UvA-DARE (Digital Academic Repository) Time Series .
UvA-DARE (Digital Academic Repository)Time series analysis and the individual as the unit of psychological researchHamaker, E.L.Publication date2004Link to publicationCitation for published version (APA):Hamaker, E. L. (2004). Time series analysis and the individual as the unit of psychologicalresearch.General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s)and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an opencontent license (like Creative Commons).Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, pleaselet the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the materialinaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letterto: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. Youwill be contacted as soon as possible.UvA-DARE is a service provided by the library of the University of Amsterdam (https://dare.uva.nl)Download date:28 Apr 2021
References sAitkin,, M., & Longford, N. (1986). Statistical modelling issues in school effectivenessstudies. Journal of the Royal Statistical Society. Series A (General), 149, 1-43.Akaike,, H. (1973). Information theory and an extension of t h e maximum likelihoodprinciple. In B. N. Petrov & F . Caski (Eds.), Procedings of the second internationaltional symposium on information theory. Budapest: Akademiai Kaido.Ali,, M. M. (1977). Analyis of autoregressive-moving average models: Estimation andprediction. Biometrika, 64, 535-545.Allen,, B. P., &: Potkay, C. R. (1981). On the arbitrary distinction between states andtraits. Journal of Personality and Social Psychology, 1, 916-928.Allport,, G. W. (1946). Personality: A psychological interpretation.New York: HenryHoltt and Company.Anderson,, T. W. (1960). Some stochastic process models for intelligence test scores.Inn K. J. Arrow, S. Karlin, & P. Suppes (Eds.), Mathematicalmethods in thesocialsocial sciences, 1959 (pp. 205-220). Stanford, CA: Stanford University Press.Andersson,, G., Hagnebo, C., & Yardley, L. (1997). Stress and symptoms of Meniere'sdisease:: A time-series analyis. Journal of PsychosomaticResearch, 43, 595-603.Ansley,, C. F . (1979). An algorithm for the exact likelihood of a mixed autoregressivemovingg average process. Biometrika, 66, 59-65.Bakeman. R., & G o t t m a n , J. (1997). Observing interaction: An introduction to sequentialquential analysis. Cambridge: University Press.Baldwin,, A. L. (1946). T h e study of individual personality by means of the intraindividuall correlation. Journal of Personality, 14, 151-168.Baumeister,, R. E., & Tice, D. M. (1988). Metatraits. Journal of Personality, 571-598.Bern,, D. J., &; Allen, A. (1974). On predicting some of the people some of the time:T h ee search for cross-situational consistencies in behavior. PsychologicalReview,81,81, 506-520.Bentler,, P. M., k. Bonett, D. G. (1980). Significance tests and goodness of fit in theanalysiss of covariance structures. Psychological Bulletin, 88, 588-606.Block,, J. (1993). Personality as an affective-processingsystem: Toward an integrativetheory.theory. Mahwah, NJ: Lawrence Erlbaum Associates, Inc.Boker,, S. M., & Nesselroade, J. R. (2002). A method for modeling t h e intrinsic dynamicss of intraindividual variability: Recovering parameters of simulated oscillatorsinn multi-wave panel data. Multivariate Behavioral Research, 31, 127-160.Bollen,, K. A. (1989). Structural equations with latent variables. New York: J o h n Wiley&& Sons.
