Showing papers by "John J. McArdle published in 2012"
TL;DR: The results support the dual contention that lifestyle engagement may buffer some of the cognitive changes observed in late life, and persons who are exhibiting poorer cognitive performance may also relinquish some lifestyle activities.
Abstract: Objective: Do lifestyle activities buffer normal aging-related declines in cognitive performance? The emerging literature will benefit from theoretically broader measurement of both lifestyle activities and cognitive performance, and longer-term longitudinal designs complemented with dynamic statistical analyses. We examine the temporal ordering of changes in lifestyle activities and changes in cognitive neuropsychological performance in older adults. Method: We assembled data (n = 952) across a 12-year (5-wave) period from the Victoria Longitudinal Study. Latent change score models were applied to examine whether (and in which temporal order) changes in physical, social, or cognitive lifestyle activities were related to changes in three domains of cognitive performance. Results: Two main results reflect the dynamic coupling among changes in lifestyle activities and cognition. First, reductions in cognitive lifestyle activities were associated with subsequent declines in measures of verbal speed, episodic memory, and semantic memory. Second, poorer cognitive functioning was related to subsequent decrements in lifestyle engagement, especially in social activities. Conclusions: The results support the dual contention that (a) lifestyle engagement may buffer some of the cognitive changes observed in late life, and (b) persons who are exhibiting poorer cognitive performance may also relinquish some lifestyle activities. (PsycINFO Database Record (c) 2011 APA, all rights reserved). Language: en
170 citations
TL;DR: Results indicate that recent increases in the lateral ventricle size were a leading indicator of subsequent declines in memory performance from age 60 to 90, and this extension of latent difference scores allows for testing hypotheses where recent changes are a primary predictor of subsequent changes.
Abstract: Latent difference score models (e.g., McArdle & Hamagami, 2001) are extended to include effects from prior changes to subsequent changes. This extension of latent difference scores allows for testing hypotheses where recent changes, as opposed to recent levels, are a primary predictor of subsequent changes. These models are applied to bivariate longitudinal data collected as part of the Baltimore Longitudinal Study of Aging on memory performance, measured by the California Verbal Learning Test, and lateral ventricle size, measured by structural MRIs. Results indicate that recent increases in the lateral ventricle size were a leading indicator of subsequent declines in memory performance from age 60 to 90.
157 citations
TL;DR: Li et al. as discussed by the authors found that Chinese women score much lower than do Chinese men, a gender difference that grows among older Chinese cohorts, suggesting that in traditional poor Chinese communities there are strong economic incentives to favor boys at the expense of girls.
Abstract: In this paper, we 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 Study (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-in a sense new and old China. Our cognition measures proxy for two different dimensions of adult cognition-episodic memory and intact mental status. On both measures, Chinese women score much lower than do Chinese men, a gender difference that grows among older Chinese cohorts. We relate both these cognition scores to schooling, urban residence, family and community levels of economic resources, and height. We find that cognition is more closely related to mean community resources than to family resources, especially for women, suggesting that in traditional poor Chinese communities there are strong economic incentives to favor boys at the expense of girls. We also find that these gender differences in cognitive ability have been steadily decreasing across birth cohorts as the economy of China grew rapidly. Among cohorts of young adults in China, there is no longer any gender disparity in cognitive ability. This parallels the situation in the United States where cognition scores of adult women actually exceed those of adult men.
119 citations
TL;DR: The findings suggest that depressive symptoms affect subsequent academic achievement and not the other way around, especially for Native Hawaiians compared with female non-Hawaiians.
Abstract: There is a relatively consistent negative relationship between adolescent depressive symptoms and educational achievement (e.g., grade point average [GPA]). However, the causal direction for this association is less certain due to the lack of longitudinal data with both indicators measured across at least 2 time periods and due to the lack of application of more sophisticated contemporary statistical techniques. We present multivariate results from a large longitudinal cohort-sequential study of high school students (N = 7,317) with measures of self-reported depressive symptoms and self-reported GPAs across multiple time points (following McArdle, 2009, and McArdle, Johnson, Hishinuma, Miyamoto, & Andrade, 2001) using an ethnically diverse sample from Hawai'i. Contemporary statistical techniques included bivariate dynamic structural equation modeling (DSEM), multigroup ethnic and gender DSEMs, ordinal scale measurement of key outcomes, and imputation for incomplete longitudinal data. The findings suggest that depressive symptoms affect subsequent academic achievement and not the other way around, especially for Native Hawaiians compared with female non-Hawaiians. We further discuss the scientific, applied, and methodological-statistical implications of the results, including the need for further theorizing and research on mediating variables. We also discuss the need for increased prevention, early intervention, screening, identification, and treatment of depressive symptoms and disorders. Finally, we argue for utilization of more contemporary methodological-statistical techniques, especially when violating parametric test assumptions.
