Quantitative Research Collaboratory
The Quantitative Research Collaboratory (QRClab) is a team of researchers working on projects which improve and expand quantitative methods and research practices in psychology (and related) research. Projects in the lab focus on implementation and analysis of repeated-measures design, open science practices, meta-science, and computational statistics (e.g., bootstrapping). New projects on new topics are always welcome!
The QRClab is seeking graduate students and undergraduates to contribute to the research in this lab. Students will begin on a collaborative project with direct contact with the Principal Investigator, and transition to greater independence as experience and desire dictate.
Congratulations to Valerie Polad! She is an incoming PhD candidate at The University of North Carolina, Chapel Hill.
Congratulations to graduate student Tritan Tibbe for being awarded the NSF Grant! Learn more about the NSF grant here.
Congratulations Nickie Yang who is joining the UCLA B.I.G. program! Learm more about B.I.G. here.
Congratulations Valerie Polad! She presented her research at the Electronic Undergraduate Statistics Research Conference. Learn more about Reducing Carry Over Effects in Within-Subjects Designs here!
Research from the QRClab was recently featured on Season 2 Episode 1 of Quantitude: The Podcast. Honors student Kathleen Lamarque-Navarrete's research in collaboration with Dr. Jennifer Sumner, explores the use of propensity scores in recruitment of participants for cohort studies.
Congratulations QRC Research Assistant, Kathleen Lamarque-Navarrete, who has been accepted into the Departmental Honors program in Psychology!
Congratulations Charlotte Huang who won the 2020 UCLA Library Prize in Science, Engineering, and Math!
QRClab members, Valerie Polad and Zach Loran, presented their research at the 2020 Undergraduate Research Week!
Congratulations Valerie Polad! Newest QRClab member as part of the PROPS program. Learn more about PROPS here.
Graduate Students: Please email me if you are interested in getting involved in the lab. I will be accepting applications for PhD students for Fall 2022. GREs are optional for admissions to the PhD program at UCLA for Fall 2022. Quantitative psychology is by definition very reliant on quantitative skill sets which can be demonstrated in a number of ways: performance in mathematics courses, performance on the quantitative section of the GRE, and/or letters of recommendation speaking to your quantitative expertise. When reading applications we will look for demonstrated ability in quantitative skills, but this should not require a GRE score if other parts of your application speak to these skills. If you are unsure whether you should or should not include GRE scores in your application to UCLA, please feel free to contact me. See the Department Website for more information about the application process.
Current Graduate Students
Jessica Fossum - 3rd year PhD Student
Jessica is a second-year graduate student at UCLA in the Department of Psychology — Quantitative Area, advised by Dr. Amanda K. Montoya. She graduated with a B.A. in Psychology and a B.S. in Applied Mathematics from Seattle Pacific University in 2019. She is particularly interested in statistical power and how it is determined in moderation, mediation, and moderated mediation models.
Tristan Tibbe - 3rd year PhD Student
Tristan is a second-year graduate student in the Quantitative Area of the Psychology Department at UCLA. He received a Bachelor of Science Degree with majors in Psychology and Mathematics and minors in Statistics and Spanish from Central Michigan University in 2018. He is currently interested in investigating and applying statistical methods to promote open science and enhance replicability.
Alondra Cruz - 1st year PhD Student
Alondra is a first-year graduate student at UCLA in the Department of Psychology — Quantitative Area, advised by Dr. Amanda K. Montoya. She graduated with a B.S. in Psychology from Arizona State University in 2020. She is particularly interested in causal inference approaches to mediation analysis and implementation of missing data approaches in mediation analysis.
Carolyn Moor (Statistics)
Nickie Yang (Psychobiology)
Erika Garcia Ruiz (Psychobiology)
Yuhan Mei (Communications, Psychology)
Kevin Le (Cognitive Sciences, Class of 2020) LinkedIn
Anjum Farook (Psychology, Class of 2020) LinkedIn
Zach Loran (Statistics, Geography, Class of 2021)
Yihuan (Charlotte) Huang (Applied Mathematics, Cognitive Sciences, Class of 2021)
Kat Lamarque-Navarrete (Psychology, Class of 2021) LinkedIn