1244ReferencesBollen. K. A. k C u r r a n . P. J. (2004). Autoregressive latent trajectories (ALT) models:AA synthesis of two traditions. Sociological Methods and Research, 32. 336-383.Boring. E. (1929). A history of experimental psychology. New York: The Century Co.Borkenau. P. & Ostendorf, F. (1998). The Big Five as states: How useful is theFivee Factor model to descrihe intraindividual variations over time? Journal ofResearchResearch in Personality. 32. 202-221.Borsboom. D. Mellenbergh, G. J., k Van Heerden. J. (2003). The theoretical s t a t u soff latent variables. Psychological Review, 110. 203-219.Box,, G. E. P. & Jenkins. G. M. (1976). Time series analysis: Forecasting and control(Revisedd ed.). San Francisco: Holden-Day.Boxx Fisher, J. (1978). R. A. Fisher: The life of a scientist. New York: Wiley.Brillinger. D. (1975). Time series: Data analysis and theory. New York: Holt. Rinehartandd Winston.Browne. M. W. & Du Toit. S. H. C. (1991). Models for learning data. In L. M. Collinskk J. L. Horn (Eds.). Best methods for the analsyis of change: Recent advances.unasweredunaswered questions, future directions (p. 47-68). Washington. DC: AmericanPsychologicall Association.Browne. M. W. & Nesselroade. J. R. (in preparation). Representing psychologicalprocessess with dynamic factor models: Some promising uses and extensions ofA R M AA time series models. In McDonaldFestschrift.Buss. A. (1989). Personality as traits. American Psychologist. 44- 1378-1388.Buss. D. M. k Craik, K. H. (1983). The act frequency approach to personality.PsychologicalPsychological Review. 90, 105-126.Catt tell. R. B. (1966). P a t t e r n s of change: Measurement in relation to state-dimension.traitt change, lability, a n d process concepts. In R. B. Cattell (Ed.). Handbook ofmultivariatemultivariate experimental psychology (p. 355-402). Chicago: Rand McNally andCompany. .Cattell. R. B. (1967). T h e structuring of change by P-technique and incrementalR-technique. In C. W. Harris (Ed.). Problems in measuring change (p. 167-198).Madison. Wisconsin: T h e University of Wisconsin Press.Cattell. R. B. (1978). The scientific use of factor analysis in behavioral and lifesciences.sciences. New York: Plenum Press.Cattell. R. B. Cattell. A. K. S. k Rhymer. R. D. (1947). P-technique demonstratedinn determining psycho-physiological source traits in a normal individual. Psychometrika.chometrika. 12(4). 267-288.Cervone. D. (2004). T h e architecture of personality. Psychological Review, 111. 183204. .Chassan. J. (1959). On the development of clinical statistical systems for psychiatry.Biometrics.Biometrics.15. 396-404.Chatfield. C. (1989). The analysis of time series: An introduction (4th ed.). London:C h a p m a nn and Hall.Chi. E. M. k Reinsel. G. C. (1989). Models for longitudinal d a t a with random effectsandd AR (1) errors. Journal of the American Statistical Association. 84- 452-459.Cohn. J. F., k Tronick. E. Z. (1988). Mother-infant face-to-face interaction: Influenceiss bidirectional and unrelated t o periodic cycles in either partner's behavior.DevelopmentalDevelopmentalPsychology, 2\, 386-392.Cook. T. D. k Campbell. D. (1979). Quasi-experimentation:Design and analysisissuesissues for field settings. Chicago: Rand McNally College Publishing Company.
