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Relevant bibliographies by topics / Multilevel analysis

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Journal articles
Dissertations / Theses
Books
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Academic literature on the topic 'Multilevel analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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Journal articles on the topic "Multilevel analysis"

1

Augusto Arbugeri, Cesar, Tiago Kommers Jappe, Telles Brunelli Lazzarin, et al. "Asymetrical Multilevel Hybrid Inverter - Analysis And Experimentation." Eletrônica de Potência 24, no. 3 (2019): 296–305. http://dx.doi.org/10.18618/rep.2019.3.0031.

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Le Borne, Sabine. "Multilevel Hierarchical Matrices." SIAM Journal on Matrix Analysis and Applications 28, no. 3 (2006): 871–89. http://dx.doi.org/10.1137/040607964.

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van den Eeden, Pieter, and Joop J. Hox. "Introduction - Multilevel Analysis." Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique 51, no. 1 (1996): 5–9. http://dx.doi.org/10.1177/075910639605100101.

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Zhang, Weihua, Jiaxin Li, Yi Li, and Haibo Chen. "Multilevel Phase Analysis." ACM Transactions on Embedded Computing Systems 14, no. 2 (2015): 1–29. http://dx.doi.org/10.1145/2629594.

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Caldwell, Alex B. "Simultaneous multilevel analysis." American Psychologist 49, no. 2 (1994): 144–45. http://dx.doi.org/10.1037/0003-066x.49.2.144.

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HOX, JOOP J., and ITA G. G. KREFT. "Multilevel Analysis Methods." Sociological Methods & Research 22, no. 3 (1994): 283–99. http://dx.doi.org/10.1177/0049124194022003001.

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Blau, Peter M. "Multilevel structural analysis." Social Networks 15, no. 2 (1993): 201–15. http://dx.doi.org/10.1016/0378-8733(93)90005-6.

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Timmerman, Marieke E. "Multilevel component analysis." British Journal of Mathematical and Statistical Psychology 59, no. 2 (2006): 301–20. http://dx.doi.org/10.1348/000711005x67599.

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Kehl, René, Reinhard Nabben, and Daniel B. Szyld. "Adaptive Multilevel Krylov Methods." ETNA - Electronic Transactions on Numerical Analysis 51 (2019): 512–28. http://dx.doi.org/10.1553/etna_vol51s512.

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Kuo, C. C. Jay, Tony F. Chan, and Charles Tong. "Multilevel Filtering Elliptic Preconditioners." SIAM Journal on Matrix Analysis and Applications 11, no. 3 (1990): 403–29. http://dx.doi.org/10.1137/0611029.

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Dissertations / Theses on the topic "Multilevel analysis"

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Venkatasubramanian, S. "Illiteracy in India : a multilevel analysis." Thesis, University of Portsmouth, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302445.

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Sy, Oumar Sekou. "Multilevel mediation analysis estimation and applications /." Search for this dissertation online, 2004. http://wwwlib.umi.com/cr/ksu/main.

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Woodhouse, Geoffrey M. "Adjustment for measurement error in multilevel analysis." Thesis, University College London (University of London), 1998. http://discovery.ucl.ac.uk/10019113/.

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Measurements in educational research are often subject to error. Where it is desired to base conclusions on underlying characteristics rather than on the raw measurements of them, it is necessary to adjust for measurement error in the modelling process. In this thesis it is shown how the classical model for measurement error may be extended to model the more complex structures of error variance and covariance that typically occur in multilevel models, particularly multivariate multilevel models, with continuous response. For these models parameter estimators are derived, with adjustment based

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Wong, Chun-mei May. "Multilevel models for survival analysis in dental research." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B3637216X.

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Feng, Yuanjian. "Detection and Characterization of Multilevel Genomic Patterns." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/38577.

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DNA microarray has become a powerful tool in genetics, molecular biology, and biomedical research. DNA microarray can be used for measuring the genotypes, structural changes, and gene expressions of human genomes. Detection and characterization of multilevel, high-throughput microarray genomic data pose new challenges to statistical pattern recognition and machine learning research. In this dissertation, we propose novel computational methods for analyzing DNA copy number changes and learning the trees of phenotypes using DNA microarray data. DNA copy number change is an important form of str

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Pham, Thanh Vinh. "The performance of Multilevel Structural Equation Modeling (MSEM) in comparison to Multilevel Modeling (MLM) in multilevel mediation analysis with non-normal data." Scholar Commons, 2017. http://scholarcommons.usf.edu/etd/7077.

