Doctoral Degrees

Department of Human Development and Family Studies > Academics > Graduate >

Doctorate

Doctor of Philosophy in Human Development and Family Studies

Human Development and Family Studies is the interdisciplinary study of individuals and relationships across the lifespan in diverse contexts of families, communities, and cultures. Ph.D. candidates are prepared to transform the human experience through applied research rooted in social justice.

Doctoral students collaborate with faculty mentors in experiences related to applied research, developing a focal area of scholarship. Each student completes rigorous course work, including research methodology, comprehensive exams, and the dissertation. Student achievements are documented in a professional portfolio throughout the doctoral program.

The Doctor of Philosophy Degree in Human Development and Family Studies offers three concentrations from which students may choose.

Child Development

Students earning a doctorate in Child Development complete a rigorous set of experiences in preparation for a research career in a university academic environment, research organization, or similar settings.

Learn More

Couple and Family Therapy

Our COAMFTE-accredited Couple and Family Therapy Ph.D. program focuses on relational processes, empirically supported interventions, and clinical research methodology.

Learn More

Diversity, Youth and Family Development

Join a nationally known, diverse community of scholars exploring child/adolescent development, culture, gender, sexuality and families.

Learn More

Learning Goals

The Learning Goals of the HDFS Ph.D. provide a focus for each student’s training. Each student crafts their own focus and has choices in the course work, research, and other learning experiences, as they work to meet the common learning goals.

Use foundational and contemporary theoretical frameworks, relevant to the study of individuals and families in context, to explain developmental and/or change processes.

Construct (organize, make sense of) and critically evaluate the body of empirical knowledge for a field/topic of study to identify gaps and justify new directions.

Critically analyze and make sound methodological decisions, implement a research study, and defend choices.

Demonstrate effective written and oral communication to disseminate information to a scholarly audience, integrating theory, empirical knowledge, and research methods as appropriate.

Demonstrate effective teaching, including instructional design and implementation.

Use HDFS theory and research to address real-world problems in practice, programming, or policy.

Demonstrate ethical behavior in all aspects of scholarship and articulate understanding of ethical issues in research, teaching, and practice.

Articulate an understanding of positionality, and describe approaches to diversity, equity, and inclusion relevant to research, teaching, practice, and policy.

Choosing a faculty member

Choosing a faculty member to work with during your scholarly career is one of the most important decisions you will make. Below are the faculty accepting graduate students. All faculty are available to you regardless of concentration, so we encourage you to learn more about our faculty and who might best support your interests and objectives. 

Doctoral Degree Adviser

An intake adviser is designated to counsel you during the first semester. You should select a permanent academic adviser before the completion of two semesters of study. The faculty member who guides the dissertation may be either the academic adviser or another member of the committee. The intake adviser often becomes the permanent adviser, but you have the option to select an alternative.

Doctoral Degree Committee

A Ph.D. program of study is planned by you and a committee composed of at least four Michigan State University regular faculty members, one of whom is designated as a major professor. The Ph.D. committee is appointed to direct your work and its membership must be approved by the Graduate Program Director. For additional details on related University policy, see the Academic Programs Catalog.

Methods Training

Our department offers a variety of advanced methods courses and other learning opportunities for graduate students to prepare them to be critical consumers and ethical producers of rigorous research. Our faculty have expertise in advanced research design and statistical methods in applied research settings. Our methods training program reflects this applied focus by helping students apply advanced statistical techniques to real-world scientific questions.

HDFS 880: Research Design and Measurement

HDFS 881: Quantitative Research Methods

HDFS 960: Applied Multivariate Data Analysis

HDFS 961: Applied Structural Equation Modeling

HDFS 962: Longitudinal Structural Equation Modeling

HDFS 892: Measurement

See MSU Course Descriptions to learn more about each course and their prerequisites and then link to https://reg.msu.edu/Courses/Search.aspx

For non-HDFS students interested in enrolling, please contact us at: HDFS.methods@hdfs.msu.edu

Dr. Ryan P. Bowles is an expert in Rasch measurement, Item Response Theory, and Structural Equation Modeling with categorical outcomes. His research focuses on the assessment of early childhood language and literacy development. Dr. Bowles teaches Quantitative Research Methods, Applied Multivariate Data Analysis, Applied SEM, Longitudinal SEM, and Measurement.

Dr. Ahnalee Brincks specializes in latent variable modeling and has expertise in longitudinal data analysis, hierarchical linear models, structural equation modeling, and the analysis of data from randomized clinical trials.

Dr. Megan Maas specializes in latent class methodologies, longitudinal survey research, and dyadic data analysis to understand sexual behaviors, how online and offline sexual behaviors change over time, and how partners in intimate relationships affect one another. Dr. Maas teaches Research Design and Measurement and Quantitative Research Methods.

Dr. Amy K. Nuttall is an expert in structural equation modeling (SEM), longitudinal data analysis (LSEM), and mixture modeling. She employs these methods in longitudinal data (including intensive longitudinal “diary” sampling), family/dyadic data, and biological data to understand the impact of family processes and dynamics on development over time. Dr. Nuttall teaches Applied Multivariate Data Analysis, Applied SEM, and Longitudinal SEM.

Dr. Yijie Wang’s research employs experience sampling and longitudinal designs to understand development in daily lives and over time. Her work also uses secondary data from nationally representative samples such as the National Longitudinal Study of Adolescent to Adult Health (Add Health) and the Early Childhood Longitudinal Study (ECLS). Dr. Wang teaches Applied Multivariate Data Analysis.

Graduate

Your Next Step

Apply