Referencess125Costa,, P. T., & McCrea, R. R. (1994). Set like plaster? Evidence for stability of adultpersonality. In T. F. Heatherton & J. L. Weinberger (Eds.), Canpersonalitychange?change? (pp. 21-40). Washington DC: American Psychological Association.Cowan,, R. (1972). Francis Ga;ton's statistical ideas: T h e influence of eugenics. Isis,63,63, 509-528.Cowles,, M. (1989). Statistics in psychology: An historical perspective. Hillsdale, NewJersey:: Lawrence Erlbaum Associates.Curran,, P. J., & Bollen, K. A. (2001). T h e best of b o t h worlds: Combining autoregressivee and latent curve models. In L. M. Collins & A. G. Sayer (Eds.), Newmethodsmethods for the analysis of change (pp. 105-136). Washington DC: AmericanPsychologicall Association.Czogalik,, D., & Russell, R. (1995). Interactional structures of therapist and clientparticipationn in adult psychotherapy: P technique and chronography. Journal ofConsultingConsulting and Clinical Psychology, 63, 28-36.Danziger,, K. (1990). Constructingthe subject: Historical origins of psychologicalresearch.research. Cambridge: Cambridge University Press.Desrosières,, A. (1998). The politics of large numbers. Cambridge: Harvard UniversityPress. .Diggle,, P. J. (1990). Time series: A biostatistical introduction.Oxford: OxfordUniversityy Press.Dolan,, C. V., k, Molenaar, P. C. M. (1991). A comparison of 4 methods of calculatings t a n d a r dd errors in the analysis of covariance structure using normal theory mlestimation. British Journal of Mathematical and Statistical Psychology, 44 3 5 9 368. .Dolan,, C. V., & Molenaar, P. C. M. (1993). NONLIS: a F O R T R A N 77 programforr multi-group covariance structure analysis subject to linear, non-linear, andsimplee b o u n d constraints. In F. J. Maarse & K. Kattenpoe l Oude Heerink (Eds.),ComputersComputers in psychology (Vol. 4, pp. 105-117). Swets a n d Zeitlinger.Duncan,, T. E., Duncan, S. C , Strycker, L. A., Li, F., & Alpert, A. (1999). An introductiontion to latent variable growth curve modeling: Concepts, issues and applications.Mahwah,, NJ: Lawrence Erlbaum Associates, Inc., Publishers.Durbin,, J., & Koopman, S. J. (2001). Time series analysis by state space methods.Neww York: Oxford University Press.Duu Toit, S. H. C , & Browne, M. W. (2001). T h e covariance structure of a vectorA R M AA time series. In R. Cudeck, S. Du Toit, & D. Sörbom (Eds.), Structuralequationequation modeling: Present and future. A festschrift in honor of Karl Jöreskog(pp. 279-314). Scientific Software International.Ellis,, J. L., & Van den Wollenberg, A. L. (1993). Local homogeneity in latent models:AA characterization of the homogeneous monotone IRT model.Psychometrika,58,58, 417-429.Engle,, R., & Watson, M. (1981). A one-factor multivariate time series model ofmetropolitann wage rates. Journal of the American Statistical Association,76,774-781. .Epstein,, S. (1979). T h e stability of behavior: 1. On predicting most of the peoplemostt of the time. Journal of Personality and Social Psychology, 37, 1097-1126.Epstein,, S. (1980). The stability of behavior: 2. Implications for psychological research.AmericanAmerican Psychologist, 35, 790-806.
1266ReferencesEpstein. S. (1994). Trait theory as personality theory: Can a part be as great as thewhole? Psychological Inquiry. 5. 120-122.Eysenck. H. J. (1983). Cicero and t h e state-trait theory of anxiety: Another case ofdelayedd recognition. American Psychologist, 38. 114-115.Ferrer. E., k Nesselroade. J. (2003). Modeling affective processes in dyadic relationsviaa dynamic factor analysis. Emotion. 3. 344-360.Fiske,, D. W. (1994). Two cheers for the Big Five! Psychological Inquiry. 5. 123-124.Fleeson,, W . (2001). Toward a structure- and process-integrated view of personality:: Traits as density distributions of states. Journal of Personality and SocialPsychology.Psychology. 80. 