Publications & Presentations by other primary authors

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2010s

Blankson, A. N., & McArdle, J. J. (2014) A Brief Report on the Factor Structure of the Cognitive Measures in the HRS/AHEAD Studies. Journal of Aging Research (5).

Zhang Z., McArdle, J. J., Hamagami, A., & Grimm, K. (2014) Structural Equation Modeling Using the Reticular Action Model (RAM) Notation.

Brandmaier, A. M., von Oertzen, T., McArdle, J. J., & Lindenberger, U. (2013). Structural equation model trees. Psychological Methods, 18 (1), 71-86.

Coman, E.N., Picho, K., McArdle, J.J., Villagra, V., Dierker, L., & Iordache, E. (2013). The paired t-test as a simple latent change score model. Frontiers In Psychology, 4, 738.

Prescott, C. A., Achorn, D. L., Kaiser, A., Mitchell, L., McArdle J. J., & Lapham, S. J. (2013). The Project TALENT Twin and Sibling Study. Twin Research and Human Genetics, 16 (1), 437-448.

Prindle, J. J. & McArdle, J. J. (2013). How representative is the ACTIVE sample? A statistical Comparison of the ACTIVE sample and the HRS sample. Journal of Aging and Health, 25 (8 Supp), 85S-102S.

Grimm, K. J., An, Y., McArdle, J. J., Zonderman, A. B., & Resnick, S. M. (2012). Recent Changes Leading to Subsequent Changes: Extensions of Multivariate Latent Difference Score Models. Structural Equation Modeling, 19(2), 268-292.

Hishinuma, E. S., Chang, J. Y., McArdle, J. J., & Hamagami, F. (2012). Potential causal relationship between depressive symptoms and academic achievement in the Hawaiian high schools health survey using contemporary longitudinal latent variable change models. Developmental Psychology, 48(5), 1327-1342.

Lei, X., Hu, Y., McArdle, J. J., Smith, J. P., & Zhao, Y. (2012). Gender Differences in Cognition among Older Adults in China. Journal of Human Resources, 47(4), 951-971.

Ferrer, E. & McArdle, J. J. (2010). Longitudinal modeling of developmental changes in psychological research. Current Directions in Psychological Science, 19(3), 149-154.

Krause, J. S., Reed, K. S., & McArdle, J. J. (2010). A Structural Analysis of Health Outcomes After Spinal Cord Injury. Journal of Spinal Cord Medicine, 33(1), 22-32.

Krause, J. S., Reed, K. S., & McArdle, J. J. (2010). Factor structure and predictive validity of somatic and nonsomatic symptoms from the patient health questionnaire-9: a longitudinal study after spinal cord injury. Archives of Physical Medicine and Rehabilitation, 91 (8), 1218-1224.

Krause, J. S., Reed, K. S., & McArdle, J. J. (2010). Prediction of somatic and non-somatic depressive symptoms between inpatient rehabilitation and follow-up. Spinal Cord, 48(3), 239-244.


2000s

Brommelhoff, J. A., Gatz, M., Johansson, B., McArdle, J. J., Fratiglioni, L., & Pedersen, N. L. (2009). Depression as a risk factor or prodromal feature for dementia? Findings in a population-based sample of swedish twins Psychology and Aging, 24(2), 373-384.

Finkel, D., Reynolds, C. A., McArdle, J. J., Hamagami, F., & Pedersen, N. L. (2009). Genetic variance in processing speed drives variation in aging of spatial and memory abilities. Developmental Psychology, 45(3), 820-834.

Gerstorf, D., Hoppmann, C. A., Kadlec, K. M., & McArdle, J. J. (2009). Memory and depressive symptoms are dynamically linked among married couples: Longitudinal evidence from the AHEAD study. Developmental Psychology, 45 (6), 1595-1610.

King, D. W., King, L. A., McArdle, J. J., Shalev, A. Y., & Doron-LaMarca, S. (2009). Sequential temporal dependencies in associations between symptoms of depression and posttraumatic stress disorder: An application of bivariate latent difference score structural equation modeling. Multivariate Behavioral Research, 44 (4), 437-464.

Krause, J. S., McArdle, J. J., Pickelsimer, E., & Reed, K. S. (2009). A latent variable structural path model of health behaviors after spinal cord injury. Journal of Spinal Cord Medicine, 32(2), 162-174.

Rogers, M. A. M., Plassman, B. L., Kabeto, M., Fisher, G., McArdle, J. J., Llewellyn, D. J., Potter, G. G., & Langa, K. M. (2009). Parental education and late-life dementia in the United States Journal of Geriatric Psychiatry and Neurology, 22(1), 71-80.

