Bibliographies thématiques / Longitudinal data analysi

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Littérature scientifique sur le sujet « Longitudinal data analysi »

Auteur : Grafiati
Publié le 9 mars 2023
Mis à jour le 31 juillet 2025

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Articles de revues sur le sujet "Longitudinal data analysi"

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Vakulenko, Elena S. "Comparative Analysis of Interregional and Intersectoral Mobility in Russia." Economy of Region 16, no. 4 (2020): 1193–120. http://dx.doi.org/10.17059/ekon.reg.2020-4-13.

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One of the most important characteristics of the labour market is labour mobility that allows assessing the economic efficienc y o f labour . A comparativ e analysi s i s necessar y fo r determinin g th e degre e o f mobility . I n term s o f spatia l and sectoral characteristics, the paper assesses the degree and dynamics of mobility in the Russian labour market based on previously published studies, as well as the authors’ findings. To determine the degree of mobility, the research uses various approaches, applying both direct (mobility costs, transition matrices) and indirect indicators (st
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Vakulenko, Elena S. "Comparative Analysis of Interregional and Intersectoral Mobility in Russia." Economy of Region 16, no. 4 (2020): 1193–120. http://dx.doi.org/10.17059/ekon.reg.2020-4-13.

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One of the most important characteristics of the labour market is labour mobility that allows assessing the economic efficienc y o f labour . A comparativ e analysi s i s necessar y fo r determinin g th e degre e o f mobility . I n term s o f spatia l and sectoral characteristics, the paper assesses the degree and dynamics of mobility in the Russian labour market based on previously published studies, as well as the authors’ findings. To determine the degree of mobility, the research uses various approaches, applying both direct (mobility costs, transition matrices) and indirect indicators (st
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Czernitzki, Anna-Franziska, Christina Pospisil, Martin Musalek, Rebekka Mumm, and Christiane Scheffler. "Analysis of longitudinal data of height z-scores in kindergarten children – A pilot study." Anthropologischer Anzeiger 74, no. 2 (2017): 109–12. http://dx.doi.org/10.1127/anthranz/2017/0708.

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Baltagi, Badi H. "Longitudinal Data Analysis." Journal of the Royal Statistical Society: Series A (Statistics in Society) 172, no. 4 (2009): 939–40. http://dx.doi.org/10.1111/j.1467-985x.2009.00614_9.x.

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Carey, Vincent J. "Longitudinal Data Analysis." Journal of the American Statistical Association 102, no. 479 (2007): 1075. http://dx.doi.org/10.1198/jasa.2007.s202.

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Oppliger, Robert A., Steven W. Marshall, and Ian D. Shrier. "Longitudinal Data Analysis." Medicine & Science in Sports & Exercise 33, no. 5 (2001): S85. http://dx.doi.org/10.1097/00005768-200105001-00489.

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Ployhart, Robert E., Brian C. Holtz, and Paul D. Bliese. "Longitudinal data analysis." Leadership Quarterly 13, no. 4 (2002): 455–86. http://dx.doi.org/10.1016/s1048-9843(02)00122-4.

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Ugarte, M. Dolores. "Longitudinal data analysis." Journal of Applied Statistics 36, no. 10 (2009): 1175–76. http://dx.doi.org/10.1080/02664760902811563.

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Ziegel, Eric R., P. Diggle, K. Liang, and S. Zeger. "Analysis of Longitudinal Data." Technometrics 37, no. 3 (1995): 356. http://dx.doi.org/10.2307/1269941.

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Ziegel, Eric R., D. Hand, and M. Crowder. "Practical Longitudinal Data Analysis." Technometrics 39, no. 1 (1997): 112. http://dx.doi.org/10.2307/1270801.

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Thèses sur le sujet "Longitudinal data analysi"

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LIU, XIAOQIU. "Managing Cardiovascular Risk in Hypertension: Methodological Issues in Blood Pressure Data Analysis." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2017. http://hdl.handle.net/10281/154475.

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Hypertension remains in 2017 a leading cause of mortality and disability worldwide. A number of issues related to the determinants of cardiovascular risk in hypertensive patients and to the strategies for better hypertension control are still pending. In such a context, aims of my research program were: 1. To investigate the contribution of blood pressure variability to the risk of cardiovascular mortality in hypertensive patients. In this setting, different methods for assessing blood pressure variability and different models exploring the link between blood pressure variability and outcome
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Petzold, Max. "Evaluation of information in longitudinal data." Göteborg : Statistical Research Unit, Göteborg University, 2003. http://catalog.hathitrust.org/api/volumes/oclc/52551306.html.