1011-1027.Forgays. D. Forgays. D. K. k Spielberger. C. (1997). Factor structure of the statetraitt anger expression inventory. Journal of Personality Assessment. 69. 497-507.Fowley,, D., k Horton, M. (1995). The student edition of MATLAB.New Jersey:Prentice-Hall. .Freeman. H. (1963). Introduction to statistical inference. Reading. Massachusetts:Addison-YVesleyy Publishing Company. Inc.Funder. D. C. (1994). Explaining traits. Psychological Inquiry. 5. 125-127.Galtung. J. (1967). Theory and methods of social research. Oslo, Norway: Universitetsforlaget. .Gardner. G., Harvey. A. C , k Phillips. G. D. A. (1980). An algorithm for exact maximumm likelihood estimation of autoregressive-moving average models by meansoff kalman. Applied Statistics. 29. 311 322.Garfein. A. J., k Smyer. M. A. (1991). P-technique factor analysis of t h e multipleaffectt adjective check list (MAACL). Journal of Psychopathology and BehavioralAssessment.Assessment.13. 155-171.Geweke. J. F . . k Singleton. K. J. (1981). Maximum likelihood "confirmatory" factoranalysiss of econometric time series. InternationalEconomic Review. 22. 37-54.Gill. P. E. Murray, W., Saunders, M. A., k Wright, M. H. (1986). User's guide forNPSOLNPSOL (version 5.0-2): Technical report sol 86-2. Stanford University, StanfordCA. 94305.: Department of Operations Research.Goldberg,, L. R. (1994). How not t o whip a straw dog. Psychological Inquiry. 5.128-130. .G o t t m a n . J. M. (1979). Marital interaction: Experimental invetsigations.New York:Academicc Press.G o t t m a n . J. M. & Ringland. J. T. (1981). The analysis of dominance and bidirectionalityy in social development. Child Development. 52. 393-412.Granger. C. W. J., k Morris, M. J. (1976). Time series modelling and interpretation.JournalJournal of the Royal Statistical Society, 139, 246-257.G r a s m a n ,, R. P. P. P. Huizenga, H. M., Waldorp, L. J., Boeker, K. B. E., k Molenaar,P. C. M. (2004). Frequency domain simultaneous source and source coherenceestimationn with a n application t o M E G . IEEE Transactions on Biomedical Engineering,gineering, 51, 45-55.Grayson,, D. (2004). Some m y t h s and legends in quantitative psyhology.UnderstandingStatistics,Statistics, 3, 101-134.Gregson,, R. A. M. (1983). Time series in psychology. Hillsdale. New Jersey: LawrenceErlbaumm Associates. Inc.Grice,, J. W. (2004). Bridging the idiographic-nomothetie divide in ratings of self andothers. Journal of Personality., 72(2), 203-241.
Referencess127G u t t m a n ,, L. A. (1954). A new approach to factor analysis: T h e radex. In P. F .Lazarsfeldd (Ed.), Mathematicalthinking in the social sciences (pp. 197-218).Columbiaa University Press.Hamaker,, E. L. (in press). Conditions for the equivalence of t h e autoregressive latenttrajectoryy model and a latent growth curve model with autoregressive disturbances. Sociological Methods and Reasearch.Hamaker,, E. L., Dolan, C. V., k Molenaar, P. C. M. (2002). On t h e n a t u r e of SEMestimatess of A R M A parameters. Structural Equation Modeling, 9, 347-368.Hamaker,, E. L., Dolan, C. V., k Molenaar, P. C M. (2003). ARMA-based SEM whenthee number of time points T exceeds t h e number of cases N: raw d a t a m a x i m u mlikelihood. Structural Equation Modeling, 10, 352-379.Hamaker,, E. L., Dolan, C. V., k Molenaar, P. C. M. (in press). Statistical modelingoff the individual: Rationale and application of multivariate time series analysis.MultivariateMultivariate BehavioralResearch.Hamaker,, E. L., k Molenaar, P. C. M. (2004). The integrated trait-statemodel.Unpublishedd manuscript, Department of Psychology, University of A m s t e r d a m .Hamilton,, J. D. (1994). Time series analysis.Princeton, New Jersey: PrincetonUniversityy Press.Hankins,, F. H. (1908). Adolphe Quetelet as statistician. New York: Columbia University. .Hanna,, G., & Lei, H. (1985). A longitudinal analysis using the LISREL-model withstructuredd means. Journal of Educational