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DTSTART;VALUE=DATE:20230101
DTEND;VALUE=DATE:20300102
DTSTAMP:20260404T121757
CREATED:20220909T003648Z
LAST-MODIFIED:20250410T161246Z
UID:4477-1672531200-1893542399@www.statscamp.org
SUMMARY:Self-Paced: SEM Foundations & Extended Applications (Instant Download)
DESCRIPTION:Instant Asynchronous Video Download – 4-day Statistics Short Course\nDOWNLOAD SAMPLE COURSE SLIDES AND WATCH COURSE VIDEO PREVIEW\nSeminar Overview: SEM Foundations & Extended Applications\n\nDo you want to take your measurement to the latent level? Well\, this is it\, you have found it\, the foundation to what you need to know for latent variable modeling – structural equation modeling (SEM)! Most campers report their prior training was insufficient and/or outdated. We will introduce you to the current techniques and advances in SEM as well as guide you through the steps to ‘craft’ an exquisite SEM model. \n\nSeminar Topics:\n\nPhantom Constructs\nFitting measurement models\nThree methods of scale setting – including effects coding!\nUpdated recommendations for Scale Validation\nMultiple-Group Comparisons with applications for experimental and observational groups!\nFactorial/Measurement Invariance – Are you measuring the same construct?\nExtended Applications Such as Parceling and Missing Data\nMediation and Indirect Effects using Bootstrapping\nModeration\, creating latent interaction terms!\n\nSeminar Description:\nThis 4 day short course covering SEM Foundations & Extended Applications is an intensive short seminar on the principles of structural equation modeling. \n\nInstructor: Todd D. 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\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\n\nSeminar Includes:\nMaterials\, downloads\, recorded course video viewable for up to one year. \n\n\nLearning Objectives\nLearning Objectives:\nThe 4-day training institute on Structural Equation Modeling (SEM Foundations) will enable participants to: \n\nDescribe the psychometric properties that underly Structural Equation Modeling (SEM).\nDefine a latent construct using manifest variables.\nIdentify a latent construct using numerous methods of identification\, including marker method\, fixed factor\, and effects coding.\nConduct confirmatory factor analysis (CFA) and evaluate model fit using several fit indices.\nCompare CFA models using several comparison metrics.\nGenerate and implement item parceling schemes.\nEvaluate multiple groups using the CFA framework using weak and strong invariance.\nTest and compare latent parameters in a multiple group framework.\nEvaluate and address missing data with both FIML and Multiple Imputation.\nImplement a planned missing data design.\nEvaluate mediation and moderation in an SEM framework.\nEvaluate multi-trait\, multi-method (MTMM) models.\nEvaluate hierarchical models.\n\nSeminar Audience\nSeminar Audience:\nIf you need to analyze the covariance structure of multivariate data and have a basic statistical background\, 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 do not need to know matrix algebra\, calculus\, or likelihood theory (although that knowledge would be beneficial). Participants from a variety of fields\, including sociology\, psychology\, education\, human development\, marketing\, business\, biology\, medicine\, political science\, and communication\, will benefit from the seminar. \nThe seminar will support LISREL\, Mplus or Laavan. Some assistance will be available for questions related to other structural modeling packages. No previous knowledge of LISREL\, Mplus or Laavan is assumed. Furthermore\, nearly all the techniques taught in the seminar can be translated fairly easily to most other packages. \nSeminar Files\nSeminar Files\nBelow are links to seminar files for those who enrolled in the seminar. Please download these files onto your computer before the first day of the seminar. The files are password protected to respect the intellectual property rights of the instructors. By using your login information you agree not to share your login information or the content protected by it. \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\n\n1:30 – 3:15\nWelcome and Introductions. Philosophy\n\n\n3:15 – 3:30\nSnack and Refreshment Break\n\n\n3:30 – 5:00\nPsychometrics; Defining Constructs\n\n\n\n\n\n\nDay 2\n\n \n\n\n9:00 – 