CV

Adam C. Garber

Email |

R course materials | https://garberadamc.github.io/project-site/

EDUCATION

Doctoral Student (September 2015 – Present)
Education, Emphases in Quantitative Methods & Cognitive Science
University of California, Santa Barbara
Advisor: Dr. Karen Nylund-Gibson

Master of Arts (May 2019)
University of California, Santa Barbara
Education, Special Education

Bachelor of Arts (May, 2011)
University of California, Santa Cruz
Psychology

TEACHING EXPERIENCE

Graduate Teaching Assistant (Spring, 2020)
ED 216C: Structural Equation Modeling; Dr. Nylund-Gibson
University of California, Santa Barbara

Graduate Teaching Assistant (Winter, 2020)
ED 216B: Factor Analysis; Dr. Nylund-Gibson
University of California, Santa Barbara

Graduate Teaching Assistant (Fall, 2019)
ED 216G: Applied Mixture Modeling; Dr. Nylund-Gibson
University of California, Santa Barbara

Graduate Teaching Assistant (Spring, 2019)
ED 214C: Linear Statistical Models for Data Analysis; Dr. Nylund-Gibson
University of California, Santa Barbara

Teaching Assistant (Summer, 2017)
INT95: Freshman Summer Start Program (FSSP); Dr. Ralph Gallucci
University of California, Santa Barbara

WORKSHOPS

Teaching Assistant (Winter, 2019)
Professional Development Mini-Course: Introduction to Latent Transition Analysis.
AERA Annual Meeting Toronto, Canada

Teaching Assistant (Summer, 2019)
Professional Development Intensive Two Day Course: Introduction to Latent Transition Analysis.
Methods U, GGSE, University of California, Santa Barbara

ACADEMIC WORK EXPERIENCE

ACADEMIC APPOINTMENTS

Graduate Student Researcher, Implicit Bias Study (2020 – Present)
Position: Hosted by Westmont College (50% appointment)
Principal Investigator: Dr. Carmel Saad

Graduate Statistics Support Peer (2019 – 20)
Position: Hosted by Gervitz Graduate School of Education (25% appointment)

Graduate Student Researcher (2016 – 2017)
Position: Hosted by Department of Chemical Engineering (50% appointment)
Principal Investigator: Dr. Michael Gerber (University of California, Santa Barbara)

Cognitive Research Assistant (2011)
Principal Investigator: Professor Alan H Kawamoto
University of California, Santa Cruz

GRANT WRITING EXPERIENCE

Grant Writing Research Assistant (2020)
Investigator: Nylund-Gibson
Applied Mixture Modeling Training Workshops and Resources for Education Researchers
To be submitted to Institute of Education Sciences. (in progress)

Grant Writing Research Assistant (2019)
Investigator: Nylund-Gibson
Applied Mixture Modeling Training Workshops and Resources for Education Researchers
Submitted to Institute of Education Sciences (IES).

Grant Writing Research Assistant (2015)
Investigator: Wang & Singer
A comparative study of patterns of family support for children with developmental disabilities:
Similarities and differences in U.S. and China. Submitted to Department of Education.

PRESENTATIONS

Garber, A. & Nylund-Gibson, K. L. (2021) Structural Invariance in Multigroup Latent Class Analysis: Perception of Disability Status and Academic Expectations [Symposium]. AERA Annual Meeting (virtual)

Garber, A., Wang, M. & Nylund-Gibson, K. L. (2021) Typologies of Autism: The Utility of Latent Class Analysis to Understand Heterogeneity in Social Responsiveness [Symposium]. AERA Annual Meeting (virtual)

Garber, A. & Nylund-Gibson, K. L. (2020) Structural Invariance in Multigroup Latent Class Analysis: Perception of Disability Status and Academic Expectations. GGSE Interdisciplinary Research Symposium Santa Barbara, CA.

Garber, A. & Nylund-Gibson, K. L. (2020) Structural Invariance in Multigroup Latent Class Analysis: Perception of Disability Status and Academic Expectations [Symposium]. AERA Annual Meeting San Francisco, CA http://tinyurl.com/vg5nw9q (Conference Canceled)

Garber, A., Wang, M. & Nylund-Gibson, K. L. (2020) Typologies of Autism: The Utility of Latent Class Analysis to Understand Heterogeneity in Social Responsiveness [Symposium]. AERA Annual Meeting San Francisco, CA http://tinyurl.com/yx6ve9yg (Conference Canceled)

Nylund-Gibson, K. L. & Garber, A. (2020) Understanding Change in Latent Transition Analysis Models Using Auxiliary Variables [Symposium]. AERA Annual Meeting San Francisco, CA http://tinyurl.com/vuslpat (Conference Canceled)