Statistics, 10(2), 161-169.H a n n a n . E., k Deistier, M. (1988). The statistical theory of linear systems. New York:Wiley. .H a n n a n ,, M. T. (1971). Aggregation and disaggregation in sociology. Lexington, Massachusetts:: D. C. Heath and Company.Harvey,, A. C. (1989). Forecasting, structural time series models and the Kalman filter.Cambridge:: University Press.Harvey,, A. C. (1993). Time series models (2nd ed.). New York: Harvester Wheatsheaf.Heathcote,, A., Brown, S., k Mewhort, D. J. K. (2000). T h e power law repealed: T h ecasee for an exponential law of practice. PsychonomieBulletin and Review, 7,185-207. .Heck,, A. (1997). Introduction to MAPLE (2nd ed.). New York: Springer-Verlag.Hermans,, C. (2003). De dwaaltocht van het sociaal-darwinisme:Vroegeinterpretatiesvanvan Charles Darwins theorie van natuurlijke selectie 1859-1918.Amsterdam:Uitgeverijj Nieuwezij ds.Hersen,, M., k Barlow, D. H. (1976). Single-case experimental designs: Strategies forstudyingstudying behavior change. New York: Pergamon Press.Hershberger,, S. L., Corneal, S. E., k Molenaar, P. C. M. (1995). Dynamic factor analysis:: An application t o emotional response patterns underlying daughter/fatherandd stepdaughter/stepfather relationships. Structural Equation Modeling, 2, 3 1 52. .Hershberger,, S. L., Molenaar, P. C. M., k Corneal, S. E. (1996). A hierarchy ofunivariatee and multivariate structural time series models. In G. A. Marcoulideskk R. E. Schumacker (Eds.), Advanced structural equation modeling: Issues andtechniquestechniques (pp. 159-194). Mahwah, New Jersey: Lawrence E r l b a u m Associates.Hertzog,, C , k Nesselroade, J. R. (1987). Beyond autoregressive models: Some implicationss of the trait-state distinction for the structural modeling of developmental
1288Referenceschange. Child Development,58. 93 109.Hillmer. S. (2002). Time series regression. In D. M. Moskowitz &r S. L. Hershberger(Eds.). Modeling intrainidividualvariability with repeated measures data: Methodsods and applications. Mahwah, New Jersey: Lawrence Erlbaum Associations.Hofstee,, W . (1994). Will the t r u e trait theorist please stand up? PsychologicalInquiry.5.5. 134-137.Holtzman,, W. H. (1967). Statistical models for the study of change in the single case.Inn C. W. Harris (Ed.). Problems in measuring change (p. 199-211). Madison.Wisconsin:: T h e University of Wisconsin Press.Hooker,, K. Nesselroade, D. W., Nesselroade. J. R. & Lerner. R. M. (1987). T h es t r u c t u r ee of intraindividual temperament in the context of mother-child dyads:P-techniquee factor analyses of s h o r t - t e r m change. DevelopmentalPsychology.23.23. 332 346.H o m e ,, G. P., Yang, M. C. K., & Ware, W. B. (1982). Time series analysis for singlesubjectt designs. Psychological Bulletin. 91. 178-192.Howarth. E. (1977). Mood variation p a t t e r n s based on factor analysis. PsychologicalReports.Reports. 41. 1159-1164.Hu,, L. & Bentler. P. M. (2000). Cutoff criteria for fit indexes in covariance struct u r ee analysis: Conventional criteria versus new alternatives. StructuralEquationModeling.Modeling. 6. 1-55.Humphreys,, L. G. (1960). Investigations of the simplex. Psychometrika.25. 313-323.Immink. W . (1986). Parameter estimation in Markov models and dynamicfactoranalysis. analysis.J o h n ,, O. P. (1990). T h e "Big Five" factor taxonomy: Dimensions of personality inthee n a t u r a l language and in questionnaires. In L. Pervin (Ed.), Handbook ofpersonalitypersonality theory and research (p. 66-100). New York: Guilford.Johnson. J. A. (1999). Persons in situations: Distinguishing newr wine from old wineinn new bottles. European Journal of Personality, 13, 443-453.Jones. C. J., & Nesselroade, J. R. (1990). Multivariate, replicated, single-subject,repeatedd measures design and P-technique factor analysis: A review of intraindividuall change studies. Experimental Aging Research. 