10:45\nIdentification & Scale setting\n\n\n10:45 – 11:00\nSnack and Refreshment Break\n\n\n11:00 – 12:30\nConfirmatory Factor Analysis I – Introduction to CFA\n\n\n12:30 – 1:30\nLunch Break\n\n\n1:30 – 3:15\nConfirmatory Factor Analysis II – Comparing Models\, Model fit\n\n\n3:15 – 3:30\nSnack and Refreshment Break\n\n\n3:30 – 5:00\nMultiple-Group CFA – Testing for invariance\n\n\n\n\n\n\nDay 3\n\n \n\n\n9:00 – 10:45\nMultiple-Group CFA – Tests and comparing latent parameters\n\n\n10:45 – 11:00\nSnack and Refreshment Break\n\n\n11:00 – 12:30\nParcels and Parceling; Missing Data & Power\n\n\n12:30 – 1:30\nLunch Break\n\n\n1:30 – 3:15\nMultiple-Group SEM & Latent Regression Models\n\n\n3:15 – 3:30\nSnack and Refreshment Break\n\n\n3:30 – 5:00\nCatch up and Discussion\n\n\n\n\n\n\nDay 4\n\n \n\n\n9:00 – 10:45\nMediators\n\n\n10:45 – 11:00\nSnack and Refreshment Break\n\n\n11:00 – 12:30\nModerators\n\n\n12:30 – 1:30\nLunch Break\n\n\n1:30 – 3:15\nInteractions Multi-Trait Multi-Method (MTMM) models\n\n\n3:15 – 3:30\nSnack and Refreshment Break\n\n\n3:30 – 5:00\nCatch up and Discussion\n\n\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/sem-foundations-and-extended-applications/
LOCATION:MT
CATEGORIES:On-Demand,SEM Foundations & Extended Applications
ATTACH;FMTTYPE=image/jpeg:https://www.statscamp.org/wp-content/uploads/2022/09/sem-foundations-training-course-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230101
DTEND;VALUE=DATE:20300102
DTSTAMP:20260404T121757
CREATED:20230825T183614Z
LAST-MODIFIED:20241114T000716Z
UID:7137-1672531200-1893542399@www.statscamp.org
SUMMARY:Self Paced: The Craft of Longitudinal Structural Equation Modeling (Instant Download)
DESCRIPTION:Dive into a transformative learning experience! Our seminar goes beyond the ordinary\, offering a dynamic series of engaging lectures and hands-on computer workshops. Elevate your skills with advanced training in Structural Equation Modeling (SEM) tailored specifically for the analysis of longitudinal data. Seize this opportunity to unlock new insights – join us and propel your expertise to the next level!\nASYNCHRONOUS – 5-day Statistics Short Course (4hrs per day)\nDOWNLOAD SAMPLE COURSE SLIDES AND WATCH COURSE VIDEO PREVIEW\nMastering Longitudinal Structural Equation Modeling: An In-Depth Workshop for Advanced Analysis \nWelcome to an immersive and advanced seminar experience! Join us for an intensive short camp focused on mastering the analysis of longitudinal data through Structural Equation Modeling (SEM). Engage in a comprehensive program featuring a blend of expert lectures and hands-on computer workshops. This unique opportunity ensures participants gain advanced proficiency in utilizing SEM for the in-depth analysis of longitudinal data. Elevate your skills—enroll now for an unparalleled learning journey! \n  \n\n\n\nDay 1\n\n \n\n\n5:00 – 6:45\nWelcome and Introductions. Overview of Longitudinal Models\n\n\n6:45 – 7:00\nSnack and Refreshment Break\n\n\n7:00 – 9:00\nReview of Foundations of SEM\n\n\n\n\n\n\nDay 2\n\n \n\n\n5:00 – 6:45\nParcels and Parceling\n\n\n6:45 – 7:00\nSnack and Refreshment Break\n\n\n7:00 – 8:00\nDesign and Measurement Issues in Longitudinal Modeling\n\n\n8:00 – 8:30\nLongitudinal Panel Models: Basics\n\n\n8:30 – 9:00\nMultiple-group Longitudinal Panel Models: CFA\, SEM\, & RI-CLPM\n\n\n\n\n\n\nDay 3\n\n \n\n\n5:00 – 6:45\nMixture Modeling\n\n\n6:45 – 7:00\nSnack and Refreshment Break\n\n\n7:00 – 8:00\nLongitudinal Mediation\n\n\n8:00 – 8:30\nIndividual Consultations\n\n\n8:30 – 9:00\nCatch up and Discussion\n\n\n\n\n\n\nDay 4\n\n \n\n\n5:00 – 6:45\nLatent Growth Curve Modeling: Basics & Multivariate and Multiple Groups\n\n\n6:45 – 7:00\nSnack and Refreshment Break\n\n\n7:00 – 8:30\nMissing Data: Planned and Unplanned\n\n\n8:30 – 9:00\nCatch up and Discussion\n\n\n\n\n\n\nDay 5\n\n \n\n\n5:00 – 6:45\nLongitudinal Moderation\n\n\n6:45 – 7:00\nSnack and Refreshment Break\n\n\n7:00 – 8:30\nCatch up and Discussion\n\n\n8:30 – 9:00\nWrap-up then Individual Consultations\n\n\n\n\n\n\n\nCourse Topics:\nDesign and measurement issues in cross-sectional and longitudinal research\, Traditional panel designs\, Overview of missing data\, Latent growth curve modeling\, Testing for Mediation and Moderation\, Multilevel and multiple group SEM\, Using Phantom Constructs\, Multiple group modeling. \nCourse Description:\nEmbark on an advanced