Carter, D., Garber, A., Nylund-Gibson, K. L., Dowdy, E. & Furlong, M. J. (2020) Understanding Patterns of Social-Emotional Strengths Across Students With and Without Disabilities: Different, Not Worse [Symposium]. AERA Annual Meeting San Francisco, CA http://tinyurl.com/qlyypv5 (Conference Canceled)

Garber, A. & Nylund-Gibson, K. L. (2019) Conditional Mediation in Latent Class Analysis [Symposium]. AERA Annual Meeting Toronto, Canada

Garber, A. & Wang, M. (2017) Responsive Early Education and Intervention: A Call for School and Family Collaboration [Poster]. CEC Annual Meeting Boston, MA

PUBLICATIONS

Felix, E.D., Afifi, T., Horan, S. M., Meskunas, H., & Garber, A. (2020). Why family communication matters: The role of co-rumination and topic avoidance in understanding post-disaster mental health.

Nylund-Gibson, K., Garber, A., Carter, D., Simon, O., Whaling, K., Arch, D., Chan, M., Lawrie, S., and Tartt, E. (in progress) Ten Frequently Asked Questions about Latent Transition Analysis (LTA).

Nylund-Gibson, K., Garber, A., Nishina, A., Bellmore, A., Witkow, M., Singh, J. (in progress). The Utility of Latent Class Analysis to Understand Heterogeneity in Youth Coping Strategies: A Methodological Introduction.

Denson, N., Ing, M., Nylund-Gibson, K., Garber, A., Whaling, K., Chan, M., Carter, D., Arch, D. (in progress). Interactions with Diversity in Higher Education: A Latent Class Analysis.

WORK EXPERIENCE

Behavioral Clinician (June 2016 – 2020) Koegel Autism Center University of California, Santa Barbara

Behavioral Clinician (September 2014 – June 2017) Holdsambeck & Associates
Santa Barbara, CA

Behavioral Clinician (May 2014 – December 2014) Trumpet Behavioral Health
Santa Barbara, CA

Mental Health Worker (February 2010 – January 2011)
7th Avenue Center: Mental Health Hospital Santa Cruz, CA

ACADEMIC PROJECTS

Website: Tidy Workflow with MplusAutomation
Teaching materials & tutorials in advanced quantitative methods taught with R programming language:
https://garberadamc.github.io/project-site/

SKILLS

COURSES

GRADUATE LEVEL COURSES

Quantitative Causal Inference, Political Methodology (PS 207) • Applied Econometrics (ESM 246) • Introduction to environmental data analysis & stats in R (ESM 206) • Advanced Research Methods & Statistics in Linguistics (LING 202) • Applied Mixture Models (ED 201F) • Structural Equation Modeling (ED 216F) • Factor Analysis (ED 216B) • Advanced Multivariate Statistics (ED 216 A) • Introduction to Statistics (ED 214A) • Inferential Statistics (214B) • Linear Statistics (ED 214C)

Qualitative Research Methods (ED 221A) • Constructing Measures (ED 217A) • Analyzing and Validating Measures (ED 217B) • Language as Culture (LING 227) • Cultural Psychology (ED 201F) • Anthropological Perspectives on Education (ED 205) • Neuroscience (PSYCH 211) • Behavioral Neuroendocrinology (PSYCH 235) • Teaching Psychology (PSYCH 590A) • Advances in the Learning Sciences (210A) • Classroom Ethnography (ED 221B) • Cognitive Perspectives on Achievement Motivation (ED 209I) • Cognitive Science, Spatial Cognition (INT 201A) • Cognitive Science & Similarity (INT 201B) • Cognitive Science and the Humanities: Bridging the Divide (INT 201C)

Special Education Law (ED 222D) • Cognitive Development in Autism and Other Severe Disabilities (CNCSP 212) • Cognitive Assessment in Professional Psychology (CNCSP 250) • Behavioral Assessment and Intervention for Children and Adolescents (CNCSP 256) • Academic and Cognitive Characteristics of Students with Mild Disabilities (ED 222B) • Professional Issues in Severe Developmental Disabilities (ED 291) • Social and Affective Characteristics of Children with Learning Disabilities (ED 222C) • Single Case Experimental Design (ED 201D) • Exceptional Children (ED 222A)

AUDITED COURSES

Causal Inference for Social Science (PS 207) • Introduction to Multilevel Modeling (UCLA; PSYCH256A) • Advanced Methods for Environmental Data Analysis in R (ESM 244) • Bayesian Statistics (PSTAT 115) • Introduction to Machine Learning (PSTAT 231) • Machine Learning (CS 165B) • Survey Design & Environmental Public Opinion (ESM 218) • Computational Neuroscience (PSYCH 265)