9,892 rated or chosen profiles from 496 respondents, in up to 10 tasks of 2 profiles varying on 6 attributes.
One of 3 tables from the same source; this one is the india table. The others are listed under Related tables.
| Description | Women of reproductive age in New Delhi, India (n = 496; 2017-2018, interviewer-administered on a tablet) chose between two options of a hypothetical contraceptive microarray patch in 10 discrete-choice tasks, options described by 6 attributes (pain, skin reaction, location, size, duration of protection, effect on menstruation) with illustrations; level text in Hindi. |
|---|---|
| Reference | FHI 360. (2020). Discreet choice experiment survey for development of a contraceptive microarray patch in India and Nigeria (FHI360 2017-2018) [Data set]. Harvard Dataverse. |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/TOSSWN |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 496 |
|---|---|
| Rows (one per respondent, task and profile) | 9,892 |
| Tasks per respondent (most) | 10 |
| Profiles per task | 2 |
| Attributes | 6 |
| Tasks with no profile chosen | 0 |
| Topic | health covid |
|---|---|
| A profile represents | product service |
| Country | IN |
| Language shown | hi |
| Language of stored levels | hi |
| Task order | recorded in the deposit |
| Profile position | recorded in the deposit |
Outcomes:
| choice | Look carefully at the features of the two method options. Which of these methods do you prefer? (translated) [choice, forced] |
|---|
attr_durationattr_locationattr_menstruationattr_painattr_sizeattr_skin_reactionchoiceidprofiletask
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("fhi360_2020_mnp_india", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("fhi360_2020_mnp_india", source="conj")
@misc{https://doi.org/10.7910/dvn/tosswn,
doi = {10.7910/DVN/TOSSWN},
url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/TOSSWN},
author = {{FHI 360}},
keywords = {Medicine, Health and Life Sciences, DCE, choice, preference, contraception, microarray patch, India, Nigeria},
title = {Discreet Choice Experiment Survey for Development of a Contraceptive Microarray Patch in India and Nigeria (FHI360 2017-2018)},
publisher = {Harvard Dataverse},
year = {2020}
}
| 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 |