journey of expertise with our intensive seminar focused on the nuanced analysis of longitudinal data through Structural Equation Modeling (SEM). Join a dynamic program featuring expert-led lectures and hands-on computer workshops\, meticulously designed to provide participants with unparalleled training in utilizing SEM for the comprehensive analysis of longitudinal data. Elevate your skills\, refine your approach\, and gain mastery in the craft of Longitudinal Structural Equation Modeling. Seize this opportunity to dive deep into advanced methodologies and enhance your proficiency in handling longitudinal data sets. Enroll now for a transformative learning experience at the forefront of statistical analysis. \n\nInstructor: Todd D. 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\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\n\nSeminar Includes:\nMaterials\, downloads\, recorded course video viewable for up to one year. \n\n\nLearning Objectives\nLearning Objectives:\nThis comprehensive 5-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:\nIf 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 seminar is for you. We strongly recommend that you attend our five-day intensive summer institute on SEM Foundations as a pre-requisite to taking this 5-day advanced seminar. If you have not taken the foundations Seminar\, you should have extensive experience or have taken a graduate-level seminar on SEM before enrolling. \nParticipants from a variety of fields\, including sociology\, psychology\, education\, human development\, marketing\, business\, biology\, medicine\, political science\, and communication\, will benefit from the seminar. \nSoftware and Computer Support\nSoftware and Computer Support:\nParticipants need to bring a laptop computer with Wi-Fi capabilities. \nThe seminar will support LISREL\, Mplus or Laavan. Some assistance will be available for questions related to other structural modeling packages. Previous knowledge of LISREL\, Mplus or Laavan is preferred but not required. \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.Download 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/the-craft-of-longitudinal-structural-equation-modeling-a-comprehensive-seminar/
LOCATION:MT
CATEGORIES:Longitudinal SEM,Longitudinal Structural Equation Modeling,On-Demand
ATTACH;FMTTYPE=image/jpeg:https://www.statscamp.org/wp-content/uploads/2023/08/longitudinal-structural-equation-modeling-statistics-course.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240308T120000
DTEND;TZID=America/New_York:20240311T170000
DTSTAMP:20260404T121757
CREATED:20230825T215540Z
LAST-MODIFIED:20240124T173906Z
UID:7147-1709899200-1710176400@www.statscamp.org
SUMMARY:Latent Profile Analysis
DESCRIPTION:LIVESTREAM / ASYNCHRONOUS – 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\n2024 Stats Camp: 4-Day LPA\n\n\nDay 1\nDay 1 (Friday)\n\n\n\n12:00-12:30\nWelcome and introductions\n\n\n\n12:30-1:30\nOverview of mixture modeling in a general latent variable framework\n\n\n\n1:30-1:45\nBreak\n\n\n\n1:45-3:15\nOverview of LPA Analysis Steps\n\n\n\n3:15-3:30\nBreak\n\n\n\n3:30-5:00\nMplus syntax introduction with Latent Profile Analysis (LPA) example\n\n\n\nDay 2\nDay 2 (Saturday)\n\n\n\n12:00-1:30\nLPA class enumeration across variance-covariance structures introduction\n\n\n\n1:30-1:45\nSnack and refreshment break\n\n\n\n1:45-3:15\nPractice running LPA models in Mplus\n\n\n\n3:15-3:30\nLunch break\n\n\n\n3:30-5:00\nSyntax and interpretation of output for LPA enumeration across variance-covariance structures\n\n\n\nDay 3\nDay 3 (Sunday)\n\n\n\n12:00-1:30\nMultinomial Logistic Regression Review (On Own)\n\n\n\n1:30-1:45\nSnack and refreshment break\n\n\n\n1:45-3:15\nExamination of Profile homogeneity and separation\n\n\n\n3:15-3:30\nLunch break\n\n\n\n3:30-5:00\nIndividual consultation & Practice of LPA modeling process\n\n\n\nDay 4\nDay 4 (Monday)\n\n\n\n12:00-1:30\nIntroduction to latent class regression (LCR) with inclusion of predictive covariates\n\n\n\n1:30-1:45\nSnack and refreshment break\n\n\n\n1:45-3:15\nLCR continued with inclusion of distal outcomes\n\n\n\n3:15-3:30\nLunch break\n\n\n\n3:30-5:00\nIndividual consultation\n\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-online-training/
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,Livestream
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