cdm_mentalhealth_tan_2023_rapi

16,537 responses from 719 respondents to 23 items.

About this table

DescriptionCognitive Diagnosis Modeling for characterizing mental health symptom profiles, Rutgers Alcohol Problem Index (RAPI)
ReferenceTan, Z., De la Torre, J., Ma, W., Huh, D., Larimer, M. E., & Mun, E. Y. (2023). A tutorial on cognitive diagnosis modeling for characterizing mental health symptom profiles using existing item responses. Prevention Science, 24(3), 480-492.
DOI10.1007/s11121-022-01346-8
LicenceCC BY 4.0
Source datahttps://data.mendeley.com/datasets/97bzg6z28h/1

Size and shape

Responses16,537
Respondents719
Items23
Response categories5
Responses per respondent23
Responses per item719
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleEducational
construct typeBehavioral, Physical health/functioning
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng
construct nameRutgers Alcohol Problem Index (RAPI)

Item text

This table has item text in the IRW: the wording administered to respondents, not just the response codes.

InstrumentCognitive Diagnosis Modeling for characterizing mental health symptom profiles, Rutgers Alcohol Problem Index (RAPI)
Mean words per item9.304
Mean characters per item49.348
Mean characters per response10.200
Flesch-Kincaid grade level4.636

Columns

iditemqmatrix__anqmatrix__apqmatrix__deqmatrix__horesp

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python:

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("cdm_mentalhealth_tan_2023_rapi")
# Python
pip install irw

import irw
df = irw.fetch("cdm_mentalhealth_tan_2023_rapi")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse v53.0
Redivis dataset DOI10.57761/4g08-xt41
Manifest pin for this IRW versionv53.0
Metadata sourceirw_meta v23.0