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Yao, Fang. "Functional data analysis for longitudinal data /." For electronic version search Digital dissertations database. Restricted to UC campuses. Access is free to UC campus dissertations, 2003. http://uclibs.org/PID/11984.

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Sort, Lucas. "Development of new statistical approaches for the investigation of multiblock and tensor longitudinal data." Electronic Thesis or Diss., université Paris-Saclay, 2025. http://www.theses.fr/2025UPASG001.

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En recherche médicale, les données sont devenues de plus en plus complexes au cours des dernières décennies. En effet, les données sont désormais souvent observées à différentes occasions au cours du temps pour permettre un meilleur suivi de l'évolution des processus biologiques ayant un intérêt d'ordre médical. Dans ce contexte, ces données, souvent nommées données longitudinales, possèdent fréquemment une structure complexe de dimension élevée. Par exemple, dans un nombre croissant de situations, les données peuvent être structurées en un tableau multidimensionnel, également appelé tenseur.
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Zhu, Liang. "Semiparametric analysis of multivariate longitudinal data." Diss., Columbia, Mo. : University of Missouri-Columbia, 2008. http://hdl.handle.net/10355/6044.

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Thesis (Ph. D.)--University of Missouri-Columbia, 2008.<br>The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on August 3, 2009) Vita. Includes bibliographical references.
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Mills, Joanna E. "The analysis longitudinal binary data." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/NQ57350.pdf.

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Fullwood, Catherine Lee. "Longitudinal analysis of anticoagulent data." Thesis, Lancaster University, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.431469.

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Bai, Yang, and 柏楊. "Statistical analysis for longitudinal data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B42841756.

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Bai, Yang. "Statistical analysis for longitudinal data." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B42841756.

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Kim, Yangjin. "Statistical analysis of longitudinal data /." free to MU campus, to others for purchase, 2003. http://wwwlib.umi.com/cr/mo/fullcit?p3100054.

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Livres sur le sujet "Longitudinal data analysi"

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Donald, Hedeker, and Gibbons Robert D. Longitudinal Data Analysis. John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/0470036486.

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Funatogawa, Ikuko, and Takashi Funatogawa. Longitudinal Data Analysis. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-0077-5.

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Hedeker, Donald R. Longitudinal data analysis. Wiley-Interscience, 2006.

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1962-, Fitzmaurice Garrett M., ed. Longitudinal data analysis. Chapman & Hall/CRC, 2008.

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1955-, Gibbons Robert D., ed. Longitudinal data analysis. J. Wiley, 2006.

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Robert, Crouchley, ed. Longitudinal data analysis. Avebury, 1987.

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Sutradhar, Brajendra C. Longitudinal Categorical Data Analysis. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-2137-9.

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Hand, David, and Martin Crowder. Practical Longitudinal Data Analysis. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4899-3033-0.

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Peter, Diggle, and Diggle Peter, eds. Analysis of longitudinal data. 2nd ed. Oxford University Press, 2002.

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Kung-Yee, Liang, and Zeger Scott L, eds. Analysis of longitudinal data. Clarendon Press, 1994.

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Chapitres de livres sur le sujet "Longitudinal data analysi"

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Dugard, pat, John Todman, and Harry Staines. "Longitudinal data." In Approaching Multivariate Analysis, 2nd ed. Routledge, 2022. http://dx.doi.org/10.4324/9781003343097-15.

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Funatogawa, Ikuko, and Takashi Funatogawa. "Longitudinal Data and Linear Mixed Effects Models." In Longitudinal Data Analysis. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-0077-5_1.

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Funatogawa, Ikuko, and Takashi Funatogawa. "Autoregressive Linear Mixed Effects Models." In Longitudinal Data Analysis. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-0077-5_2.

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Funatogawa, Ikuko, and Takashi Funatogawa. "Case Studies of Autoregressive Linear Mixed Effects Models: Missing Data and Time-Dependent Covariates." In Longitudinal Data Analysis. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-0077-5_3.

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Funatogawa, Ikuko, and Takashi Funatogawa. "Multivariate Autoregressive Linear Mixed Effects Models." In Longitudinal Data Analysis. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-0077-5_4.

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Funatogawa, Ikuko, and Takashi Funatogawa. "Nonlinear Mixed Effects Models, Growth Curves, and Autoregressive Linear Mixed Effects Models." In Longitudinal Data Analysis. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-0077-5_5.

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Funatogawa, Ikuko, and Takashi Funatogawa. "State Space Representations of Autoregressive Linear Mixed Effects Models." In Longitudinal Data Analysis. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-0077-5_6.

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Cummings, Peter. "Longitudinal Data." In Analysis of Incidence Rates. Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9780429055713-19.

