Hierarchical Models

Anna Björklund

Senior Data Science Fellow 2024-2025, Data Science Fellow 2023-2024
Linguistics

I am a fifth-year PhD student in the Department of Linguistics with an areal interest in the Wintuan languages, traditionally spoken in the northern Sacramento Valley and now undergoing revitalization. My primary research interests are in leveraging archival recordings for the phonetic analysis of these under-documented languages, as well as designing tools to assist in their revitalization. I have worked as a linguistic consultant for the Paskenta Band of Nomlaki Indians since 2020 and the Wintu Tribe of Northern California since 2022. I received my MA in linguistics from UC...

Anusha Bishop

Availability: By appointment only

Consulting Areas: Python, R, Cloud & HPC Computing, Data Sources, Data Visualization, Geospatial Data, Maps & Analysis, Machine Learning, Research Design, Cluster analysis, Experimental design, Hierarchical Models, High dimensional statistics, Means Tests, Nonparametric methods, Regression Analysis, Software Output Interpretation, Spatial statistics, Bash or Command Line, Excel, Git or Github, RStudio

Pratik Sachdeva, Ph.D.

Data/Research Scientist, Senior Consultant, and Senior Instructor

I am staff at the Social Sciences D-Lab. I received my Ph.D. in the Physics department at Berkeley. My research lies in the realm of theoretical/computational neuroscience, which aims to use mathematical and computational tools to better understand how neural systems operate and process information. My projects include using information-theoretic techniques to study how neural variability impacts information processing in neural circuits and investigating the statistical issues that impede the interpretation of parametric models of neural activity.

Beyond research, I'm...

Sohail Khan

Data Science Fellow 2024-2025
School of Information

Hey everyone, I’m Sohail - a 1st years Master’s student studying Data Science at the I-School. I am interested in the intersection between Computer Science, Data Science, and Cognitive Psychology and using these tools to understand, discover, and drive the development of assistive technologies.

I have experience building with brain computer Interfaces, developing distributed data processing applications, and am currently working on a large scale archival project aimed at preserving the history and memory of resistance movements through an embedding based...

Amanda Glazer

Instructor
Statistics

Amanda is a PhD candidate in the statistics department at Berkeley. Her research focuses on causal inference with applications in education, political science and sports. Previously she earned her Bachelor’s degree in mathematics and statistics, with a secondary in computer science, from Harvard.

Enrique Valencia López

Data Science Fellow
Graduate School of Education

Enrique Valencia López is a PhD student in the Policy, Politics and Leadership cluster at the Graduate School of Education.His research interests relate to three broad areas: the stratification of education by gender, immigration status and ethnicity; the measurement of teacher working conditions and well-being; and education in Latin America.

Before coming to Berkeley, Enrique worked for Mexico’s National Institute for Educational Evaluation and Assessment (INEE) in both the Policy and Indicators area. During that time, he co-authored Mexico’s first report on the educational...

Sahiba Chopra

Data Science Fellow 2024-2025
Haas

I'm a PhD student in the Management and Organizations (Macro) group at Berkeley Haas. I have a diverse professional background, primarily as a data scientist across numerous industries, including fintech, cleantech, and media. I hold a BA in Economics from the University of Maryland, an MS in Applied Economics from the University of San Francisco, and an MS in Business Administration from UC Berkeley.

My research focuses on the intersection of inequality, technology, and the labor market. I am particularly interested in understanding how to reduce inequality in...

Tracy Burnett

Data Science for Social Justice Fellow 2024
Department of Environmental Science, Policy, and Management

Tracy uses qualitative methods founded in complexity theory and hierarchy theory to model the interlinked scales of coupled social-ecological systems. She conducted the majority of her research among nomads in Amdo, Tibet. She works to develop both theoretical and technological tools that support linguistic diversity and cultural resilience.

A Basic Introduction to Hierarchical Linear Modeling

March 4, 2024
Mingfeng Xue
by Mingfeng Xue. Hierarchical Linear Modeling (HLM) is an extension of linear models, which offers an approach to analyzing data structures with nested levels. This blog elucidates HLM's significance over traditional linear regression models, particularly in handling clustered data and multilevel predictors. Illustrated with an example from educational research, the blog demonstrates model implementation and interpretation steps. It showcases how HLM accommodates both independent variables from different levels and hierarchical structure data, providing insights into their impacts on the outcome variable. Recommended resources further aid readers in mastering HLM techniques.

María Martín López

Data Science Fellow
Psychology

María Martín López is a PhD student in the Cognition area within the Department of Psychology. Her research relates to cognitive computational and quantitative models of individual differences in behaviors, thoughts, and emotions. She is particularly interested in how we can create and leverage novel algorithms to understand, measure, and predict processes relating to externalizing psychopathology (e.g. impulsivity, aggression, substance use). She answers these questions using a range of computational and quantitive models including AI, NLP, SEM, time series analysis, multi-level...