Longitudinal Studies of Aging Article List

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Paggi, M. E., Jopp, D., & Hertzog, C. (2016). The importance of leisure activities in the relationship between physical health and well-being in a life span sample. Gerontology, 62, 450-458.

ABSTRACT: Background: Previous studies have examined the relationships between physical health and leisure activities and between leisure activities and well-being, but, to our knowledge, none has examined these relationships simultaneously. Objective: This study investigated the relationships between leisure activities, health and well-being considering the role of age, and whether leisure activities mediate the relationship between physical health and well-being. Methods: Utilizing a cross-sectional database of 259 adults (ages 18-81 years) who completed several questionnaires, linear regression models and mediation models were tested. Results: Regression analyses indicated that physical health was related to leisure activities and leisure activities were related to well-being. When physical health was measured by subjective ratings, age had a stronger relationship with leisure activities. However, when physical health was indicated by health restrictions, physical health had a stronger relationship with leisure activities than did age. Leisure activities were a partial mediator of the relationship between physical health and well-being. Conclusion: The results demonstrated that the reduction in leisure activities with age has more to do with physical health limitations than with older age itself. In addition, regardless of age, the benefits of physical health for well-being are due in part to the level of leisure activity participation. These results highlight the importance of leisure activities for successful aging throughout the adult life span. Interventions designed to improve well-being through increasing leisure activity participation should take physical health into consideration, particularly for older adults.

External Link: doi:10.1159/000444415


Brandmaier, A.M., von Oertzen, T., Ghisletta, P., Hertzog, C., & Lindenberger, U.  (2015). LIFESPAN: A tool for the computer-aided design of longitudinal studies.  Frontiers in Psychological Science.

ABSTRACT: Researchers planning a longitudinal study typically search, more or less informally, a multivariate space of possible study designs that include dimensions such as the hypothesized true variance in change, indicator reliability, the number and spacing of measurement occasions, total study time, and sample size. The main search goal is to select a research design that best addresses the guiding questions and hypotheses of the planned study while heeding applicable external conditions and constraints, including time, money, feasibility, and ethical considerations. Because longitudinal study selection ultimately requires optimization under constraints, it is amenable to the general operating principles of optimization in computer-aided design. Based on power equivalence theory (MacCallum et al., 2010; von Oertzen, 2010), we propose a computational framework to promote more systematic searches within the study design space. Starting with an initial design, the proposed framework generates a set of alternative models with equal statistical power to detect hypothesized effects, and delineates trade-off relations among relevant parameters, such as total study time and the number of measurement occasions. We present LIFESPAN (Longitudinal Interactive Front End Study Planner), which implements this framework. LIFESPAN boosts the efficiency, breadth, and precision of the search for optimal longitudinal designs. Its initial version, which is freely available at http://www.brandmaier.de/lifespan, is geared toward the power to detect variance in change as specified in a linear latent growth curve model.

External Link: doi:10.1080/0361073X.2014.897150


Hülür, G., Hertzog, C., Pearman, A. M., & Gerstorf, D. (2015). Correlates and Moderators of Change in Subjective Memory and Memory Performance: Findings from the Health and Retirement Study. Gerontology, 61, 232-240.

