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Articles

On Standardizing Within-Person Effects: Potential Problems of Global Standardization

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References

  • Aafjes-van Doorn, K., Lilliengren, P., Cooper, A., Macdonald, J., & Falkenström, F. (2017). Patients affective processes within initial experiential dynamic therapy sessions. Psychotherapy, 54(2), 175–183. doi:10.1037/pst0000072
  • Armeli, S., O’Hara, R. E., Ehrenberg, E., Sullivan, T. P., & Tennen, H. (2014). Episode-specific drinking-to-cope motivation, daily mood, and fatigue-related symptoms among college students. Journal of Studies on Alcohol and Drugs, 75(5), 766–774. doi:10.15288/jsad.2014.75.766
  • Baird, R. (2016). The effect of misspecifying random-effect time-varying predictors as fixed on estimates of other parameters (Doctoral dissertation). University of Notre Dame, Notre Dame, IN.
  • Baird, R., & Maxwell, S. E. (2016). Performance of time-varying predictors in multilevel models under an assumption of fixed or random effects. Psychological Methods, 21(2), 175–188. doi:10.1037/met0000070
  • Bergeman, C., & Deboeck, P. R. (2014). Trait stress resistance and dynamic stress dissipation on health and well-being: The reservoir model. Research in Human Development, 11(2), 108–125. doi:10.1080/15427609.2014.906736
  • Bolger, N., & Laurenceau, J.-P. (2013). Intensive longitudinal methods: An introduction to diary and experience sampling research. New York, NY: Guilford Press.
  • Bryk, A. S., & Raudenbush, S. W. (1987). Application of hierarchical linear models to assessing change. Psychological Bulletin, 101(1), 147–158. doi:10.1037//0033-2909.101.1.147
  • Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24(4), 385–396. Retrieved from http://www.jstor.org/stable/2136404
  • Curran, P. J., & Bauer, D. J. (2011). The disaggregation of within-person and between-person effects in longitudinal models of change. Annual Review of Psychology, 62(1), 583–619. doi:10.1146/annurev.psych.093008.100356
  • Dejonckheere, E., Bastian, B., Fried, E. I., Murphy, S. C., & Kuppens, P. (2017). Perceiving social pressure not to feel negative predicts depressive symptoms in daily life. Depression and Anxiety, 34(9), 836–844. doi:10.1002/da.22653
  • Dejonckheere, E., Mestdagh, M., Houben, M., Erbas, Y., Pe, M., Koval, P., … Kuppens, P. (2018). The bipolarity of affect and depressive symptoms. Journal of Personality and Social Psychology, 114(2), 323–341. http://dx.doi.org/10.1037/pspp0000186
  • Du, H., & Wang, L. (2018). Reliabilities of intraindividual variability indicators with autocorrelated longitudinal data: Implications for longitudinal study designs. Multivariate behavioral research, 53(4), 502–520. doi:10.1080/00273171.2018.1457939
  • Eid, M., & Diener, E. (1999). Intraindividual variability in affect: Reliability, validity, and personality correlates. Journal of Personality and Social Psychology, 76(4), 662–676. doi:10.1037/0022-3514.76.4.662
  • Enders, C. K., & Tofighi, D. (2007). Centering predictor variables in cross-sectional multilevel models: A new look at an old issue. Psychological Methods, 12(2), 121–138. doi:10.1037/1082-989X.12.2.121
  • Estabrook, R., Grimm, K. J., & Bowles, R. P. (2012). A Monte Carlo simulation study of the reliability of intraindividual variability. Psychology and Aging, 27, 560–576. doi:10.1037/a0026669
  • Ferrer, E., Gonzales, J. E., & Steele, J. (2013). Intra-and interindividual variability of daily affect in adult couples. GeroPsych: The Journal of Gerontopsychology and Geriatric Psychiatry, 26(3), 163–172. doi:10.1024/1662-9647/a000095
  • Fiske, D. W., & Rice, L. (1955). Intra–individual response variability. Psychological Bulletin, 52(3), 217–250. doi:10.1037/h0045276
  • Fitzmaurice, G. M., Laird, N. M., & Ware, J. H. (2011). Applied longitudinal analysis (2nd ed.). Hoboken, NJ: John Wiley & Sons.