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Hox, Joop J., Mirjam Moerbeek, and Rens van de Schoot. "Analyzing Longitudinal Data." In Multilevel Analysis. Routledge, 2017. http://dx.doi.org/10.4324/9781315650982-5.

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Das, Abhik. "Longitudinal Data Analysis." In Encyclopedia of Quality of Life and Well-Being Research. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_1698.

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Actes de conférences sur le sujet "Longitudinal data analysi"

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Syrmoudis, Emmanuel, Stefan A. Mager, and Jens Grossklags. "A Longitudinal Analysis of Corporate Data Portability Practices Across Industries." In 2024 Annual Computer Security Applications Conference (ACSAC). IEEE, 2024. https://doi.org/10.1109/acsac63791.2024.00032.

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Jafari, Sadegh, Mahsa Farsouni Nezhad, Melika Nobakhtian, Arash Chaichi Mellatshahi, and Amirmohammad Kazemeini. "A Silent Voice: A Bilingual Longitudinal Analysis of Mahsa Amini’s Movement Tweet." In 2024 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2024. https://doi.org/10.1109/icdmw65004.2024.00062.

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Fomo, Desmond, and Aki-Hiro Sato. "Enhancing Big Data Analysis: A Recursive Window Segmentation Strategy for Multivariate Longitudinal Data." In 2024 IEEE International Conference on Big Data (BigData). IEEE, 2024. https://doi.org/10.1109/bigdata62323.2024.10825192.

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B, Abhin, and Renukasakshi V Patil. "Transformer-Based Analysis of Adaptive and Maladaptive Self-States in Longitudinal Social Media Data." In Proceedings of the 10th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2025). Association for Computational Linguistics, 2025. https://doi.org/10.18653/v1/2025.clpsych-1.26.

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Nguyen, Van Bac, Iman Hajirasouliha, and Martin English. "Flexural strength and behaviour of cold rolled purlins with complex longitudinal stiffeners." In IABSE Symposium, Tokyo 2025: Environmentally Friendly Technologies and Structures: Focusing on Sustainable Approaches. International Association for Bridge and Structural Engineering (IABSE), 2025. https://doi.org/10.2749/tokyo.2025.2715.

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&lt;p&gt;This paper presents the flexural strength and behaviour of cold rolled channel and zed steel purlins with complex longitudinal web and flange stiffeners. The material properties at the section’s flat parts, corners, and stiffeners are obtained from tensile tests. A series of four-point beam bending tests is carried out to determine the buckling and ultimate bending capacities of these sections. Nonlinear Finite Element analysis (FEA) is developed to model the flexural strength of the purlins and validated against the experimental tests. True stress-strain data for materials due to col
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Murkute, Nikhil, Shubhanshu Gupta, and Abhishek Abhishek. "Performance Analysis of Biplane Tailsitter UAV with Added Tail." In Vertical Flight Society 81st Annual Forum and Technology Display. The Vertical Flight Society, 2025. https://doi.org/10.4050/f-0081-2025-330.

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This paper explores the effect of addition of a horizontal tail on the longitudinal stability and performance of a Biplane Tailsitter Unmanned Aerial Vehicle (UAV). Biplane tailsitters a type of hybrid UAVs, often exhibits poor longitudinal stability during forward flight, necessitating continuous active control through application of differential motor thrust to maintain attitude. To address this challenge, this work proposes the integration of a horizontal tail on a quadrotor biplane tailsitter UAV, aiming to improve pitch stability and control authority during critical flight phases. Experi
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Chitla, Vikas Benhur, P. S. Lakshminarasimhan, Mv Manoj Kumar, and B. S. Prashanth. "Multivariate Analysis and Detection of Concept Drift in Longitudinal COVID-19 Data: Implications for Adaptive Healthcare Strategies." In 2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON). IEEE, 2024. http://dx.doi.org/10.1109/nmitcon62075.2024.10699076.

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Yao, Zhenjie, Yixin Chen, Jinwei Wang, et al. "Trend Analysis Neural Networks for Interpretable Analysis of Longitudinal Data." In 2021 IEEE International Conference on Big Data (Big Data). IEEE, 2021. http://dx.doi.org/10.1109/bigdata52589.2021.9671590.

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Boni, Mohammad Al, Seth Green, Megan Stiles, Katherine Harton, and Donald E. Brown. "Longitudinal Analysis of Linguistic flexibility of Value-motivated Groups." In 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. http://dx.doi.org/10.1109/bigdata.2018.8622319.

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Li, Yimei, Hongtu Zhu, Yasheng Chen, et al. "LSTGEE: longitudinal analysis of neuroimaging data." In SPIE Medical Imaging, edited by Josien P. W. Pluim and Benoit M. Dawant. SPIE, 2009. http://dx.doi.org/10.1117/12.812432.

