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SUMMARY:Longitudinal Structural Equation Modeling (LSEM)
DESCRIPTION:LIVE STREAM – 4-day Statistics Short Course\nDOWNLOAD SAMPLE COURSE SLIDES AND WATCH COURSE VIDEO PREVIEW\nSeminar Overview:\nA comprehensive 4-day Stats Camp seminar on Longitudinal Structural Equation Modeling. \nSeminar Topics:\n\nDesign and measurement considerations in longitudinal research\nBuilding and evaluating a longitudinal SEM\nLatent Panel SEMs\nEvaluating longitudinal measurement invariance\nMultiple group longitudinal SEM\nLatent Mediation SEM\nLatent growth curve analysis\nAdditional considerations for longitudinal modeling such as missing data and parceling\n\nSeminar Description:\nThis camp is an advanced intensive short course in the analysis of longitudinal data using SEM. The course includes a series of live lectures along with time for individual and group consultation time to provide participants with the tools needed to use of SEM for the analysis of longitudinal data. If you already have a strong background in the application of SEM to analyze the covariance structure of multivariate data and you need to learn how to apply more advanced models to longitudinal data\, this course is for you. Participants from a variety of fields\, including sociology\, psychology\, education\, human development\, marketing\, business\, biology\, medicine\, political science\, and communication\, will benefit from the course. \nParticipants will receive a link to the course materials by the first day that includes lecture slides\, software example scripts (in Mplus\, lavaan\, and LISREL)\, relevant supporting documentation\, and recommended readings. Participants will receive a link to the course video recording at the end of the camp. \nInstructor: Todd Little\, Ph.D.\n \nTodd D. Little\, Ph.D. is a Professor of Educational Psychology at Texas Tech University (TTU). Little is internationally recognized for his quantitative work on various aspects of applied SEM (e.g.\, indicator selection\, parceling\, modeling developmental processes) as well as his substantive developmental research (e.g.\, action-control processes and motivation\, coping\, and self-regulation). Prior to joining TTU\, …  Little has guided quantitative training and provided consultation to students\, staff\, and faculty at the Max Planck Institute for Human Development’s Center for Lifespan Studies (1991-1998)\, Yale University’s Department of Psychology (1998-2002)\, and researchers at KU (2002-2013\, including as director of the RDA unit at the Lifespan Institute and as director of the Center for Research Methods and Data Analysis). In 2001\, Little was elected to membership in the Society for Multivariate Experimental Psychology\, a restricted-membership society of quantitative specialists in the behavioral and social sciences.\n \nIn 2009\, he was elected President of APA’s Division 5 (Evaluation\, Measurement\, and Statistics). He founded\, organizes\, and teaches in the internationally renowned ‘Stats Camps’ each June (see statscamp.org for details of the summer training programs) and has given over 150 workshops and talks on methodology topics around the world. As an interdisciplinary-oriented collaborator\, Little has published with over 280 persons from around the world in over 65 different peer-reviewed journals. His work has garnered over 11\,000 citations. He published Longitudinal Structural Equation Modeling in 2013 and he has edited five books related to methodology\, including the Oxford Handbook of Quantitative Methods and the Guildford Handbook of Developmental Research Methods (with Brett Laursen and Noel Card). Little has served on numerous grant review panels for federal agencies such as NSF\, NIH\, and IES\, and private foundations such as the Jacobs Foundation. He has been the principal investigator or co-principal investigator on over 15 grants and contracts and he has served as a statistical consultant on over 70 grants and contracts. In the conduct of his collaborative research\, he has participated in the development of over 12 different measurement tools\, including the CAMI\, the Multi-CAM\, the BALES\, the BISC\, the I FEEL\, and the form/function decomposition of aggression. \n\n\nInstructor: Zachary Stickley\, Ph.D.