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Lauren Wallar

Lauren Waller

Lauren is a PhD student in the Department of Population Medicine at the University of Guelph in Ontario, Canada. She completed her Bachelor of Science in 2010 and Master of Science in 2012 at McMaster University in Hamilton, Ontario. After completing her Master of Science, she returned to her hometown of Guelph, Ontario to begin her PhD studies in September 2012 with Dr. Andrew Papadopoulos.

Outside of school, Lauren enjoys baking delicious goodies, (fair-weather) running, and spending time with family and friends including her 100-pound South African Boerboel, Maggie. ) Lauren is interested in enhancing public health human resources capacity through educational development. Over the past ten years, many Canadian universities have developed Master of Public Health programs to increase the effectiveness of the public health workforce. However, their desirability and impact has not been formally evaluated. Using Sawtooth Software’s Adaptive Choice-based Analysis and Latent Class Analysis, Lauren will determine student and employer preferences for Master of Public Health program characteristics. This is part of a larger project which seeks to evaluate Master of Public Health programs and their impact on meeting public health needs. In a second project, Lauren will determine the effectiveness of case studies in teaching conjoint analysis to Master of Public Health students. Using Sawtooth Software’s MaxDiff, she will generate a case study in which community wellbeing priorities are determined. This case study will be used as a tool to educate Master of Public Health students on the potential use of conjoint analysis and its related techniques in public health practice.

To contact Lauren, please e-mail her at This email address is being protected from spambots. You need JavaScript enabled to view it.. You can view her Student Profile at https://www.uoguelph.ca/graduatestudies/Profiles/Lauren_Wallar

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Lighthouse Studio

Lighthouse Studio is our flagship software for producing and analyzing online and offline surveys. It contains modules for general interviewing, choice-based conjoint, adaptive choice-based conjoint, adaptive choice analysis, choice-value analysis, and maxdiff exercises.

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