendez, F. (2026). Does Islamist Terrorism Still Affect Political Attitudes? European Journal of Political Research (forthcoming). Replication data: doi:10.7910/DVN/ALYGQS |
| DOI | 10.1017/S1475676526101017 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/ALYGQS |
| Responses | 228,070 |
|---|---|
| Respondents | 53,608 |
| Items | 3 |
| Response categories | 5 |
| Responses per respondent | 4.254 |
| Responses per item | 76023.333 |
| Density | 1.418 |
| Longitudinal | TRUE |
| age range | Adult (18+) |
|---|---|
| sample | Internet-based |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | ger |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | WhoGetsMyVoteUK 2017 voting advice application: immigration policy statements (anti-immigration scale) |
|---|---|
| Mean words per item | 14 |
| Mean characters per item | 83.667 |
| Mean characters per response | 14.800 |
| Flesch-Kincaid grade level | 9.209 |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, germann_2026_terrorism.py. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.
| Column | What it is | Source column |
|---|---|---|
| IRW standard columns | ||
id | IRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task). | made in the build script |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
wave | IRW standard Longitudinal wave indicator. | not traced |
| Respondent covariates | ||
cov_age | Covariate | age |
cov_edu | Covariate | edu |
cov_gender | Covariate | gender |
cov_lr | Covariate | lr |
cov_pol_interest | Covariate | pol_interest |
cov_region | Covariate | region |
What item codes and covariate values stand for is in the source’s codebook, Codebook (sheet in update-metaanalysis-data.xlsx).
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("germann_2026_immigration")
# Python
pip install irw
import irw
df = irw.fetch("germann_2026_immigration")
@article{Germann_2026, title={Does Islamist terrorism still affect political attitudes?}, ISSN={1475-6765}, url={http://dx.doi.org/10.1017/S1475676526101017}, DOI={10.1017/s1475676526101017}, journal={European Journal of Political Research}, publisher={Cambridge University Press (CUP)}, author={Germann, Micha and Godefroidt, Amélie and Mendez, Fernando}, year={2026}, month=Apr, pages={1–21} }
| IRW version | v549 |
|---|---|
| Redivis dataset | item_response_warehouse_2 v33.0 |
| Redivis dataset DOI | 10.57761/6m04-m698 |
| Manifest pin for this IRW version | v33.0 |
| Metadata source | irw_meta v39.0 |