[Article Review] Unlocking the Potential of Fit Index Difference Values in Exploratory Factor Analysis

Reference

Finch, W. H. (2020). Using Fit Statistic Differences to Determine the Optimal Number of Factors to Retain in an Exploratory Factor Analysis. Educational and Psychological Measurement, 80(2), 217-241. https://doi.org/10.1177/0013164419865769

Review

In this article, the author investigates the effectiveness of model fit indices in determining the optimal number of factors to retain in exploratory factor analysis (EFA). The article emphasizes the absence of a universally optimal statistical tool for resolving this issue and discusses the mixed results of using model fit indices in conjunction with normally distributed indicators and categorical indicators.

Finch (2020) conducted a simulation study comparing the performance of fit index difference values and parallel analysis, a widely used and reliable method for determining factor retention. The results demonstrated that fit index difference values outperformed parallel analysis for categorical indicators and for normally distributed indicators when factor loadings were small. This finding highlights the potential of fit index difference values as a viable alternative to parallel analysis in certain situations.

The implications of Finch's (2020) findings have a considerable impact on the field of social sciences research. By understanding the effectiveness of fit index difference values in determining the optimal number of factors to retain in EFA, researchers can make more informed decisions when selecting the appropriate statistical tool. This, in turn, can lead to more accurate and valid results, enhancing the quality of research in the social sciences.

[Article Review] A New Look at Cohort Trend and Underlying Mechanisms in Cognitive Functioning

Reference

Zheng, H. (2021). A New Look at Cohort Trend and Underlying Mechanisms in Cognitive Functioning. The Journals of Gerontology: Series B, 76(8), 1652-1663. https://doi.org/10.1093/geronb/gbaa107

Review

In this study, Zheng (2021) examines trends and underlying mechanisms in cognitive functioning across seven decades of birth cohorts, from the Greatest Generation to the Baby Boomers. The study uses data from the Health and Retirement Study and measures cognitive functioning as a summary score on a 35-point cognitive battery of items. The author finds that cognitive functioning has been improving from the Greatest Generation to Late Children of Depression and War Babies, but then significantly declines since the Early-Baby Boomers and continues into Mid-Baby Boomers. This pattern is observed universally across genders, races/ethnicities, education groups, occupations, income, and wealth quartiles.

The author also finds that the worsening cognitive functioning among Baby Boomers cannot be attributed to childhood conditions, adult education, or occupation. Instead, it can be attributed to lower household wealth, lower likelihood of marriage, higher levels of loneliness, depression, and psychiatric problems, and more cardiovascular risk factors (e.g., obesity, physical inactivity, hypertension, stroke, diabetes, and heart disease). The implications of this study suggest that the worsening cognitive functioning among Baby Boomers may potentially reverse past favorable trends in dementia as they reach older ages, and cognitive impairment becomes more common if no effective interventions and policy responses are in place.

Overall, this article provides important insights into the cohort trend and underlying mechanisms in cognitive functioning, particularly among Baby Boomers. The findings have implications for dementia prevention and intervention policies, highlighting the importance of addressing risk factors such as cardiovascular disease, depression, and loneliness. The article's limitations include the study's reliance on self-reported data and the exclusion of certain groups such as those living in nursing homes or with severe cognitive impairment. Nonetheless, the study contributes to our understanding of cognitive functioning and its implications for healthy aging.