Goel Ashish, Gross Alden
Department of Medicine, University College of Medical Sciences, University of Delhi, Delhi, India.
Department of Epidemiology and Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA.
Int Psychogeriatr. 2019 Sep;31(9):1331-1341. doi: 10.1017/S1041610218001746. Epub 2019 Feb 20.
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.
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.
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.
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.
印度纵向老龄化研究（LASI）旨在收集可与健康与退休调查（HRS）相媲美的数据，因此采用了HRS的研究工具。然而，在改编认知测试之前进行严格的心理测量评估，可能会因印度各邦在教育、种族和城市化程度等方面的差异而显示出偏差。在本分析中，我们评估了各项目是否因识字率、城市化程度和教育状况而表现出项目功能差异（DIF）。
我们计算了LASI中每个项目的比例以及人口统计学特征的加权描述性统计量。接下来，我们使用Mplus软件实施的对齐方法测试DIF，以评估项目层面的测量差异。
我们发现，LASI访谈中的认知项目因教育和识字率而存在偏差，但不因城市化程度而存在偏差。与动物（单词）流畅性相关的项目显示出DIF。该模型将正确识别总理评为最难的二元反应项目，而一周中的日期和算术项目则相对较容易。
我们的研究将有助于在教育、识字率和城市化程度之间进行比较，以支持对认知状态差异的分析。这将有助于未来的工具开发工作，识别某些亚组中潜在的问题项目。