\n \nZachary\, Ph.D. is a senior research scientist at Yhat Enterprises LLC. where he pursues his research interests in measurement design\, applied latent variable modeling\, and modern approaches to missing data. Dr. Stickley has also served as an instructor and coordinator for the Stats Camp Foundation since first joining the team as a graduate student in 2018. He received his Ph.D. in Educational Psychology from College of Education at Texas Tech University with a focus on research methodology\, measurement design\, and statistical modeling. He received his Master of Education degree from Texas Tech University and his Bachelor of Science in Psychology from Tarleton State University. \nRead More\n\n\nAPA Continuing Education Credits:\n \nThis course offers 16 hours of Continuing Education Credits. Stats Camp Foundation is approved by the American Psychological Association to sponsor continuing education for psychologists. Stats Camp Foundation maintains responsibility for this program and its content. \nSeminar Includes:\nMaterials\, downloads\, recorded course video viewable for up to one year. \n\n\n\nLearning Objectives\nLearning Objectives:\nThis comprehensive 4-day statistics training institute on Longitudinal SEM will enable participants to:\n\nUnderstand the strengths and weaknesses of the different models that can be applied to longitudinal data.\nDevelop a clear understanding of how the models can be specified and adapted to address the specific needs and questions of the investigator.\nGain knowledge of the ways in which one should formulate models\, test alternative models\, and evaluate models with regard to statistical and practical significance.\n\nSeminar Prerequisites\nSeminar Prerequisites:\nRequired: \n\nProficiency in multiple linear regression.\nAt least limited experience (e.g.\, graduate-level course) with continuous latent variable models\, e.g.\, exploratory and confirmatory factor analysis (EFA; CFA) and structural equation modeling (SEM).\nWe strongly recommend that you attend our foundations of SEM as a pre-requisite to taking this advanced course. If you have not taken the foundations course\, you should have extensive experience or have taken a graduate-level course on SEM before enrolling.\nIntermediate proficiency with at least one statistical software package (e.g.\, SPSS\, Stata\, SAS\, R\, LISREL\, Mplus\, etc.).\n\nNot required but advantageous: \n\nAt least limited experience (e.g.\, graduate-level course) with multivariate data analysis.\n\nNo level of proficiency beyond basic awareness is assumed for skills related to: \n\nLongitudinal SEM.\nAdvanced mathematical or statistical topics such as matrix algebra or likelihood theory.\n\nSoftware and Computer Support\nSoftware and Computer Support:\nParticipants need a laptop computer with Wi-Fi and webcam capabilities. \nAll statistical software used at Stats Camp will be available\, free to participants\, on our SMORS (statistical modeling on remote servers) system for the duration of camp. \nAll statistical software used at Stats Camp will be available\, free to participants\, on our SMORS (statistical modeling on remote servers) system for the duration of camp.Syllabus\n\n\n\nDay 1\n \n\n\n9:00-10:45\nWelcome and Introductions. Overview of Longitudinal Models\n\n\n10:45-11:00\nSnack and Refreshment Break\n\n\n11:00-12:30\nReview of Foundations of SEM\n\n\n12:30-1:30\nLunch Break\n\n\n1:30-3:00\nParcels and Parceling\n\n\nDay 2\n\n\n\n9:00-10:45\nDesign and Measurement Issues in Longitudinal Modeling\n\n\n10:45-11:00\nSnacks and Refreshment Break\n\n\n11:00-12:30\nLongitudinal Panel Models: Basics\n\n\n12:30-1:30\nLunch Break\n\n\n1:30-3:00\nMultiple-group Longitudinal Panel Models: CFA\, SEM\, & RI-CLPM\n\n\nDay 3\n \n\n\n9:00-10:45\nMixture Modeling\n\n\n10:45-11:00\nSnack and Refreshment Break\n\n\n11:00-12:30\nMixture Modeling\n\n\n12:30-1:30\nLunch Break & Individual Consultations\n\n\n1:30-2:30\nLongitudinal Mediation\n\n\n2:30-3:00\nIndividual Consultations\n\n\nDay 4\n\n\n\n9:00-10:45\nLatent Growth Curve Modeling: Basics & Multivariate and Multiple Groups\n\n\n10:45-11:00\nSnacks and Refreshment Break\n\n\n11:00-12:30\nMissing Data: Planned and Unplanned\n\n\n12:30-1:30\nLunch Break & Individual Consultations\n\n\n1:30-2:30\nLongitudinal Moderation\n\n\n2:30-3:00\nWrap-up then Individual Consultations\n\n\n\nDownload Sample Slides and Preview Course Video\nPlease fill out and submit the form below to get instant access to sample course materials.
URL:https://www.statscamp.org/courses/longitudinal-structural-equation-modeling/
LOCATION:Livestream and/or Asynchronous:\, If you are unavailable to join live via Zoom\, you can participate asynchronously by viewing the recorded course videos for up to 1 year.