Small, B., McArdle, J. J., Langa, K., Lipton, R., Morris, J., Smith, G., Storandt, M. & Wilson, R.S. (2009). Changes in cognitive performance in preclinical Alzheimer's disease: A collaborative analysis.. Gerontologist, 49, 195.

Zhou, Y., & McArdle, J. J. (2009). A biometric latent curve analysis of visual memory development using data from the Colorado Adaptation Project. Multivariate Behavioral Research, 44(6), 857-858.

Jarvik, L., LaRue, A., Blacker, D., Gatz, M., Kawas, C., McArdle, J.J., et al. (2008). Children of persons with Alzheimer Disease: What does the future hold? Alzheimer Disease and Associated Disorders, 22 (1), 6-20.

Plassman, B. L., Langa, K. M., Fisher, G. G., Heeringa, S. G., Weir, D. R., Ofstedal, M. B., et al. (2008). Prevalence of cognitive impairment without dementia in the United States. Annals of Internal Medicine, 148(6), 427-434.

Ram, N., Gerstorf, D., Suzman, R., Austad, S., Gatz, M, Wilson, R. & McArdle, J. (2008). Aging and the lifespan: Revisiting the role of "age" from biological, functional, psychological, and social perspectives. Gerontologist, 48, 384.

Wang, L., & McArdle, J. J. (2008). A simulation study comparison of bayesian estimation with conventional methods for estimating unknown change points. Structural Equation Modeling, 15, 52-74.

Wang, L., Zhang, Z., McArdle, J. J., & Salthouse, T. A. (2008). Investigating ceiling effects in longitudinal data analysis. Multivariate Behavioral Research, 43(3), 476-496.

Zhang, Z., McArdle, J. J., Wang, L. & Hamagami, F. (2008). A SAS interface for Bayesian Analysis with WinBUGS. Structural Equation Modeling: A Multidisciplinary Journal, 15(4), 705-728.

Albert, M., Blacker, D., Moss, M. B., Tanzi, R., & McArdle, J. J. (2007). Longitudinal change in cognitive performance among individuals with mild cognitive impairment. Neuropsychology, 21(2), 158-169.

Blacker, D., Lee, H., Muzikansky, A., Martin, E .C., Tanzi, R., McArdle, J. J., Moss, M. & Albert, M. (2007). Neuropsychological measures in normal individuals that predict subsequent cognitive decline. Archives of Neurology, 64(6) 862-871.

Finkel, D., McArdle, J. J., Reynolds, C. A., & Pedersen, N. L. (2007). Age changes in processing speed as a leading indicator of cognitive aging. Psychology and Aging, 22(3), 558-568.

Ferrer, E., McArdle, J. J., Shaywitz, B. A., Holahan, J. M., Marchione, K., & Shaywitz, S. E. (2007). Longitudinal models of developmental dynamics between reading and cognition from childhood to adolescence. Developmental Psychology, 43(6), 1460-1473.

Finkel, D., Reynolds, C. A., McArdle, J. J., & Pedersen, N.L. (2007). Cohort differences in trajectories of cognitive aging. The Journals of Gerontology, 62B(5), 286-294.

Grimm, K. J., & McArdle, J. J. (2007). A dynamic structural analysis of the impacts of context on shifts in lifespan cognitive development. In T.D. Little, J.A. Bovaird & N.A. Card (Eds.), Modeling contextual effects in longitudinal studies (pp. 363-386). Mahwah, NJ: Lawrence Erlbaum Associates.

Grimm, K. J., McArdle, J. J., & Hamagami, F. (2007). Nonlinear growth mixture models in research on cognitive aging. In K. van Montfort, H. Oud, & A. Satorra (Eds.), Longitudinal models in the behavioral and related sciences (pp. 267-294), Mahwah, NJ: Erlbaum.

Hamagami, F., & McArdle, J. J. (2007). Dynamic extensions of latent difference score models. In S.M. Boker & M.L. Wegner (Eds.), Data analytic techniques for dynamical systems (pp. 47-85). Mahwah, NJ: Lawrence Erlbaum Associates.

Hershey, D. A., Jacobs-Lawson, J. M., McArdle, J. J., & Hamagami, F. (2007). Psychological foundations of financial planning for retirement. Journal of Adult Development, 14(1-2), 26-36.

Horn, J.L. & McArdle, J.J. (2007). Understanding human intelligence since Spearman. In R. Cudeck & R. C. MacCallum (Eds.), Factor analysis at 100: Historical developments and future directions. (pp. 205-247). Mahwah, NJ: Erlbaum.