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The mediation analysis has been used to test if the effect of one variable on another variable is mediated by the third variable. The mediation analysis answers a question of how a predictor influences an outcome variable. Such information helps to gain understanding of mechanism underlying the variation of the outcome. When the mediation analysis is conducted on hierarchical data, the structure of data needs to be taken into account. Krull and MacKinnon (1999) recommended using Multilevel Modeling (MLM) with nested data and showed that the MLM approach has more power and f

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Neilson, Lisa Anne. "Social capital and political consumerism: a multilevel analysis." Connect to resource, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1156951934.

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Hesari, Saeed Aroni. "A multilevel superelement substructuring for boxlike caisson analysis." Thesis, University of Ottawa (Canada), 1994. http://hdl.handle.net/10393/6540.

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A multilevel superelement substructuring approach for linear-static analysis of rectangular boxlike caissons is developed. The structure is considered as an assemblage of superelements in three substructural levels. These are panel, layer, and caisson superelements. Each superelement substructure is derived by applying the principle of static condensation. Rectangular 9-node flat shell elements, which are composed of membrane stress and Mindlin plate bending elements, are assembled together to make the stiffness and load matrices of each panel substructure. Every panel substructure is condense

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Shumka, Ellen. "The social facilitation of bullying : a multilevel analysis." Thesis, University of British Columbia, 2012. http://hdl.handle.net/2429/43517.

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It is well documented that bullying is harmful and relatively common among children and adolescents. Children report understanding that bullying is wrong, yet bullying continues to be a persistent problem in schools. The goal of the present study was to examine whether children’s bullying behaviours were socially facilitated by group norms and beliefs. Children’s justifications and rationalizations for engaging in wrongful behaviour, a phenomenon referred to as moral disengagement (MD), have been linked to bullying behaviour at the individual level. Specifically, children who report engaging i

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Wong, Chun-mei May, and 王春美. "Multilevel models for survival analysis in dental research." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B3637216X.

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Books on the topic "Multilevel analysis"

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Hox, Joop J., Mirjam Moerbeek, and Rens van de Schoot. Multilevel Analysis. Routledge, 2017. http://dx.doi.org/10.4324/9781315650982.

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Hox, J. J. Applied multilevel analysis. 2nd ed. TT-Publikaties, 1995.

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J, Bosker R., ed. Multilevel analysis: An introduction to basic and advanced multilevel modeling. Sage Publications, 1999.

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Leeuw, Jan de, and Erik Meijer, eds. Handbook of Multilevel Analysis. Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-73186-5.

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de, Leeuw Jan, and Meijer Erik 1963-, eds. Handbook of multilevel analysis. Springer, 2008.

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de, Leeuw Jan, and Meijer Erik 1963-, eds. Handbook of multilevel analysis. Springer, 2008.

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de, Leeuw Jan, and Meijer Erik 1963-, eds. Handbook of multilevel analysis. Springer, 2008.

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Hox, J. J. Multilevel analysis: Techniques and applications. 2nd ed. Routledge, 2010.

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Darrell, Bock R., University of California, Los Angeles. Center for Research in Evaluation, Standards, and Student Testing., and NORC (Organization), eds. Multilevel analysis of educational data. Academic Press, 1989.

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Hox, J. J., and J. Kyle Roberts. Handbook of advanced multilevel analysis. Routledge, 2011.

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Book chapters on the topic "Multilevel analysis"

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Hox, Joop J., Mirjam Moerbeek, and Rens van de Schoot. "Introduction to Multilevel Analysis." In Multilevel Analysis. Routledge, 2017. http://dx.doi.org/10.4324/9781315650982-1.

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Hox, Joop J., Mirjam Moerbeek, and Rens van de Schoot. "Multivariate Multilevel Regression Models." In Multilevel Analysis. Routledge, 2017. http://dx.doi.org/10.4324/9781315650982-10.

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Hox, Joop J., Mirjam Moerbeek, and Rens van de Schoot. "The Multilevel Approach to Meta-Analysis." In Multilevel Analysis. Routledge, 2017. http://dx.doi.org/10.4324/9781315650982-11.

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Hox, Joop J., Mirjam Moerbeek, and Rens van de Schoot. "Sample Sizes and Power Analysis in Multilevel Regression." In Multilevel Analysis. Routledge, 2017. http://dx.doi.org/10.4324/9781315650982-12.

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Hox, Joop J., Mirjam Moerbeek, and Rens van de Schoot. "Assumptions and Robust Estimation Methods." In Multilevel Analysis. Routledge, 2017. http://dx.doi.org/10.4324/9781315650982-13.