ABSTRACT: Aging researchers have long been interested in understanding individuals’ subjective perceptions of their own memory functioning. Previous research has shown that subjective memory ratings are partly based on memory performance but also reflect the influence of other factors, such as depressive symptoms. The aim of the present study was to examine (1) longitudinal associations between trajectories of subjective memory and memory performance, (2) variables that predict levels of and changes in subjective memory and memory performance, and (3) variables that moderate associations between these constructs. We applied a latent growth curve model to four occasions of data from 15,824 participants of the Health and Retirement Study (HRS; mean age at baseline = 64.27 years, SD = 9.90; 58% women). Results revealed that latent changes in subjective memory were correlated with latent changes in memory performance (φ = 0.49), indicating that participants who reported steeper declines of subjective memory indeed showed steeper declines of memory performance over time. Three major patterns of associations emerged with respect to predictors of subjective memory and subjective memory change. First, the level of memory performance showed stronger associations with age, gender, and education, whereas subjective memory was more strongly associated with subjective age and personality traits. For example, women performed better than men on the episodic memory test, but there were no gender differences in subjective memory. Also, older age was associated with steeper declines of memory performance but with less decline of subjective memory. Second, personality traits that predicted subjective memory intercepts did not predict subjective memory slopes. Third, the strength of associations between levels and slopes of subjective memory and memory performance varied as a function of gender, education, depressive symptoms, and personality traits. Conscientiousness moderated the relationship of the level of subjective memory to the level of memory performance, consistent with the hypothesis that persons high in conscientiousness more accurately monitor memory successes and failures. The results reinforce the importance of depressive symptoms as a predictor of subjective memory but also indicate that a broader perspective on the reasons why memory complaints have modest correlations with memory itself is needed.

External Link: doi: 10.1159/000369010

Hülür, G., Hertzog, C., Pearman, A., Ram, N., & Gerstorf, D. (2014). Longitudinal associations of subjective memory with memory performance and depressive symptoms: Between-person and within-person perspectives.  Psychology and Aging, 29, 814-817.

ABSTRACT: Clinical diagnostic criteria for memory loss in adults typically assume that subjective memory ratings accurately reflect compromised memory functioning. Research has documented small positive between-person associations between subjective memory and memory performance in older adults. Less is known, however, about whether within-person fluctuations in subjective memory covary with within-person variance in memory performance and depressive symptoms. The present study applied multilevel models of change to 9 waves of data from 27,395 participants of the Health and Retirement Study (HRS; mean age at baseline = 63.78; SD = 10.30; 58% women) to examine whether subjective memory is associated with both between-person differences and within-person variability in memory performance and depressive symptoms and explored the moderating role of known correlates (age, gender, education, and functional limitations). Results revealed that across persons, level of subjective memory indeed covaried with level of memory performance and depressive symptoms, with small-to-moderate between-person standardized effect sizes (0.19 for memory performance and -0.21 for depressive symptoms). Within individuals, occasions when participants scored higher than usual on a test of episodic memory or reported fewer-than-average depressive symptoms generated above-average subjective memory. At the within-person level, subjective memory ratings became more sensitive to within-person alterations in memory performance over time and those suffering from functional limitations were more sensitive to withinperson alterations in memory performance and depressive symptoms. We take our results to suggest that within-person changes in subjective memory in part reflect monitoring flux in one’s own memory functioning, but are also influenced by flux in depressive symptoms.

External Link: doi: 10.1037/a0037619


Pearman, A. M., Hertzog, C., & Gerstorf, D. (2014).  Little evidence for links between memory complaints and memory performance in very old age: Longitudinal analyses from the Berlin Aging Study.  Psychology and Aging, 29, 828-842.

ABSTRACT: Cross-sectional and longitudinal relationships between memory complaint and memory performance were examined in a sample of old-old participants from the Berlin Aging Study (BASE; N = 504, ages 70 to 100, age M = 84.7 at study onset). Participants were measured 4 times over the course of 6 years. Similar to many previous studies, initial cross-sectional memory complaints were predicted by depression and neuroticism, but not memory performance. Subjective age also predicted memory complaint independent of other variables. Latent growth curve models based on age and time in the study revealed that memory complaints did not change in level with age or time, and manifested no reliable random effects (individual differences in change). These models also detected no significant relationship between changes in memory and either initial memory complaint or changes in memory complaint over age or over time. None of the covariates that predicted initial memory complaints were related to changes in memory complaints over time. An autoregressive latent variable model for memory complaints, consistent with a conceptualization of complaints as judgments constructed from beliefs and other influences in the moment, did detect a concurrent effect of memory on memory complaints at the third occasion, controlling on initial complaints. These results suggest that for the oldest-old, changes in memory complaints may not primarily reflect monitoring of actual age-related memory changes, but rather are affected by other variables, including age-based memory stereotypes, neuroticism, depression, and concerns about aging.

