Amanda Kay Montoya

Amanda Kay Montoya is an Associate Professor in the Quantitative Psychology area of the Department of Psychology at UCLA. She received her PhD in Quantitative Psychology from The Ohio State University in 2018 under the supervision of Dr. Andrew Hayes. Her research focuses on improving statistical methodology in psychological science, with particular expertise in mediation, moderation, and conditional process analysis.

Dr. Montoya's educational background includes:

• B.S. in Psychology with minor in Mathematics from University of Washington (2013)
• M.A. in Psychology and M.S. in Statistics from Ohio State University (2016)
• Ph.D. in Quantitative Psychology from Ohio State University (2018)

Her research program centers on developing and improving statistical methods for psychological research, with particular focus on mediation and moderation analysis in various experimental designs. She has made significant contributions to understanding how to properly conduct and interpret mediation analyses, especially in within-subject designs. Beyond methodological development, she is also interested in meta-science issues including research practices that affect replicability and addressing inequities in STEM education for women.

Dr. Montoya's publications demonstrate a clear trajectory of advancing methodological approaches in psychological science, with recent work spanning from foundational methodological papers on mediation analysis to applied studies examining weight stigma. Her research has been funded by prestigious organizations including NSF and NIH.

Her scientific awards include:

• NSF Graduate Research Fellow

Dr. Montoya actively mentors graduate students in the Quantitative Psychology program at UCLA and teaches several statistics courses including Psychological Statistics (Psych 100A), Advanced Psychological Statistics - Regression Analysis (Psych 250C), and Mediation, Moderation, and Conditional Process Analysis (Psych 254B). Her research has been supported by NSF, NIH, and internal UCLA grants. She runs the Mechanisms and Contingencies Lab (MAC lab) which focuses on developing and applying advanced statistical methods to psychological research questions.

She is an active presenter at major conferences, with upcoming workshops scheduled in 2024 on mediation and moderation analysis for both between-subjects and within-subject designs.