Sneed, J. R., Hamagami, F., McArdle, J. J., Cohen, P., & Chen, H. (2007). The dynamic interdependence of developmental domains across emerging adulthood. Journal of Youth and Adolescence, 36(3) 351-362.

Andrade, N. N., Hishinuma, E. N., McDermott, J. F., Johnson, R. C., Goebert, D .A., Makini, G. K. et al. (2006). The national center on indigenous hawaiian behavioral health study of prevalance of psychiatric disorders in native Hawaiian adolescents. Journal of the American Academy of Child and Adolescent Psychiatry, 45(1), 26-36.

Feng, D., Silverstein, M., Giarrusso, R., McArdle, J. J., & Bengtson, V. L. (2006). Attrition of older adults in longitudinal surveys: Detection and correction of sample selection bias using multigenerational data. Journal of Gerontology: Social Sciences, 61B(6), S323-S328.

Ghisletta, P., McArdle, J. J., & Lindenberger, U. (2006). Longitudinal cognition-survival relations in old and very old age: 13-year data from the Berlin Aging Study. European Psychologist, 11(3), 204-223.

King, D. W., King, L. A., McArdle, J. J., Grimm, K., Jones, R.T. & Ollendick, T.H. (2006). Characterizing time in longitudinal trauma research. Journal of Traumatic Stress, 19 (2) 205-215.

King, L. A., King, D. W., McArdle, J. J, Saxe, G. N., Doron-LaMarca, S. & Orazem, R. J. (2006). Latent difference score approach to longitudinal trauma research. Journal of Traumatic Stress, 19(6), 771-785.

Boker, S. M. & McArdle, J. J. (2005). Vector field plot. In P. Armitage & T. Colton (Eds.), Encyclopedia of biostatistics (2nd ed.). (pp. 5700-5704). Chichester, England: John Wiley & Sons, Ltd.

Bowles, R. P., Grimm, K. J., & McArdle, J. J. (2005). A structural factor analysis of vocabulary knowledge and relations to age. Journal of Gerontology: Psychological Sciences, 60B (5), P234-P241.

Ferrer, E., Salthouse, T. A., McArdle, J. J., Stewart, W. F. & Schwartz, B. S. (2005). Multivariate modeling of age and retest in longitudinal studies of cognitive abilities. Psychology and Aging, 20(3), 412-422.

Finkel, D., Reynolds, C. A., McArdle, J. J., & Pedersen, N. L. (2005). The longitudinal relationship between processing speed and cognitive ability: Genetic and environmental influences. Behavior Genetics, 35(5), 535-549.

Reynolds, C. A., Finkel, D., McArdle, J. J., Gatz, M., Berg, S. & Pedersen, N. L. (2005). Quantitative genetic analysis of latent growth curve models of cognitive abilities in adulthood. Developmental Psychology, 41(1), 3-16.

Ferrer, E., Hamagami, F. & McArdle, J. J. (2004). Modeling latent growth curves with incomplete data using different types of structural equation modeling and multilevel software. Structural Equation Modeling, 11(3), 452-483.

Ferrer, E. & McArdle, J. J. (2004). An experimental analysis of dynamic hypotheses about cognitive abilities and achievement from childhood to early adulthood. Developmental Psychology, 40(6), 935-952.

Smyth, F. L., & McArdle, J. J. (2004). Ethnic and gender difference in science graduation at selective colleges with implications for admission policy and college choice. Research in Higher Education, 45(4), 353-381.

Ferrer, E. & McArdle, J. J. (2003). Alternative structural models for multivariate longitudinal data analysis. Structural Equation Modeling, 10(4), 493-524.

Finkel, D., Reynolds, C. A., McArdle, J. J., Gatz, M., & Pedersen, N. L. (2003). Latent growth curve analyses of accelerating decline in cognitive abilities in late adulthood. Developmental Psychology, 39 (3), 535-550.

Boker, S. M., McArdle, J. J. & Neale, M. (2002). An algorithm for the hierarchical organization of path diagrams and calculation of components of expected covariance. Structural Equation Modeling, 9(2), 174-194.

Nesselroade, J. R., McArdle, J. J., Aggen, S. H., & Meyers, J. M. (2002). Dynamic factor analysis models for representing process in multivariate time-series. In D. M. Moskowitz & S. L. Hershberger (Eds.), Modeling individual variability with repeated measures data: Advances & techniques. (pp. 235-265). Mahwah, NJ: Erlbaum.

Ghisletta, P., & McArdle, J. J. (2001). Latent growth curve analyses of the development of height. Structural Equation Modeling, 8 (4), 531-555.