External Link: doi: 10.1037/a0037141

Lindenberger, U., Ghisletta, P., von Oertzen, T., & Hertzog, C. (2011). Cross-sectional age-related variance extraction: What’s change got to do with it? Psychology and Aging, 26, 34-47.

ABSTRACT: In cross-sectional age variance extraction (CAVE), age, the indicator of a hypothesized developmental mechanism, and a developmental outcome are specified as independent, mediator, and target variables, respectively, to test hypotheses about behavioral development. We show that: (a) longitudinal change in a mediator variable accounting for substantial cross-sectional age-related variance in the target variable need not correlate with the target variable’s longitudinal change; and, conversely, (b) longitudinal change in a mediator not sharing cross-sectional age-related variance with the target variable may nevertheless correlate highly with that variable’s longitudinal change. We discourage use of CAVE for testing multivariate hypotheses about behavioral development.

External Link: doi: 10.1037/a0020525

von Oertzen, T., Hertzog, C., Lindenberger, U., & Ghisletta, P. (2010). The effect of multiple indicators on the power to detect interindividual differences in change. British Journal of Mathematical and Statistical Psychology. 63, 627-646.

ABSTRACT: Hertzog, Lindenberger, Ghisletta, and von Oertzen (2008) evaluated the statistical power of linear Latent Growth Curve Models (LGCMs) to detect individual differences in change, i.e. variances of latent slopes, as a function of sample size, number of longitudinal measurement occasions, and Growth Curve Reliability (GCR). We extend this work by investigating the effect of the number of indicators per measurement occasion on power. We analytically demonstrate that the positive effect of multiple indicators on statistical power is inversely related to the relative magnitude of occasion-specific latent residual variance and is independent from the specific model that constitutes the observed variables, in particular from other parameters in the LGCM. When designing a study, researchers have to consider tradeoffs of costs and benefits of different design features. We demonstrate how knowledge about power equivalent transformations between indicator measurement designs allow researchers to identify the most cost-efficient research design for detecting parameters of interest. Finally, we integrate different formal results to show how number of measurement occasions and number of indicators per occasion trade off power equivalently in LGCMs.

External Link: doi: 10.1348/000711010X486633


Hertzog, C. (2010). Regarding methods for studying behavioral development: The contributions and influence of K. Warner Schaie. Research in Human Development, 7, 1-8.

ABSTRACT: This introduction to a special issue of Research in Human Development discusses K. Warner Schaie’s methodological contributions to our understanding of adult development.

External Link: doi :10.1080/15427600903578110


Hertzog, C., von Oertzen, T., Ghisletta, P., & Lindenberger, U.  (2008). Evaluating the Power of latent growth curve models to detect individual differences in change. Structural Equation Modeling, 15, 541-563.

ABSTRACT: We evaluated the statistical power of single-indicator latent growth curve models (LGCMs) to detect individual differences in change (variances of latent slopes) as a function of sample size, number of longitudinal measurement occasions, and growth curve reliability (GCR). We recommend the 2 degree-of-freedom generalized test assessing loss of fit when both slope related random effects, the slope variance and intercept-slope covariance, are fixed to zero. Statistical power to detect individual differences in change is low to moderate unless the residual error variance is low, sample size is large, and there are more than four measurement occasions. The generalized test has greater power than a specific test isolating the hypothesis of zero slope variance, except when the true slope variance is close to zero, and has uniformly superior power to a Wald test based on the estimated slope variance.

External Link: PsychNET


Allemand, M., Zimprich, D., & Hertzog, C. (2007). Cross-sectional age differences and longitudinal age changes of personality in middle adulthood and old age. Journal of Personality, 75(2),323-358.