  • Foshee, V. A., Benefield, T. S., Reyes, H. L. MNaughton., Ennett, S. T., Faris, R., Chang, L.-Y., … Suchindran, C. M. (2013). The peer context and the development of the perpetration of adolescent dating violence. Journal of Youth and Adolescence, 42(4), 471–486. doi:10.1007/s10964-013-9915-7
  • Freeman, L. K., & Gottfredson, N. C. (2017). Using ecological momentary assessment to assess the temporal relationship between sleep quality and cravings in individuals recovering from substance use disorders. Addictive Behaviors, 83, 95–101. https://doi.org/10.1016/j.addbeh.2017.11.001
  • Gerstorf, D., Siedlecki, K. L., Tucker-Drob, E. M., & Salthouse, T. A. (2009). Within-person variability in state anxiety across adulthood: Magnitude and associations with between-person correlates. International Journal of Behavioral Development, 33(1), 55– 64. doi:10.1177/0165025408098013
  • Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: Journal of the Econometric Society, 37(3), 424–438.
  • Hamaker, E. L. (2012). Why researchers should think” within-person”: A paradigmatic rationale. In M. Mehl & T. Conner (Eds.), Handbook of methods for studying daily life (pp. 43–61). New York, NY: Guilford Publications.
  • Hamaker, E. L., Dolan, C. V., & Molenaar, P. (2005). Statistical modeling of the individual: Rationale and application of multivariate time series analysis. Multivariate Behavioral Research, 40(2), 207–233. doi:10.1207/s15327906mbr4002-3
  • Hamaker, E. L., & Grasman, R. P. (2015). To center or not to center? Investigating inertia with a multilevel autoregressive model. Frontiers in Psychology, 5, Article 1492, 1–15. https://doi.org/10.3389/fpsyg.2014.01492
  • Hamaker, E. L., Kuiper, R. M., & Grasman, R. P. (2015). A critique of the cross-lagged panel model. Psychological Methods, 20(1), 102–116. doi:10.1037/a0038889
  • Hedeker, D., Mermelstein, R., Berbaum, M., & Campbell, R. (2009). Modeling mood variation associated with smoking: An application of a heterogeneous mixed-effects model for analysis of ecological momentary assessment (EMA) data. Addiction, 104(2), 297–307. doi:10.1111/j.1360-0443.2008.02435.x
  • Hedeker, D., Mermelstein, R. J., & Demirtas, H. (2008). An application of a mixed-effects location scale model for analysis of ecological momentary assessment (EMA) data. Biometrics, 64(2), 627–634. doi:10.1111/j.1541-0420.2007.00924.x
  • Hedeker, D., Mermelstein, R. J., & Demirtas, H. (2012). Modeling between-subject and within-subject variances in ecological momentary assessment data using mixed-effects location scale models. Statistics in Medicine, 31(27), 3328–3336. doi:10.1002/sim.5338
  • Hedges, L. V. (2007). Effect sizes in cluster-randomized designs. Journal of Educational and Behavioral Statistics, 32(4), 341–370. doi:10.3102/1076998606298043
  • Hox, J. J. (2010). Multilevel analysis: Techniques and applications (2nd ed.). New York, NY: Routledge.
  • Jongerling, J., Laurenceau, J.-P., & Hamaker, E. L. (2015). A multilevel AR (1) model: Allowing for inter-individual differences in trait-scores, inertia, and innovation variance. Multivariate Behavioral Research, 50(3), 334–349. doi:10.1080/00273171.2014.1003772
  • Ke, Z., & Wang, L. (2015). Detecting individual differences in change: Methods and comparisons. Structural Equation Modeling, 22(3), 382–400. doi:10.1080/10705511.2014.936096
  • Kelley, K., & Preacher, K. J. (2012). On effect size. Psychological Methods, 17(2), 137–152. doi:10.1037/a0028086
  • Kreft, I. G. G., de Leeuw, J., & Aiken, L. S. (1995). The effect of different forms of centering in hierarchical linear models. Multivariate Behavioral Research, 30(1), 1– 21. doi:10.1207/s15327906mbr3001-1
  • Liu, Y., & West, S. G. (2016). Weekly cycles in daily report data: An overlooked issue. Journal of Personality, 84(5), 560–579. doi:10.1111/jopy.12182
  • Lüdtke, O., Marsh, H. W., Robitzsch, A., Trautwein, U., Asparouhov, T., & Muthén, B. (2008). The multilevel latent covariate model: A new, more reliable approach to group-level effects in contextual studies. Psychological Methods, 13(3), 203. doi:10.1037/a0012869
  • Lydon-Staley, D. M., Xia, M., Mak, H. W., & Fosco, G. (2018). Adolescent emotion network dynamics in daily life and implications for depression. Journal of abnormal child psychology, 1–13. https://doi.org/10.1007/s10802-018-0474-y.
  • Maxwell, S. E., & Delaney, H. D. (2004). Designing experiments and analyzing data: A model comparison perspective (2nd ed.). New York, NY: Taylor & Francis Group.
  • Michela, J. L. (1990). Within-person correlational design and analysis. In C. Hendrick & M. S. Clark (Eds.), Review of personality and social psychology, Vol. 11, Research methods in personality and social psychology (pp. 279–311). Thousand Oaks, CA: Sage Publications.