CATEGORIES:Longitudinal SEM,Longitudinal Structural Equation Modeling,Winter Camp
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SUMMARY:Latent Profile Analysis
DESCRIPTION:LIVE STREAM – 4-day Statistics Short Course\n\nDOWNLOAD SAMPLE COURSE SLIDES AND WATCH COURSE VIDEO PREVIEW\nSeminar Overview:\nAn introduction to “person-centered” data analysis. Topics include latent profile analysis (aka\, latent class cluster analysis)\, and modeling predictors and outcomes of latent profile membership. Hands-on practice with Mplus is provided. \nSeminar Topics:\nLatent Profile Analysis (LPA) steps including research questions appropriate for latent profile analysis\, profile (class) enumeration and assessing profile model results (classification quality\, profile homogeneity and separation)\, predicting profile membership with other variables and profile membership predicting outcomes. Practice analyses will be completed to build comfort with syntax and reading of output. We will also cover how to interpret and present the results to maximize audience understanding. \nSeminar Description:\nThis four-day camp is an intensive short seminar in the fundamentals of latent profile analysis (LPA).\nLPA is a type of latent variable model-based finite mixture models that express the overall distribution of one or more continuous variables as a mixture of a finite number of component distributions. In direct applications\, one assumes that the overall population heterogeneity with respect to a set of continuous\, manifest variables is due to the existence of two or more distinct homogeneous subgroups\, or latent profiles\, of individuals. These approaches are often termed “person-centered” analyses in contrast to the “variable-centered” analyses of conventional factor and SEM models. \nThis seminar will introduce participants to the prevailing “best practices” for direct applications of basic latent profile analysis to cross-sectional data\, specifically latent profile analysis (LPA) also known as latent class cluster analysis (LCCA)\, including model assumptions\, specification\, estimation\, evaluation\, selection\, and interpretation. Models that allow for the inclusion of correlates and predictors of latent profile membership as well as distal outcomes of latent profile membership will be presented. The implementation of these models in the most recent version of the Mplus software will be demonstrated and practiced throughout the seminar. \nInstructor: Whitney Moore\, Ph.D.\n \nDr. Whitney Moore is an Assistant Professor of Kinesiology at East Carolina University. Whitney received her Ph.D. in the Psychosocial Aspects of Health and Physical Activity from the University of Kansas. She has been a Stats Camp instructor since 2012 (after experience being a “counselor” for SEM\, Longitudinal SEM\, and MLM). Whitney has taught graduate courses in research design\, introduction to statistics\, ANOVA\, SEM\, and measurement development at two different R1 institutions. Her research is at the intersection of advanced quantitative methods and psychosocial aspects applied to sport\, exercise\, and physical education contexts. This is particularly illustrated in her work on measurement development; helping to develop or modify 12 measures in the last 10 years. Whitney is particularly interested in planned missing data designs\, finite mixture modeling\, plus mediation and moderation in SEM. \nRead More\n\n\nAPA Continuing Education Credits:\n \nThis course provides 16 credit hours for continuing education. Stats Camp Foundation is approved by the American Psychological Association to sponsor continuing education for psychologists. Stats Camp Foundation maintains responsibility for this program and its content. \n\nSeminar Includes:\nMaterials\, downloads\, recorded course video viewable for up to one year. \n\n\n\nLearning Objectives\nLearning Objectives:\nThis comprehensive 4-day statistics training institute on Latent Profile Analysis will enable participants to:\n\nAcquire understanding of latent profile analysis techniques as applied in the social and behavioral sciences.\nDevelop an appreciation for the research questions and data best suited for latent profile analysis models and the common pitfalls leading to the misuse of mixture models.\nGain detailed knowledge of current “best practices” for mixture model specification\, estimation\, selection\, evaluation\, comparison\, interpretation\, and presentation.\nUnderstand how latent profile variables may be integrated into a larger (latent) variable system.\nBecome acquainted with a variety of mixture modeling extensions.\nBecome proficient in the use of Mplus for analysis of mixture models.