ABSTRACT: The present study examines different aspects of personality continuity (or change) in middle adulthood and old age both crosssectionally and longitudinally. The sample comprised 445 middle-aged (42-46 years) and 420 older (60-64 years) participants, reassessed after a 4-year interval. Personality was measured using the NEO-FFI personality inventory. After having established strict factorial invariance, factor covariances were found to be equal for both age groups and at both testing occasions, indicating perfect structural continuity of personality. A number of age differences in personality emerged at both measurement occasions. Longitudinally, in both age groups, an average decline in Neuroticism was observed. Longitudinal stability coefficients were around .80 in middle-aged and old participants, implying high, but not perfect, differential continuity. With respect to continuity of divergence, statistically significant cross-sectional age differences were found for the variance of Openness at both measurement occasions. Eventually, concerning specific versus general continuity, a variety of medium effect-sized correlated changes in the Big Five personality domains across the 4-year period was established, implying that personality changes share a certain amount of commonality.

External Link: PMID:17359241


Hertzog, C., Lindenberger, U., Ghisletta, P., & Oertzen, T. v. (2006). On the Power of Multivariate Latent Growth Curve Models to Detect Correlated Change. Psychological Methods, 11(3), 244-252.

ABSTRACT: We evaluated the statistical power of single-indicator latent growth curve models (LGCMs) to detect correlated change between two variables (covariance of slopes) as a function of sample size, number of longitudinal measurement occasions, and reliability (measurement error variance). Power approximations following the method of Satorra and Saris (1985) were used to evaluate the power to detect slope covariances. Even with large samples (N=500) and several longitudinal occasions (4 or 5), statistical power to detect covariance of slopes was moderate to low unless growth curve reliability at study onset was above .90. Studies using LGCMs may fail to detect slope correlations because of low power rather than a lack of relationship of change between variables. The present findings allow researchers to make more informed design decisions when planning a longitudinal study and aid in interpreting LGCM results regarding correlated interindividual differences in rates of development.

External Link: PMID:16953703


Small, B. J., Hertzog, C., Hultsch, D. F., & Dixon, R. A.  (2003). Stability and change in adult personality over 6 years: Findings from the Victoria Longitudinal Study. Journal of Gerontology: Psychological Sciences, 58B, 166-176.

ABSTRACT: Data from the Victoria Longitudinal Study were used to examine the 6-year longitudinal stability of personality in older adults. Personality was measured with the NEO Personality Inventory. The longitudinal sample consisted of 223 adults initially ranging from 55 to 85 years of age. Longitudinal confirmatory factor analyses were used to examine the stability of individual differences in change over time, and the stability of the longitudinal factor structure. The results indicated both substantial stability at the level of individual differences in change, as well as significant individual differences in change that were related to age and gender. Finally, the factor structure of personality was invariant over time but did not approximate simple structure for the five dimensions of personality. Our study of 6-year personality development provided both (a) a confirmation of early significant stability findings and (b) unique evidence for significant individual differences in late adulthood.

External Link: PMID:12730309


Hertzog, C., Dixon, R. A., Hultsch, D. F., & MacDonald, S. W. S.  (2003).  Latent change models of adult cognition: Are changes in processing speed and working memory associated with changes in episodic memory? Psychology and Aging, 18,755-769.

ABSTRACT: The authors used 6-year longitudinal data from the Victoria Longitudinal Study (VLS) to investigate individual differences in amount of episodic memory change. Latent change models revealed reliable individual differences in cognitive change. Changes in episodic memory were significantly correlated with changes in other cognitive variables, including speed and working memory. A structural equation model for the latent change scores showed that changes in speed and working memory predicted changes in episodic memory, as expected by processing resource theory. However, these effects were best modeled as being mediated by changes in induction and fact retrieval. Dissociations were detected between cross-sectional ability correlations and longitudinal changes. Shuffling the tasks used to define the Working Memory latent variable altered patterns of change correlations.

