ANNOUNCE: Mplus COURSE in the UK (Multilevel Analysis with Latent Variables)
Bengt and Linda Muthen will present a one-day course on
Multilevel Analysis with Latent Variables using Mplus
at the Institute of Education in London on the 4th December 2007
This one-day short course gives an overview of multilevel analysis
opportunities using the Mplus program (www.statmodel.com). New modeling
features in the upcoming Version 5 of Mplus will be discussed. Mplus goes
beyond analysis capabilities in conventional multilevel software, providing
several unique features of interest to the applied analyst. Starting with
conventional multilevel regression and growth modeling, the course will
discuss methods for multilevel analysis of exploratory and confirmatory
factor models, mediational models, structural equation models, regression
mixture models, latent class models, latent transition models, and growth
mixture models. Mplus input setups are provided for a variety of examples
and Mplus output is used for interpretation of analysis results.
Venue: The workshop will be held at the Institute of Education,
University of London, 20 Bedford Way, London, WC1H 0AL
and is hosted by the Centre for Longitudinal Studies (CLS).
Format: The course is in lecture format with no need for computer analyses.
Cost: £60 (including morning coffee/lunch/afternoon tea)
Booking a place
A workshop flyer with full details of the course and a
booking form are available now from the CLS website at IoE:
http://www.cls.ioe.ac.uk website - See under the Events section.
For further details contact:
Lorna Hardy
Tel: 020 7612 6861
email:[log in to unmask]
A more extended description appears below:
Course Summary: This one-day workshop discusses advances in multilevel
latent variables modelling made possible by the general modelling framework
of the Mplus program (www.statmodel.com). The generality of the Mplus
framework comes from the unique use of both continuous and categorical
latent variables. While continuous latent variables have seen frequent use
in factor analysis structural equation modelling, and random effects growth
modelling, modelling that includes categorical latent variables is less
widespread. Starting with more traditional multilevel models, the workshop
discusses models that use categorical latent variables, either alone or
together with continuous latent variables. The theme is the use of
categorical latent variables to represent latent classes corresponding to
different groups of individuals and latent trajectory classes corresponding
to different types of development.
Learning Outcomes: The aim of the workshop is to give an overview of
conventional and new techniques. For each topic, issues of model
specification, estimation, testing and model modification are discussed.
Several examples are examined. Modelling strategies are presented. Mplus
input setups are provided and Mplus output is used for interpretation of
analysis results.
Topics Covered:
Cross-sectional models;
Complex survey data analysis
Two-level regression
Two-level regression mixture analysis
Two-level complier-average causal effect analysis for randomized trials
Two-level path analysis
Two-level factor analysis
Two-level structural equation modelling
Two-level latent class analysis
Longitudinal models
Growth modelling with random effects
Two-level growth modelling (3-level analysis)
Growth mixture modelling
Two-level growth mixture modelling
Two-level latent transition analysis
Latent class variables on level 1 and level 2
Target Audience: Statisticians and quantitative researchers with an
interest in the analysis of hierarchically structured data. The course will
not assume a high level of statistical knowledge, but participants should
be familiar with the application and interpretation of multiple regression
analysis.
Knowledge Assumed: Prerequisites: Intermediate understanding of latent
variable modelling and multilevel modelling and familiarity with
categorical data analysis, especially logistic regression.
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