  • Molenaar, P. C. M. (2004). A manifesto on psychology as idiographic science: Bringing the person back into scientific psychology – this time forever. Measurement: Interdisciplinary Research and Perspectives, 2(4), 201–218. doi:10.1207/s15366359mea0204_1
  • Molenaar, P. C. M., & Campbell, C. G. (2009). The new person-specific paradigm in Psychology. Current Directions in Psychological Science, 18(2), 112– 117. doi:10.1111/j.1467-8721.2009.01619.x
  • Muthén, L. K., & Muthén, B. O. (2002). How to use a Monte Carlo study to decide on sample size and determine power. Structural Equation Modeling, 9(4), 599–620. doi:10.1207/S15328007SEM0904-8
  • Nesselroade, J. R. (1991). The warp and woof of the developmental fabric. In R. Downs, L. Liben & D. Palermo (Eds.), Visions of development, the environment, and aesthetics: The legacy of Joachim F. Wohlwill (pp. 213–240). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Nesselroade, J. R., & Molenaar, P. (2010). Emphasizing intraindividual variability in the study of development over the life span. In R. M. Lerner, M. E. Lamb&, A. M. Freund (Eds.), The handbook of life-span development (pp. 30–54). Hoboken, NJ: John Wiley & Sons.
  • Nesselroade, J. R., & Salthouse, T. A. (2004). Methodological and theoretical implications of intraindividual variability in perceptual motor performance. Journals of Gerontology: Psychological Sciences, 59B, 49–55. doi:10.1093/geronb/59.2.P49
  • Ram, N., & Gerstorf, D. (2009). Time-structured and net intra-individual variability: Tools for examining the development of dynamic characteristics and processes. Psychology and Aging, 24(4), 778–791. doi:10.1037/a0017915
  • Ramseyer, F., Kupper, Z., Caspar, F., Znoj, H., & Tschacher, W. (2014). Time-series panel analysis (tspa): Multivariate modeling of temporal associations in psychotherapy process. Journal of Consulting and Clinical Psychology, 82(5), 828–838. doi:10.1037/a0037168
  • Raudenbush, S., & Bryk, A. (2002). Hierarchical linear models (2nd ed.). Thousand Oaks, CA: Sage Publications.
  • Schmiedek, F., Lövdén, M., & Lindenberger, U. (2009). On the relation of mean reaction time and intraindividual reaction time variability. Psychology and Aging, 24(4), 841– 857. doi:10.1037/a0017799
  • Schuurman, N. K., Ferrer, E., de Boer-Sonnenschein, M., & Hamaker, E. L. (2016). How to compare cross-lagged associations in a multilevel autoregressive model. Psychological Methods, 21(2), 206–221. doi:10.1037/met0000062
  • Snijders, T. A. B., & Bosker, R. J. (2012). Multilevel analysis: An introduction to basic and advanced multilevel modeling (2nd ed.). London, UK: Sage.
  • Wang, L., & Grimm, K. (2012). Investigating reliabilities of intra-individual variability indicators. Multivariate Behavior Research, 47, 1–31. doi:10.1080/00273171.2012.715842
  • Wang, L., Hamaker, E., & Bergeman, C. S. (2012). Investigating inter-individual differences in intra-individual variability. Psychological Methods, 17(4), 567–581. doi:10.1037/a0029317
  • Wang, L., & Maxwell, S. E. (2015). On disaggregating between-person and within-person effects with longitudinal data using multilevel models. Psychological Methods, 20(1), 63–83. doi:10.1037/met0000030
  • Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measure of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063–1070.
  • Watson, D., Wiese, D., Vaidya, J., & Tellegen, A. (1999). The two general activation systems of affect: Structural findings, evolutionary considerations, and psychobiological evidence. Journal of Personality and Social Psychology, 76(5), 820–838.
  • Zautra, A., Smith, B., Affleck, G., & Tennen, H. (2001). Examinations of chronic pain and affect relationships: Applications of a dynamic model of affect. Journal of Consulting and Clinical Psychology, 69(5), 786–795.
  • Zautra, P., Potter, A., & Reich, J. (1997). The independence of affects is context-dependent: An integrative model of the relationship between positive and negative affect. Annual Review of Gerontology and Geriatrics, 17, 75–103.
  • Zhang, Q., & Wang, L. (2014). Aggregating and testing intra-individual correlations: Methods and comparisons. Multivariate Behavioral Research, 49(2), 130–148. doi:10.1080/00273171.2013.870877
  • Zhang, Q., Wang, L., & Bergeman, C. S. (2018). Multilevel autoregressive mediation models: Specification, estimation, and applications. Psychological Methods, 23(2), 278–297. doi:10.1037/met0000161

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