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Hox, Joop J., Mirjam Moerbeek, and Rens van de Schoot. "Multilevel Factor Models." In Multilevel Analysis. Routledge, 2017. http://dx.doi.org/10.4324/9781315650982-14.

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Hox, Joop J., Mirjam Moerbeek, and Rens van de Schoot. "Multilevel Path Models." In Multilevel Analysis. Routledge, 2017. http://dx.doi.org/10.4324/9781315650982-15.

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Hox, Joop J., Mirjam Moerbeek, and Rens van de Schoot. "Latent Curve Models." In Multilevel Analysis. Routledge, 2017. http://dx.doi.org/10.4324/9781315650982-16.

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Hox, Joop J., Mirjam Moerbeek, and Rens van de Schoot. "The Basic Two-Level Regression Model." In Multilevel Analysis. Routledge, 2017. http://dx.doi.org/10.4324/9781315650982-2.

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Hox, Joop J., Mirjam Moerbeek, and Rens van de Schoot. "Estimation and Hypothesis Testing in Multilevel Regression." In Multilevel Analysis. Routledge, 2017. http://dx.doi.org/10.4324/9781315650982-3.

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Conference papers on the topic "Multilevel analysis"

1

G.Bhagath, Dubbaka Meghana, Begari Sneha, and Dugyala Nithin Rao. "A Comparative Analysis of Multilevel Inverter Configurations." In 2024 3rd International Conference on Automation, Computing and Renewable Systems (ICACRS). IEEE, 2024. https://doi.org/10.1109/icacrs62842.2024.10841713.

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Striz, A., and Jaroslaw Sobieszczanski-Sobieski. "Displacement based multilevel structural optimization." In 6th Symposium on Multidisciplinary Analysis and Optimization. American Institute of Aeronautics and Astronautics, 1996. http://dx.doi.org/10.2514/6.1996-4098.

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Tianxing, Man, Nataly Zhukova, and Georgi Tsochev. "A Multilevel Intelligent Assistant for Multilevel Social Network Analysis." In 2020 IEEE 10th International Conference on Intelligent Systems (IS). IEEE, 2020. http://dx.doi.org/10.1109/is48319.2020.9199840.

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Nassar, Ahmed, and Ebru Sezer. "Multilevel Sentiment Analysis In Arabic." In 2019 7th Palestinian International Conference on Electrical and Computer Engineering (PICECE). IEEE, 2019. http://dx.doi.org/10.1109/picece.2019.8747209.

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Minai, Ahmad Faiz, and Abu Tariq. "Analysis of Cascaded multilevel inverter." In 2010 India International Conference on Power Electronics (IICPE). IEEE, 2011. http://dx.doi.org/10.1109/iicpe.2011.5728129.

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Ng, Raymond T., and Dominic Tam. "Analysis of multilevel color histograms." In Electronic Imaging '97, edited by Ishwar K. Sethi and Ramesh C. Jain. SPIE, 1997. http://dx.doi.org/10.1117/12.263420.

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Karypis, George, and Vipin Kumar. "Analysis of multilevel graph partitioning." In the 1995 ACM/IEEE conference. ACM Press, 1995. http://dx.doi.org/10.1145/224170.224229.

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Alexandrov, Natalia. "Multilevel and multiobjective optimization in multidisciplinary design." In 6th Symposium on Multidisciplinary Analysis and Optimization. American Institute of Aeronautics and Astronautics, 1996. http://dx.doi.org/10.2514/6.1996-4122.

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Setianingsih, Triseu. "Performance Analysis of Children's Health Program in Indonesia: A Multilevel Analysis." In The 7th International Conference on Public Health 2020. Masters Program in Public Health, Universitas Sebelas Maret, 2020. http://dx.doi.org/10.26911/the7thicph.03.85.

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ABSTRACT Background: Most of the neonatal deaths that occur after 6-48 hours postpartum can be prevented with appropriate newborn care and initiated immediately after delivery through adequate and standardized first neonatal visit. In Indonesia, it is still not in accordance with the expected target. This study aimed to analyze the factors that influence the first neonatal visit from various levels through a multilevel analysis approach. Subjects and Method: This was a cross sectional study with samples of individual level (level 1) was 1014 mother babies, village Level (level 2) as many as 95

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YATES, K., Z. GURDAL, and S. THANGJITHAM. "Multilevel optimization using a continuum model for structures." In 4th Symposium on Multidisciplinary Analysis and Optimization. American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-4786.

