Scientific Software International (SSI) publishes statistical data analysis software: LISREL (structural equation model/SEM, survey generalized linear model/SGLIM), 
HLM (hierarchical linear modeling, multilevel model), SuperMix (mixed models, mixed-effects program, MIXREG, MIXOR, MIXNO and MIXPREG) and Item Response Theory/IRT (BILOG-MG, MULTILOG, PARSCALE)Scientific Software International (SSI) publishes statistical data analysis software: LISREL (structural equation model/SEM, survey generalized linear model/SGLIM), 
HLM (hierarchical linear modeling, multilevel model), SuperMix (mixed models, mixed-effects program, MIXREG, MIXOR, MIXNO and MIXPREG) and Item Response Theory/IRT (BILOG-MG, MULTILOG, PARSCALE)Scientific Software International (SSI) publishes statistical data analysis software: LISREL (structural equation model/SEM, survey generalized linear model/SGLIM), 
HLM (hierarchical linear modeling, multilevel model), SuperMix (mixed models, mixed-effects program, MIXREG, MIXOR, MIXNO and MIXPREG) and Item Response Theory/IRT (BILOG-MG, MULTILOG, PARSCALE)

L  LISREL Fall workshop

Structural Equation Modeling with LISREL: A First Course

Dates: Not scheduled for 2011.
Instructors: Gregory Hancock (Ralph O. Mueller had to withdraw in August 2010 due to a conflict.)

This first course serves as an introduction to structural equation modeling (SEM) and, thus, is primarily intended for new users of LISREL. Building on participants' familiarity with multiple linear regression, the presenters will establish the purpose, language, and flexibility of SEM and the LISREL software. Measured variable path analysis, confirmatory factor analysis (and related topics such as construct validity/reliability), and latent variable path analysis will be sequentially introduced. The workshop will also include discussions on multi-group analyses and practical guidelines on how to present SEM results in substantive manuscripts. Throughout, participants will become familiar with the SIMPLIS command language of the LISREL software through annotated examples and hands-on exercises.

Each participant will receive the latest LISREL for Windows student CD and presentation handouts. Participants are strongly encouraged to bring a laptop computer to complete the hands-on exercises. The only prerequisite for participation is a working knowledge of multiple linear regression and an interest to explore SEM with LISREL as a multi-faceted, flexible tool for the testing of a priori theories hypothesized to underlie correlational data.

L  LISREL workshop - Fall session schedule (Not scheduled for 2011)

Day 1

  9:00 - 10:30

Introduction and Overview: Background, terminology and notation, general description of SEM, statistical reminders

10:30 - 10:50 Break- refreshments provided
10:50 - 12:20

Measured Variable Path Analysis (MVPA) I: Standardized MVPA

12:20 -   1:40 Buffet luncheon
  1:40 -   3:10

Measured Variable Path Analysis II: Unstandardized MVPA

  3:10 -   3:30 Break- refreshments provided
  3:30 -   5:00

Measured Variable Path Analysis III: Model identification, parameter estimation, data-model fit assessment, model comparisons)

 Day 2
  9:00 - 10:30

Confirmatory Factor Analysis (CFA): Incorporating latent variables, parameter estimation, data-model fit

10:30 - 10:50 Break- refreshments provided
10:50 - 12:20

Construct Validity and Reliability: Maximal reliability, multitrait-multimethod analysis

12:20 -   1:40 Buffet luncheon
  1:40 -   3:10 Second-Order Factor Models
  3:10 -   3:30 Break- refreshments provided
  3:30 -   5:00

Latent Variable Path Analysis (LVPA): Structural relations among latent variables, model re-specifications, two-phase SEM process

 Day 3
  9:00 - 10:30

Multi-Group Analyses: Comparing groups on MVPA, CFA, and LVPA models

10:30 - 10:50 Break- refreshments provided
10:50 - 12:20

Reality Check
Getting practical: Communicating SEM results

12:20 -   1:40 Buffet luncheon
  1:40 -   3:00

SEM with ordinal variables (SSI Staff)

  3:00 -   3:15 Break- refreshments provided
  3:15 -   4:30

SEM with ordinal variables (SSI staff)

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