Human Factors and Applied Cognition
PsychologyThe College of Humanities and Social Sciences

Patrick E McKnight

Patrick E McKnight

Patrick E McKnight

Associate Professor

Research methods and data analysis with a particular interest in measurement.

Patrick oversees MRES (Measurement, Research methodology, Evaluation, and Statistics -- pronounced “mysteries”) - a group of diverse students and faculty who work together, collaborate with others, travel internationally, and aim to improve science.  We collaborate with Google, Intel, Koch Foundation, National Geographic, Merck, among others. Patrick’s work largely focuses on applications of psychological science to content areas in medicine, psychology (usability, psychophysics, trust, purpose in life, and anxiety/depression) and methods (crowdsourcing, data validity, and scale development).  He serves on the Adisory Board of Stats.org and contributes to many scientific intiatives - commerical, military, and public domains.  Patrick and Todd Kashdan co-mentor graduate students in both MRES and the Kashdan Lab to provide a well-rounded graduate training.  Patrick’s mentorship style tends to be “hands-off” but he meets with students weekly to collaboratively write and solve problems - all via Google Hangouts.  You can find out more about Patrick by visiting his personal website.  Proudly supporting and using DataCamp for my lab and courses.  

Current Research

Methods

  • Survey design
  • Psychometric analysis of complex constructs
  • Survey design

Evaluation in Science

  • Quantification of scientific contribution
  • Evaluation of scientific impact and scientific evidence

 Measurement

  • Trust
  • Uncertainty & Decision-making
  • Purpose in life
  • Psychological flexibility

 Statistics

  • Quantifying uncertainty
  • Empirically evaluating counterfactual reasoning

Selected Publications

Please see my Google Scholar page.

Courses Taught

PSYC 611: Advanced Quantitative Methods I

PSYC 612: Advanced Quantitative Methods II

PSYC 754: Regression

PSYC 757: Bayesian Methods and Statistics

 

Education

BS Mechanical Engineering, University of Notre Dame, 1988

MA Exercise and Sports Science, University of Arizona, 1992

PhD Psychology, University of Arizona, 1997

Dissertations Supervised

Lisa Ann Alexander, Good Question? How Subtle Changes in Question Wording Alters the Interpretation of Measures That Assess the Cognitive Symptoms of Anxiety and Depression. (2017)

Samuel Monfort, Performance, Trust, and Workload in an Automation-aided Visual Search Task (2017)

Jacob S Quartuccio, Why Are Healthy Habits so Hard to Form? Is It You, or the Habit? (2017)

Simone Erchov, Reconceptualizing Trust: Defining, Modeling, and Measuring Trust (2017)

John Graybeal, Investigating the Impact of Daytime Exposure to Blue-Enriched Light and the Power of Expectancy: Modest Benefits to Arousal and Cognition (2016)

Jessica Yarbro, A Primer on Bayesian Cost-Effectiveness Methods for Health Psychologists (2016)

Daniel Blalock, High Risk, High Reward: Daily Perceptions of Social Challenge and Performance in Social Anxiety Disorder (2016)

Julius Najab, On Selection Bias Magnitudes (2013)