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Reports on the topic "Multilevel analysis"

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Zyphur, Michael. Multilevel Modeling and Multilevel SEM in Mplus. Instats Inc., 2023. http://dx.doi.org/10.61700/k7ptxsg8judu9469.

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This seminar introduces the Mplus multilevel latent variable modeling framework and describes multilevel variance/effect decomposition, random/fixed effects (including random slopes), and then proceeds to explore multilevel path analysis, multilevel CFA including multilevel bi-factor models, and multilevel SEM. Topics include ways to handle strong correlations at the between-group level, indirect effects (multilevel mediation), interaction effects (multilevel moderation), and conditional indirect effects (multilevel moderated mediation). An official Instats certificate of completion and 2 ECTS

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Zhang, Zhen. Multilevel SEM in Mplus. Instats Inc., 2022. http://dx.doi.org/10.61700/p80oftrbgz4z3469.

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This seminar introduces the Mplus multilevel latent variable modeling framework and describes topics including multilevel variance and effect decomposition, and random and fixed effects (including random slopes), and then proceeds to explore multilevel path analysis, multilevel CFA including multilevel bi-factor models, and multilevel SEM, including approaches for handling strong correlations at the between-group level, indirect effects (multilevel mediation), interaction effects (multilevel moderation), and conditional indirect effects (multilevel moderated mediation). An official Instats cer

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Zeigler-Johnson, Charnita. Multilevel Analysis of Neighborhood Characteristics and Prostate Cancer. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada574693.

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Zeigler-Johnson, Charnita. Multilevel Analysis of Neighborhood Characteristics and Prostate Cancer. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada554191.

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Zyphur, Michael. Multilevel SEM with Moderated Mediation in R. Instats Inc., 2022. http://dx.doi.org/10.61700/4cq04v1o6f59u469.

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This seminar introduces the Lavaan multilevel latent variable modeling framework and describes multilevel variance and effect decomposition, and then proceeds with multilevel path analysis, multilevel CFA, and multilevel SEM, including approaches for handling strong correlations at the between-group level, indirect effects (multilevel mediation), interaction effects (multilevel moderation), conditional indirect effects (multilevel moderated mediation), bootstrapping, and instrumental variable methods for identifying multilevel causal effects. An official Instats certificate of completion is pr

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Zhang, Zhen. Multilevel SEM with Random Slopes and Moderated Mediation in Mplus. Instats Inc., 2022. http://dx.doi.org/10.61700/5a63kcb9bqqqq469.

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This seminar introduces the Mplus multilevel latent variable modeling framework and describes topics including multilevel variance and effect decomposition, and random and fixed effects (including random slopes), and then proceeds to explore multilevel path analysis, multilevel CFA including multilevel bi-factor models, and multilevel SEM, including approaches for handling strong correlations at the between-group level, indirect effects (multilevel mediation), interaction effects (multilevel moderation), and conditional indirect effects (multilevel moderated mediation). An official Instats cer

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Zyphur, Michael. Multilevel SEM with Moderated Mediation in Mplus. Instats Inc., 2022. http://dx.doi.org/10.61700/khz0yfni0ofmb469.

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This seminar introduces the Mplus multilevel latent variable modeling framework and describes topics including multilevel variance and effect decomposition, and random and fixed effects (including random slopes), and then proceeds to explore multilevel path analysis, multilevel CFA including multilevel bi-factor models, and multilevel SEM, including approaches for handling strong correlations at the between-group level, indirect effects (multilevel mediation), interaction effects (multilevel moderation), and conditional indirect effects (multilevel moderated mediation). An official Instats cer

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Zhang, Zhen. Multilevel SEM in Mplus (Free with Course Purchase). Instats Inc., 2023. http://dx.doi.org/10.61700/aicphe1kyt4hf469.

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This seminar introduces the Mplus multilevel latent variable modeling framework and describes topics including multilevel variance and effect decomposition, and random and fixed effects (including random slopes), and then proceeds to explore multilevel path analysis, multilevel CFA including multilevel bi-factor models, and multilevel SEM, including approaches for handling strong correlations at the between-group level, indirect effects (multilevel mediation), interaction effects (multilevel moderation), and conditional indirect effects (multilevel moderated mediation). An official Instats cer

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de Saussure, G., N. M. Larson, J. A. Harvey, and N. W. Hill. Multilevel resonance analysis of sup 59 Co neutron transmission measurements. Office of Scientific and Technical Information (OSTI), 1991. http://dx.doi.org/10.2172/5697452.

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Manteuffel, T. Development and Analysis of Optimal Multilevel Solvers on Advanced Computers. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1898297.

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