4- 171-183.Jöreskog,, K. G. (1971). Estimation and testing of simplex models. The British Journalofof Mathematicaland Statistical Psychology, 23, 121-145.Jöreskog,, K. G. (1979). Statistical estimation of structural models in longitudinaldevelopmentall investigations. In J . R. Nesselroade & P. B. Baltus (Eds.), Longitudinalgitudinal research in the study of behavior and development (pp. 303-351). NewYork:: Academic Press.Jöreskog. K. G., & Sörbom, D. (1996). LISREL 8: User's reference guide. Chicago:Scientificc Software International.Jöreskog,, K. G., & Sörbom, D. (1999). LISREL 8 [computer program]. Chicago:Scientificc Software International.Kedem,, B. & Fokianos, K. (2002). Regression models for time series analysis. Hoboken,, New Jersey: J o h n Wiley and Sons.Koval,, J. J. (1997). Algorithm AS 319: Variable metric function minimization. AppliedStatistics,Statistics, 46. 515-524.Lamiell,, J. T. (1990). Explanation in t h e psychology of personality. In D. N. Robinson&& L. P. Mos (Eds.). Annals of theoretical psychology (Vol. 6. p. 153-192). NewYork:: Plenum Press.
Referencess129Lamiell. J. T. (1997). Individuals and the differnces between them
References s Aitkin,, M., & Longford, N. (1986). Statistical modelling issues in school effectiv
The love dare challenge day 1. The love dare challenge reviews. The love dare daily challenges. The love dare challenge printable. The fireproof love dare challenge. The love dare challenge app. I believe the only thing you need to have to know true love is true love. SearchReSearchDaniel M. Surprisingly, I am not in a failing marriage, but I .
DARE!! Instruments DARE!! EMC & RF Measurement equipment Vijzelmolenlaan 3 3447 GX Woerden The Netherlands Tel. 31 348 416 592 www.dare.eu instruments@dare.eu DARE!! Products B.V. CoC number: 30138672 VAT number: NL8056.13.390.B01 . The CI test Bundle is a turn-key solution for
DARE Digital Storytelling Handbook for Empowerment 5 DARE Project The DARE Digital Storytelling Handbook was developed as part of DARE: Disable the Barriers Project. It includes accessible multimedia resources to accommodate the needs of people with and without impairments. The aims of the Digital Storytelling Handbook and DARE Project are to:
solaris repository description Local\ copy\ of\ the\ Oracle\ Solaris\ 11.1\ repository solaris repository legal-uris solaris repository mirrors solaris repository name Oracle\ Solaris\ 11.1\ Package\ Repository solaris repository origins solaris repository
* 2. One to three Dare ground rod clamps 3. Dare insulated underground & hook-up wire 4. One Dare cut-off switch, if desired 5. Dare line clamps/split bolts/fence taps 6. Surge Protector * The pulse energy of the DE 20, DE 60, or DE 80 is low enough where one ground rod may be all that is needed. INSTALLING THE GROUND SYSTEM
Creating, Restoring, and Configuring the Informatica Repository 78 Starting the Informatica Repository Server 78 Creating or Restoring the Informatica Repository 79 Dropping the Informatica Repository (Optional) 81 Registering the Informatica Repository Server in Repository Server Administration Console 81 Pointing to the Informatica Repository 82
Introduction Basic Git Branching in Git GitHub Hands-on practice Git: General concepts (II/II) I clone: Clone remote repository (and its full history) to your computer I stage: Place a le in the staging area I commit: Place a le in the git directory (repository) I push: Update remote repository using local repository I pull: Update local repository using remote repository
Mar 01, 2020 · dare. I did apologize years later. But the point is that there is power in a dare. Most of us are have a daring spirit. We almost always want to rise to the challenge of something put before us, especially if done by a peer, a teacher or an employer. In general, we like to be dared. So, I want to dare you to something. This Lent I dare you to .