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Rapports d'organisations sur le sujet "Longitudinal data analysi"

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Ferrer, Emilio. Applied Longitudinal Data Analysis. Instats Inc., 2023. http://dx.doi.org/10.61700/xomktodmxmv62469.

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This comprehensive 3-day workshop is designed to equip researchers with the skills to effectively analyze longitudinal data with classic and advanced modeling techniques. The seminar covers a range of topics from understanding the importance of longitudinal data, handling missing data, modeling growth over time, to practical sessions on applying learned techniques using real-world data, with an official Instats certificate of completion provided at the conclusion. An official Instats certificate of completion and 2 ECTS Equivalent points are provided at the conclusion of the seminar.
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Du, Han. Applied Longitudinal Data Analysis in R and SPSS. Instats Inc., 2024. http://dx.doi.org/10.61700/kdliyn5fqb7tr1173.

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Longitudinal data facilitates exploring intra-individual change over time and differences across people in these changes. This workshop equips participants with essential skills to analyze data and report results of longitudinal research effectively, with all worked exercises completed using R and SPSS. The workshop will explore techniques including multilevel modeling, latent growth curve models, cross-lagged models, longitudinal mediation models, longitudinal dyadic models, and other models.
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Snijders, Tom. Longitudinal Social Network Analysis. Instats Inc., 2024. https://doi.org/10.61700/zimra7qjrsnu11850.

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This three-day workshop provides an introductory overview of longitudinal social network analysis using the RSiena package, focusing on the application of Stochastic Actor-oriented Models to study network dynamics and the co-evolution of networks and behavior. Participants will gain practical skills in modeling network panel data, as well as modeling co-evolution of networks and behavior, for application of these techniques across various academic disciplines.
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Chen, Maximillian Gene, Kristin Marie Divis, James D. Morrow, and Laura A. McNamara. Visualizing Clustering and Uncertainty Analysis with Multivariate Longitudinal Data. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1472228.

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Foged, Mette, and Giovanni Peri. Immigrants' and Native Workers: New Analysis on Longitudinal Data. National Bureau of Economic Research, 2013. http://dx.doi.org/10.3386/w19315.

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Koval, Peter. Intensive Longitudinal Methods: Design and Analysis in Mplus. Instats Inc., 2024. http://dx.doi.org/10.61700/ncsi7t3zajruo1470.

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This two-day workshop provides a comprehensive understanding of intensive longitudinal methods essential for capturing dynamic processes over time, with a focus on using Mplus for data analysis. Participants will gain practical skills in designing, analyzing, and interpreting intensive longitudinal data, enhancing the rigor and impact of their research. An official Instats certificate of completion is provided at the conclusion of the seminar. For European PhD students, the seminar offers ECTS Equivalent points.
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Aassve, Arnstein, Francesco C. Billari, Stefano Mazzuco, and Fausta Ongaro. Leaving Home Ain't Easy. A comparative longitudinal analysis of ECHP data. Max Planck Institute for Demographic Research, 2001. http://dx.doi.org/10.4054/mpidr-wp-2001-038.

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Servais, Marita. Overview of HRS Public Data Files for Cross-sectional and Longitudinal Analysis. Institute for Social Research, University of Michigan, 2010. http://dx.doi.org/10.7826/isr-um.06.585031.001.05.0023.2010.

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Rogers, Jessa, Kate E. Williams, Kristin R. Laurens, et al. Footprints in Time: Longitudinal Study of Indigenous Children. Queensland University of Technology, 2022. http://dx.doi.org/10.5204/rep.eprints.235509.

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The Longitudinal Study of Indigenous Children (LSIC; also called Footprints in Time) is the only longitudinal study of developmental outcomes for Aboriginal and Torres Strait Islander children globally. Footprints in Time follows the development of Australian Aboriginal and Torres Strait Islander children to understand what Indigenous children need to grow up strong. LSIC involves annual waves of data collection (commenced in 2008) and follows approximately 1,700 Aboriginal and Torres Strait Islander children living in urban, regional, and remote locations. This LSIC Primary School report has
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Koval, Peter, and Elise Kalokerinos. Intensive Longitudinal Methods for Psychology using R. Instats Inc., 2022. http://dx.doi.org/10.61700/2gunyc62jbmzc469.

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This seminar introduces intensive longitudinal methods (experience sampling, ecological momentary assessment, diary methods, ambulatory assessment), which involve dense repeated sampling of psychological processes in daily life. Topics include intensive longitudinal study design (Day 1), followed by basic analyses and multilevel modeling of these data using R (Day 2). An official Instats certificate of completion is provided at the conclusion of the seminar.
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