Showing papers by "John J. McArdle published in 2011"

Tracking Cognition–Health Changes From 55 to 95 Years of Age

Abstract: Objectives. Among the key targets of inquiry in cognitive aging are (1) the description of cognitive changes with advancing age and (2) the association of such cognitive changes with modulating factors in the changing epidemiological context.

Longitudinal Dynamic Analyses of Cognition in the Health and Retirement Study Panel.

Abstract: The purpose of this paper is to highlight some classic issues in the measurement of change and to show how contemporary solutions can be used to deal with some of these issues. Five classic issues will be raised here: (1) Separating individual changes from group differences; (2) options for incomplete longitudinal data over time, (3) options for nonlinear changes over time; (4) measurement invariance in studies of changes over time; and (5) new opportunities for modeling dynamic changes. For each issue we will describe the problem, and then review some contemporary solutions to these problems base on Structural Equation Models (SEM). We will fit these SEM to using existing panel data from the Health & Retirement Study (HRS) cognitive variables. This is not intended as an overly technical treatment, so only a few basic equations are presented, examples will be displayed graphically, and more complete references to the contemporary solutions will be given throughout.

RESEARCH ARTICLE Growth Rate Models: Emphasizing Growth Rate Analysis through Growth Curve Modeling

Abstract: To emphasize growth rate analysis, we develop a general method to reparametrize growth curve models to analyze rates of growth for a variety of growth trajectories, such as quadratic and exponential growth. The resulting growth rate models are shown to be related to rotations of growth curves. Estimated conveniently through growth curve modeling techniques, growth rate models have advantages above and beyond traditional growth curve models. The proposed growth rate models are used to analyze longitudinal data from the National Longitudinal Study of Youth (NLSY) on children’s mathematics performance scores including covariates of gender and behavioral problems (BPI). Individual differences are found in rates of growth from age 6 to 11. Associations with BPI, gender, and their interaction to rates of growth are found to vary with age. Implications of the models and the findings are discussed.

Gender Differences in Cognition Among Older Adults in China

Abstract: In this paper, the authors model gender differences in cognitive ability in China using a new sample of middle-aged and older Chinese respondents. Modeled after the American Health and Retirement Survey (HRS), the CHARLS Pilot survey respondents are 45 years and older in two quite distinct provinces — Zhejiang a high growth industrialized province on the East Coast, and Gansu, a largely agricultural and poor Province in the West. Their measures of cognition in CHARLS relies on two measures that proxy for different dimensions of adult cognition — episodic memory and intact mental status. They relate both these childhood health measures to adult health and SES outcomes during the adult years. They find large cognitive differences to the detriment of women that were mitigated by large gender differences in education among these generations of Chinese people. These gender differences in cognition are especially concentrated within poorer communities in China with gender difference being more sensitive to community level attributes than to family level attributes, with economic resources. In traditional poor Chinese communities, there are strong economic incentives to favor boys at the expense of girls not only in their education outcomes, but in their nutrition and eventually their adult height. These gender cognitive differences have been steadily decreasing across birth cohorts as the economy of China grew rapidly. Among younger cohorts of young adults in China, there is no longer any gender disparity in cognitive ability.