Hamagami, F., & McArdle, J.J. (2001). Advanced studies of individual differences linear dynamic models for longitudinal data analysis. In G. Marcoulides & R. Schumacker (Eds.), New developments and techniques in structural equation modeling. (pp. 203-246). Mahwah, NJ: Erlbaum.

Cohen, P., Chen, H., Hamagami, F., Gordon, K., & McArdle, J. J. (2000). Multilevel analyses for predicting sequence effects of financial and employment problems on the probability of arrest. Journal of Quantitative Criminology, 16(2), 223-235.

Hishinuma, E. S., Andrade, N. N., Johnson, R. C., McArdle, J. J., Miyamoto, R. H., Nahulu, L. B. et al. (2000). Psychometric properties of the Hawaiian Culture Scale - adolescent version. Psychological Assessment, 12(2), 140-157.

Neale, M. C., & McArdle, J. J. (2000). Structured latent growth curves for twin data. Twin Research, 3, 165-177.


1990s

Prescott, C. A., Johnson, R. C., & McArdle, J. J. (1999). Chorion type as a possible influence on the results and interpretation of twin study data. Twin Research, 2, 244-249.

Boker, S. M., & McArdle, J. J. (1998). A psychotelemetry experiment in fluid intelligence. In J. J. McArdle & R. W. Woodcock (Eds.), Human cognitive abilities in theory and practice. (pp. 215-229). Mahwah, NJ: Erlbaum.

Edman, J. L., Danko, G. P., Andrade, N., McArdle, J. J., Foster, J., & Glipa, J. (1998). Factor structure of the CES-D (Center for Epidemiologic Studies Depression Scale) among Filipino-American adolescents. Social Psychiatry and Psychiatric Epidemiology, 34, 211-215.

Prescott, C. A., McArdle, J. J., Hishinuma, E. S., Johnson, R. C., Miyamoto, R. H., Andrade, N. N. et al. (1998). Prediction of major depression and dysthymia from CES-D scores among ethnic minority adolescents. Journal of the American Academy of Child and Adolescent Psychiatry, 37(5) 495-503.

Nesselroade, J. R., & McArdle, J. J. (1997). On the mismatching of levels of abstraction in mathematical-statistical model fitting. In H. W. Reese & M. D. Franzen (Eds.), Biological and neuropsychological mechanisms: Lifespan developmental psychology. (pp. 23-49). Mahwah, NJ: Erlbaum.

Boker, S. M., & McArdle, J. J. (1995). Statistical vector-field analysis applied to mixed cross-sectional and longitudinal data. Experimental Aging Research, 21, 77-93.

Horn, J. L., & McArdle, J. J. (1992). A practical and theoretical guide to measurement invariance in aging research. Experimental Aging Research, 18(3) 117-144.

Aber, M. S., & McArdle, J. J. (1991). Latent growth curve approaches to modeling the development of competence. In M. Chandler & M. Chapman (Eds.), Criteria for competence: Controversies in conceptualization and assessment of children's abilities. (pp. 231-257). Mahwah, NJ: Erlbaum.

Parry, C. D. H., & McArdle, J. J. (1991). An applied comparison of methods for least-squares factor analysis of dichotomous variables. Applied Psychological Measurement, 15(1) 35-46.

Prescott, C. A., Johnson, R. C. & McArdle, J. J. (1991). Genetic contributions to television viewing. Psychological Science, 2(6) 430-431.

Neale, M. C., & McArdle, J. J. (1990). The analysis of assortative mating: A LISREL model. Behavior Genetics, 20(2) 287-296.

Prescott, C. A. & McArdle, J. J. (1990). Biometric analysis of categorical data on twins. Unpublished manuscript, pp. 1-33.


1980s

Nesselroade, J. R., & McArdle, J. J. (1986). Multivariable causal modeling in alcohol use research. Social Biology, 33(4) 272-296.

Short, R. Horn, J. L., & McArdle, J. J. (1984). Mathematical-statistical model building in analysis of development data. In R. N. Emde & R. J. Harmon (Ed.), Continuities and discontinuities in development. (pp. 371-401). New York: Plenum Press.

Horn, J. L., McArdle, J. J., & Mason, R. (1983). When is invariance not invariant: A practical scientist's look at the ethereal concept of factor invariance. The Southern Psychologist, 1(4) 179-188.

Horn, J. L., & McArdle, J.J. (1980). Perspectics on mathematical statistical model building (MASOB) in research on aging. In L. W. Poon (Ed.), Aging in the 1980s: Psychological issues. (pp. 530-541). Washington, DC: American Psychological Association.