65 citations
TL;DR: It is shown how to estimate both the latent curve model (LCM) and LCSM with the sem, lavaan, and OpenMx packages of the R software and how to read in, summarize, and plot data prior to analyses.
Abstract: In recent years the use of the Latent Curve Model (LCM) among researchers in social sciences has increased noticeably, probably thanks to contemporary software developments and to the availability of specialized literature. Extensions of the LCM, like the the Latent Change Score Model (LCSM), have also increased in popularity. At the same time, the R statistical language and environment, which is open source and runs on several operating systems, is becoming a leading software for applied statistics. We show how to estimate both the LCM and LCSM with the sem, lavaan, and OpenMx packages of the R software. We also illustrate how to read in, summarize, and plot data prior to analyses. Examples are provided on data previously illustrated by Ferrer, Hamagami, & McArdle, 2004. The data and all scripts used here are available on the first author's website.
46 citations
TL;DR: The authors provide an historical overview of the National Collegiate Athletic Association's (NCAA) academic reform, with a particular focus on the empirical basis for the decisions made, and examine the types of information the NCAA has collected and used to make decisions about academic policy.
Abstract: The purpose of this article is to provide an historical overview of the National Collegiate Athletic Association’s (NCAA) academic reform, with a particular focus on the empirical basis for the decisions made. The authors outline four eras of academic reform, examine the types of information the NCAA has collected and used to make decisions about academic policy, and explore the limits of such academic data.
28 citations
TL;DR: In this paper, the authors developed 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.
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 ages 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.
16 citations
TL;DR: In this paper, the authors used statistical simulation to calculate differential statistical power in dynamic structural equation models with groups and found that parameters that provide input into the change score that the transfer leads to affect power versus indirect pathways.
Abstract: This study used statistical simulation to calculate differential statistical power in dynamic structural equation models with groups (as in McArdle & Prindle, 2008). Patterns of between-group differences were simulated to provide insight into how model parameters influence power approximations. Chi-square and root mean square error of approximation (RMSEA) power approximation procedures were used to compare the effects of parameter manipulations and how researchers should interpret findings. The chi-square power of perfect fit calls for at least 270 individuals to detect moderate differences, whereas the RMSEA procedure of close fit seems to require as many as 1,450 participants. It is shown that parameters that provide input into the change score that the transfer leads to affect power versus indirect pathways. A discussion of differences in approximation values and future research directions follows.
12 citations
01 Jan 2012
11 citations
26 Sep 2012
TL;DR: This chapter is intended as an update of the previous chapter on “Growth Curve Analysis”, but here the use of the Latent Curve Analysis and Latent Change Scores approaches using Structural Equation Modeling (SEM) is emphasized.
Abstract: This chapter is intended as an update of our previous chapter on “Growth Curve Analysis” (McArdle & Nesselroade, 2003). But here we emphasize the use of the Latent Curve Analysis (LCA) and Latent Change Scores (LCS) approaches using Structural Equation Modeling (SEM). We consider some of the many questions that have been raised about this general topic during the last decade. We discuss technical and substantive features of contemporary model fitting and the inferences that follow. This presentation is not intended to be overly technical, and the parameters in these kinds of models can be estimated using standard computer programs which allow appropriate calculations. We start by providing basic definitions of LCA-SEM, and show how these lead to mean and covariance expectations, and the associated likelihood equations, and we then report some of our own illustrations applied to real data. We discuss alternative ways to achieve the same results, and this leads to other even more advanced alternatives. We suggest how these approaches can deal with incomplete longitudinal data and review important innovations in the basic LCA-SEM have occurred during the past decade. The final section summarizes and makes some predictions about the future of both LCA-SEM and LCS-SEM.
Keywords:
latent curves;
growth and changes;
latent change scores;
longitudinal structural equation modeling
4 citations