\n\nThis seminar is intended to give participants the knowledge and understanding necessary to identify and effectively execute “person-centered” analysis strategies with continuous variables using Mplus that might be most appropriate for their research questions. The seminar is also intended to provide a foundation for future learning about mixture modeling and resources to guide such endeavors. \nSeminar Prerequisites\nSeminar Prerequisites:\nIf you are interested in learning “person-centered” statistical modeling techniques that can identify unobserved subgroups (latent profiles) characterized by qualitative differences in observed multivariate outcome distributions\, this seminar is for you. You should have a good working knowledge of the principles and practice of multiple regression and elementary statistical inference. You will get the most out of the seminar if you already have experience with binary and multinomial logistic regression. You do not need to know matrix algebra\, likelihood theory\, or SEM\, although that knowledge would be beneficial. No previous knowledge of mixture modeling\, latent class analysis\, latent profile analysis\, or Mplus is assumed. Participants from a variety of fields—including psychology\, education\, human development\, public health\, prevention science\, sociology\, marketing\, business\, biology\, medicine\, political science\, and communication—will benefit from the seminar. \nSoftware and Computer Support\nSoftware and Computer Support:\nParticipants should have a laptop computer. Instruction will be provided for the methods using the most current version of Mplus (base program with mixture add-on or base program with combination add-on). Mplus is available for Windows\, Mac\, and Linux environments (www.statmodel.com). \nParticipants who do not have access to software will be given temporary access to the server that contains fully functioning versions of the recommended software.\nNote: We will also make use of Excel to do various post-processing summaries. \nParticipants will receive an electronic copy of all seminar materials\, including PowerPoint slides\, Mplus scripts\, output files\, relevant supporting documentation\, and recommended readings. \nAll statistical software used at Stats Camp will be available\, free to participants\, on our SMORS (statistical modeling on remote servers) system for the duration of camp.Syllabus\n\n\n\n\n\n\n\n\nDay 1\n \n\n\n9:00-9:30\nWelcome and introductions plus Zoom Orientation\n\n\n9:30-10:30\nOverview of mixture modeling in a general latent variable framework\n\n\n10:30-10:45\nSnack and refreshment break\n\n\n10:45-12:15\nOverview of mixture modeling in a general latent variable framework\n\n\n12:30-1:30\nLunch break\n\n\n1:30-3:15\nOverview of LPA steps\n\n\n3:15-3:30\nSnack and refreshment break\n\n\n3:30-5:00\nIntroduction to Mplus syntax introduction with Latent Profile Analysis (LPA) example\n\n\n5:30~7:30\nSocial “hour” reception for all Stats Campers\n\n\nDay 2\n\n\n\n9:00-9:30\nQ & A\n\n\n9:30-10:45\nLPA class enumeration across variance-covariance structures introduction\n\n\n10:45-11:00\nSnack and refreshment break\n\n\n11:00-12:30\nSyntax and interpretation of output for LPA enumeration across variance-covariance structures\n\n\n12:30-1:30\nLunch break\n\n\n1:30-3:15\nIndividual consultation & Practice of LPA enumeration process\n\n\n3:15-3:30\nSnack and refreshment break\n\n\n3:30-5:00\nIndividual consultation & Review of multinomial logistic regression\n\n\nDay 3\n\n \n\n\n9:00-9:30\nReview of LPA enumeration process and decision-making\n\n\n9:30-10:45\nExamination of Profile homogeneity and separation\n\n\n10:45-11:00\nSnack and refreshment break\n\n\n11:00-12:30\nIntroduction to latent class regression (LCR) with inclusion of predictive covariates\n\n\n12:30-1:30\nLunch break\n\n\n1:30-3:15\nLCR continued with inclusion of distal outcomes\n\n\n3:15-3:30\nSnack and refreshment break\n\n\n3:30-5:00\nIndividual consultation\n\n\nDay 4\n\n \n\n\n9:00-9:30\nInformation Coming Soon…\n\n\n9:30-10:45\nInformation Coming Soon…\n\n\n10:45-11:00\nSnack and refreshment break\n\n\n11:00-12:30\nInformation Coming Soon…\n\n\n12:30-1:30\nLunch break\n\n\n1:30-3:15\nInformation Coming Soon…\n\n\n3:15-3:30\nSnack and refreshment break\n\n\n3:30-5:00\nIndividual consultation\n\n\n\n\n\nDownload Sample Slides and Preview Course Video\nPlease fill out and submit the form below to get instant access to sample course materials.
URL:https://www.statscamp.org/courses/latent-profile-analysis/
LOCATION:Livestream and/or Asynchronous:\, If you are unavailable to join live via Zoom\, you can participate asynchronously by viewing the recorded course videos for up to 1 year.
CATEGORIES:Latent Profile Analysis,Winter Camp
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