303,921 responses from 697 respondents to 373 items.
| Description | Roll-call vote responses from the 52nd to 54th U.S. House of Representatives. |
|---|---|
| Reference | Shin, S. (2024). Measuring Issue Specific Ideal Points from Roll Call Votes (Doctoral dissertation, Ph. D. thesis, Harvard University. Ph. D. Candidate, Department of Government and Institute for Quantitative Social Science). |
| Licence | GPL-3.0 |
| Source data | https://github.com/sooahnshin/issueirt/blob/main/data/us1890s_votes.rda |
| Responses | 303,921 |
|---|---|
| Respondents | 697 |
| Items | 373 |
| Response categories | 2 |
| Responses per respondent | 436.042 |
| Responses per item | 814.802 |
| Density | 1.169 |
| Longitudinal | TRUE |
| age range | Adult (18+) |
|---|---|
| sample | Targeted/specific |
| construct type | Behavioral, Opinion/attitude |
| measurement tool | Observational rating |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | Legislative preference |
iditemrespwave
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("issueirt_votes_shin_2024")
# Python
pip install irw
import irw
df = irw.fetch("issueirt_votes_shin_2024")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_2 v19.0 |
| Redivis dataset DOI | 10.57761/qtx5-4m80 |
| Manifest pin for this IRW version | v19.0 |
| Metadata source | irw_meta v23.0 |