External Link: PMID:14692862


Hertzog, C., & Nesselroade, J. R.  (2003).  Assessing psychological change in adulthood: An overview of methodological issues. Psychology and Aging, 18, 639-657.


ABSTRACT: This article reviews the current status of methods available for the analysis of psychological change in adulthood and aging. Enormous progress has been made in designing statistical models that can capture key aspects of intraindividual change, as reflected in techniques such as latent growth curve models and multilevel (random-effects) models. However, the rapid evolution of statistical innovations may have obscured the critical importance of addressing rival explanations for statistical outcomes, such as cohort differences or practice effects that could influence estimates of age-related change. Choice of modeling technique and implementation of a specific modeling approach should be grounded in and reflect both the theoretical nature of the developmental phenomenon and the features of the sampling design that selected persons, variables, and contexts for empirical observation.

External Link: PMID:14692854


Hultsch, D. F., Hertzog, C., Small, B., & Dixon, R. A.  (1999). Use it or lose it: Engaged lifestyle as a buffer of cognitive decline in aging? Psychology and Aging, 14, 245-263.


ABSTRACT: Data from the Victoria Longitudinal Study were used to examine the hypothesis that maintaining intellectual engagement through participation in everyday activities buffers individuals against cognitive decline in later life. The sample consisted of 250 middle-aged and older adults tested 3 times over 6 years. Structural equation modeling techniques were used to examine the relationships among changes in lifestyles variables and an array of cognitive variables. There was a relationship between changes in intellectually related activities and changes in cognitive functioning. These results are consistent with the hypothesis that intellectually engaging activities serve to buffer individuals against decline. However, an alternative model suggested the findings were also consistent with the hypothesis that high-ability individuals lead intellectually active lives until cognitive decline in old age limits their activities.

External Link: PMID:10403712


Hertzog, C., Hultsch, D. F., & Dixon, R. A.  (1999).  On the problem of detecting effects of lifestyle on cognitive change in adulthood: Reply to Pushkar et al. (1999). Psychology and Aging, 14, 528-534.


ABSTRACT: The authors respond to issues raised about data from the Victoria Longitudinal Study and further explain concerns regarding evidence for the engagement hypothesis. Discussion focuses on the use of social stratification variables such as occupational prestige and educational attainment as measures of an engaged lifestyle. It is argued that (a) tests of the hypothesis should focus on the relationship of behaviors and activities thought to be proximal beneficial influences on adult cognitive development; (b) persuasive evidence for engagement effects from existing data require demonstration of effects of intellectual activities that are statistically independent of associations of social status with intellectual and cognitive development; and (c) currently available longitudinal data do not provide definitive evidence regarding the benefits of an engaged lifestyle on cognitive change.

External Link: PsychINFO


Hertzog, C.  (1990).  On the utility of structural equation models for developmental research. In P. B. Baltes, D. L. Featherman, & R. M. Lerner (Eds.), Life-span development and behavior, 10,257-290. Hillsdale, NJ: Lawrence Erlbaum Associates.


ABSTRACT: Structural equation models (SEM) have become an increasingly popular technique for analysis of developmental research questions. However, a number of unfortunate misconceptions can be found in the literature regarding the nature, potential, and pitfalls of SEM. It is fallacious to assume that use of SEM techniques guarantees sound causal inference from correlational data: it is equally fallacious to argue that use of SEM for purposes other than testing causal models is an invalid misapplication of the method. In developmental research, important descriptive research questions can be shown to be linked to SEM models in two important ways: Alternative SEM models may be used to provide direct statistical tests of important descriptive developmental hypotheses, and SEM model parameters can be interpreted with respect to fundamental issues in developmental analysis (e.g., estimating the degree to which differential developmental patterns alter distributions of individual differences). This paper develops the logic and procedures for implementing longitudinal SEM techniques to address descriptive developmental questions, with a brief illustration of the application of SEM to longitudinal factor analysis.

