An Applied Structural Equation Modeling Intensive

Organization: University of Colorado College of Nursing

Venue: University of Colorado College of Nursing

Location: Aurora, Colorado, United States

Event Date/Time: Jun 18, 2013 / 8:00 am - (MST) End Date/Time: Jun 21, 2013 / 2:30 pm - (MST)
Registration Date: Jun 17, 2013 Time: 00:00:00 - (MST)
Early Registration Date: May 15, 2013 Time: 00:00:00 - (MST)
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Description

Overview

Nursing and other health science researchers are using new models for measurement with new programs for data analysis.  This three day intensive will provide in-depth instruction on how to apply Structural Equation Modeling (SEM) to health science research.  The content is designed for researchers who are using SEM and seeking to improve their skills in its application, and also those new to SEM.   An optional session for individual consultation with the course faculty will be available on the fourth day (separate additional fee applies).  Attendees choosing this optional day need to bring their own research data to use in the consultation.

 

Target Audience

This conference will be of interest to nurse researchers, PhD students, post-doctoral fellows and other health and behavioral science researchers who are interested in using Structural Equation Modeling (SEM) in their research.

 

Continuing Education Credit 

The University of Colorado College of Nursing is an accredited provider of continuing nursing education by the Colorado Nurses Association, an accredited approver by the American Nurses Credentialing Center's Commission on Accreditation. This educational activity for 21.0 nursing contact hours is provided by the University of Colorado College of Nursing.

Venue

13120 E. 19th Avenue
Aurora
Colorado
United States
MORE INFO ON THIS VENUE

Organizations

University of Colorado College of Nursing
13120 E. 19th Avenue
Aurora
Colorado
80045
United States

Conference Speakers

CU College of Nursing Course Faculty

Karen H. Sousa, PhD, RN, FAAN   Dr. Sousa is a Professor and Associate Dean for Research and Scholarship at the CON.  As an outcomes researcher, she promotes Structural Equation Modeling as a method for cluster analysis, instrument development, and theory confirmation and construct validation.  Her research focus area is the determinants of HRQOL. 

Paul Cook, PhD   Dr. Cook is a licensed psychologist with 15 years of experience in data analysis and has taught multivariate statistics and quantitative methods at the graduate/PhD level since 2000. He provides consultation to doctoral students on the statistical aspects of their research through his role as the Director of the College of Nursing Center for Nursing Research.

Sarah Schmiege, PhD  Dr. Schmiege is an Assistant Professor in the Department of Biostatistics and Informatics and serves as the statistician for the CON.  She has collaborated wtih faculty as the lead statistician on several grants.  She has consulted extensively on topics related to SEM and has experience applying it across a range of health-related studies.    

Additional Information

Course Objectives: At the end of this educational program, participants should be able to:

 

  • Define structural equation modeling (SEM) and it's language
  • Determine research questions that are appropriate for SEM
  • Review regression analysis and its relationship to SEM
  • Interpret structural equation models
  • Practice both exploratory and confirmatory factor analysis
  • Practice the use of AMOS and MPlus in the estimation of models

 

Course Agenda: 

Tuesday June 18th, 8:30 am - 5:00 pm

  • Introduction to Structural Equation Modeling
  • Review of Regression Analysis

Wednesday  June 19th, 8:00 am  - 5:00 pm

  • Exploratory and Confirmatory Factor Analysis

Thursday June 20th, 8:00 am - 5:00 pm

  • Integrating Concepts to Research Topics
  • Special Topics:
    • Mediation Analysis
    • Longitudinal Growth Curve Modeling

Friday June 21st, 8:30 am - 2:30 pm      Individual Project Consultation - Spaces are Limited!

This special additional session requires payment of a separate fee of $300.00.  Participants should bring their research data with them if they choose this option.