Ashish Goel1, Alden Gross2. 1. Department of Medicine,University College of Medical Sciences, University of Delhi,Delhi,India. 2. Department of Epidemiology and Mental Health,Johns Hopkins University Bloomberg School of Public Health, Baltimore,MD,USA.
Abstract
ABSTRACTIntroduction:The Longitudinal Aging Study in India (LASI) was initiated to capture data to be comparable to the Health and Retirement Survey (HRS) and hence used study instruments from the HRS. However, a rigorous psychometric evaluation before adaptation of cognitive tests may have indicated bias due to diversities across Indian states such as education, ethnicity, and urbanicity. In the present analysis, we evaluated if items show differential item functioning (DIF) by literacy, urbanicity, and education status. METHODS: We calculated proportions for each item and weighted descriptive statistics of demographic characteristics in LASI. Next, we evaluated item-level measurement differences by testing for DIF using the alignment approach implemented using Mplus software. OBSERVATION: We found that cognitive items in the LASI interview demonstrate bias by education and literacy, but not urbanicity. Items relating to animal (word) fluency show DIF. The model rates correct identification of the prime minister as the most difficult binary response item whereas the day of the week and numeracy items are rated comparatively easier. CONCLUSIONS: Our study would facilitate comparison across education, literacy and urbancity to support analyses of differences in cognitive status. This would help future instrument development efforts by recognizing potentially problematic items in certain subgroups.
ABSTRACTIntroduction:The Longitudinal Aging Study in India (LASI) was initiated to capture data to be comparable to the Health and Retirement Survey (HRS) and hence used study instruments from the HRS. However, a rigorous psychometric evaluation before adaptation of cognitive tests may have indicated bias due to diversities across Indian states such as education, ethnicity, and urbanicity. In the present analysis, we evaluated if items show differential item functioning (DIF) by literacy, urbanicity, and education status. METHODS: We calculated proportions for each item and weighted descriptive statistics of demographic characteristics in LASI. Next, we evaluated item-level measurement differences by testing for DIF using the alignment approach implemented using Mplus software. OBSERVATION: We found that cognitive items in the LASI interview demonstrate bias by education and literacy, but not urbanicity. Items relating to animal (word) fluency show DIF. The model rates correct identification of the prime minister as the most difficult binary response item whereas the day of the week and numeracy items are rated comparatively easier. CONCLUSIONS: Our study would facilitate comparison across education, literacy and urbancity to support analyses of differences in cognitive status. This would help future instrument development efforts by recognizing potentially problematic items in certain subgroups.
Entities:
Keywords:
LASI; Longitudinal Aging Study in India; cognition; differential item functioning
Authors: Lindsay C Kobayashi; Alden L Gross; Laura E Gibbons; Doug Tommet; R Elizabeth Sanders; Seo-Eun Choi; Shubhabrata Mukherjee; Maria Glymour; Jennifer J Manly; Lisa F Berkman; Paul K Crane; Dan M Mungas; Richard N Jones Journal: J Gerontol B Psychol Sci Soc Sci Date: 2021-10-30 Impact factor: 4.942
Authors: Jet M J Vonk; Alden L Gross; Andrea R Zammit; Laiss Bertola; Justina F Avila; Roos J Jutten; Leslie S Gaynor; Claudia K Suemoto; Lindsay C Kobayashi; Megan E O'Connell; Olufisayo Elugbadebo; Priscilla A Amofa; Adam M Staffaroni; Miguel Arce Rentería; Indira C Turney; Richard N Jones; Jennifer J Manly; Jinkook Lee; Laura B Zahodne Journal: PLoS One Date: 2022-02-25 Impact factor: 3.240
Authors: E Nichols; J A Deal; B K Swenor; A G Abraham; N M Armstrong; K Bandeen-Roche; M C Carlson; M Griswold; F R Lin; T H Mosley; P Y Ramulu; N S Reed; A R Sharrett; A L Gross Journal: BMC Med Res Methodol Date: 2022-03-27 Impact factor: 4.612