External Link:


Hertzog, C., & Schaie, K. W.  (1988).  Stability and change in adult intelligence: 2. Simultaneous analysis of longitudinal means and covariance structures. Psychology and Aging, 3, 122-130.

ABSTRACT: We analyzed data on psychometric intelligence from the Seattle Longitudinal Study, simultaneously estimating longitudinal factors, their covariance structure, and their mean levels. Data on five Thurstone Primary Mental Abilities subtests were available for 412 adults, ages 22-70 at first test, who were tested three times at 7-year intervals. A previous longitudinal factor analysis had shown high stability of individual differences (covariance stability) in general intelligence for three adult age groups. We extended that model to estimate factor means. All three age groups showed high levels of covariance stability, but differed sharply in their mean profiles. The young group showed increasing levels of general intelligence, the middle-aged group had stable levels of intelligence, and the old group showed salient, approximately linear, decline. The patterns of stability in middle-age, followed by mean decline and high covariance stability in old age, suggest a normative developmental transition from a stability pattern to a decline pattern of general intelligence, with the inflection point occurring somewhere around age 60.

External Link: PMID:3268250


Hertzog, C., & Nesselroade, J. R.  (1987).  Beyond autoregressive models: Some implications of the trait-state distinction for the structural modeling of developmental change. Child Development, 58, 93-109.


ABSTRACT: The use of structural modeling techniques to fit change concepts, including developmental ones, to repeated-measurements data has been rather firmly but uncritically wedded to autoregressive model specifications. The uncritical application of an autoregressive specification to repeated measures does not take into account subtleties of conceptions of stability and change (e.g., the trait-state distinction) that are now recognized in the behavioral research literature. We review the basic distinction between trait and state and examine the implications of the different possibilities for modeling developmental phenomena. The arguments are illustrated with empirical examples.

External Link: PMID:3816352


Hertzog, C.  (1987).  Applications of structural equation models in gerontological research. In K.W. Schaie (Ed.), Annual review of gerontology and geriatrics, 7, 265-293. New York: Springer.

ABSTRACT: The past several years have been marked by an accelerating rate of increase in sophisticated new methods for conducting valid and informative empirical research on nonexperimental data (e.g., Blalock, 1985a, b: Nesselroade & Baltes, 1979). Some of the more important advances have been in the domain of structural equation models (SEM). Traditionally, SEM usually refers to complex regression models (e.g., path analysis) that analyze causal relations among unobserved (latent) variables. An important component of SEM, therefore, is that part of the model maps the latent variables onto variables we actually measure empirically (the observed or manifest variables). This part of SEM is usually termed the measurement model. The SEM measurement model is, essentially, a confirmatory factor analysis in which the observed variables are specified to be a linear combination of latent variables (factors). The part of the SEM specifying regression relationships among latent variables is the structural regression model. In this chapter I describe SEM applications, often consisting only of confirmatory factor analyses without a structural regression model, that address research questions of critical importance to gerontologists. Most of these applications are in the domain of psychometric intelligence and cognition, but they illustrate SEM techniques that can be used in other domains as well.

External Link: PMID:3120752


Hertzog, C., & Schaie, K. W.  (1986).  Stability and change in adult intelligence: 1. Analysis of longitudinal covariance structures. Psychology and Aging, 1, 159-171.


ABSTRACT: We address two questions of central interest in adult intellectual development: the equivalence of psychometric tests’ measurement properties at different ages, and the stability of individual differences in intelligence over time. We performed a series of longitudinal factor analyses using the LISREL program to model longitudinal data from Schaie’s Seattle Longitudinal Study. The results indicate complete invariance in the loadings of five subtests of Thurstone’s Primary Mental Abilities battery on a general intelligence factor. Individual differences in general intelligence were highly stable over 14-year epochs, with standardized factor correlations averaging about .9 between adjacent 7-year testing intervals. These results indicate that most individuals in this relatively select longitudinal sample maintained their relative ordering in intelligence.

External Link: PMID:3267393