Pharmaceutical Sciences PhD Recruitment

CBMC 807: Molecular Foundations in Chemical Biology
Prerequisites: Students are expected to have a solid understanding of introductory organic chemistry as taught at the undergraduate level.

This course provides a review of important concepts in organic chemistry as they apply to biological research. Topics include a review of intermolecular interactions as they apply to biological structures and function, a discussion of how small molecules interact with their targets, an overview of synthetic methods that relate particularly to drug molecules, and basic strategies of drug design.

CBMC 805: Molecular Modeling
Prerequisites: None

This course provides a general introduction to the field of Molecular Modeling while providing relevant applications of theory to both academic and industrial research endeavors.

PHRS 801: Common Core in Pharmaceutical Sciences
Prerequisites: None.

This course provides an interdisciplinary environment for students from each of the four Divisional PhD programs in UNC Eshelman School of Pharmacy. Students will learn about and develop skills in topics related to the responsible conduct of research, pharmaceutical development, professional development, and independent development.

PHRS 899: Seminars in Chemical Biology
Students must register for PHRS 899 each semester of their graduate program. However, only 4 credits of PHRS 899 (2 credits for MS) may count toward the requirement for the PhD degree.  Seminars are conducted jointly with the Division of Chemical Biology and Bioorganic Chemistry in the Department of Chemistry. Attendance at all Division seminars is mandatory and two unexcused absences will result in a grade of F. As an additional component of the seminar requirements of the graduate curriculum, attendance by all students is required during a student’s Doctoral Defense. These Defense seminars are held outside of the normal seminar series.

Each student is required to present a seminar in PHRS 899 either in the student’s third year or in the beginning of his/her fourth year and will be considered in assigning the grade in PHRS 899. In this seminar, the student critically reviews the area pertinent to his/her thesis topic making sure that s/he discusses studies that include his/her group’s contributions and those of other laboratories and includes a description of the student’s ongoing studies that add to this body of research. Faculty members will evaluate the student seminar. Students receiving an overall failing evaluation on the presentation will receive an “incomplete” grade in PHRS 899 for that semester and must consult with the seminar coordinator before giving a make-up seminar at a later date.  Additionally, students receiving “incomplete” grades may be advised to seek further training in presentations. In those cases where the student’s research contains intellectual property (IP) and where disclosure risks the IP, a student can provide a comprehensive review of a different subject in medicinal chemistry. Permission to do so will require the approval of the thesis adviser and the seminar coordinator. Each seminar topic, title, summary, and research article must be approved by the student’s research adviser and seminar coordinator.  A student presenter should send the title of their seminar talk to the Graduate Program Coordinator upon request.

PHRS 991: Research in Pharmaceutical Sciences (Research Rotations)
During the first two semesters, the student conducts three ~10-week research rotation projects, each under the supervision of a different faculty member. These rotation projects are considered as course work for PHRS 991. Students select rotations from any of the CBMC Faculty. With the approval of the DDGS, students may also perform rotation projects with faculty outside the labs of the CBMC Faculty, especially when the rotation will provide training in an area that is outside of the expertise of the CBMC Faculty.

To select an adviser for each research rotation, the student should interview members of the CBMC faculty about possible projects. Prior to each rotation, the student will turn in a RESEARCH ROTATION LAB SELECTION FORM (Appendix A) to the Graduate Program Coordinator. Over the course of the first year, each student is encouraged to schedule individual interviews with all members of the CBMC faculty. Although varied slightly from year to year, the rotations usually start in late August and end in late April in the next year.

Students admitted in the fall semesters can begin their rotations the summer before. In that scenario, the student must contact the Graduate Program Coordinator at least four weeks prior to the start of the rotation. The summer rotation will be considered as one of their three required rotations. A waiver for one research rotation may be granted if a student has previously completed substantial independent research. Students seeking such a waiver must petition the DDGS, and provide information (e.g. reports, manuscripts, grant proposals, and/or letters from research advisers) about their previous research. If a student has obtained a specific fellowship to work with a CBMC faculty member, then research rotations may be optional.

During lab rotations, students are expected to work in the laboratory at least 20 hours per week. Students are fully integrated into the laboratory during their rotation projects and are involved in lab meetings and journal clubs. At the beginning and end of each rotation, the rotation adviser and student review a written or oral statement of expectations for the student’s performance in the laboratory. These discussions provide the student with the advisers’ expectations and critical comments on areas of excellence and weakness. Guidelines for the research rotations are described in the PHRS 991 syllabus.

At the end of each rotation, students will submit a written report using the Research in Pharmaceutical Sciences – Student Evaluation Form (Appendix B) to the Graduate Program Coordinator. Students will also present the results of their rotation projects to their Student Advisory Committee (SAC). The SAC committee, in consultation with the rotation adviser, will provide a brief summary and evaluation and submit a grade to the Graduate Program Coordinator and the DDGS to be entered at the end of the semester. After the third rotation, students will present the work of their rotation in the CBMC End of Year Mini-Symposium.

 The DDGS serves as the temporary advisor for the first-year students who enroll in PHRS 991. The SAC committee provides additional mentoring and consists of three CBMC faculty. The SAC is formed at the beginning of the first semester based on a student’s request and the availability of faculty members.

CHEM 701 (Introduction to Laboratory Safety)
Prerequisites: first-year graduate student status or permission of instructor

This course provides an overview of safety rules and regulations, guidance in safe laboratory practice, and creates a culture of laboratory safety.

CBMC 804A: Biochemical Foundations of Chemical Biology.
Prerequisites: CHEM 466, BIOC 505, 601, or PHCO 643; or permission of instructors.

This course covers core biochemical and molecular biology techniques, concepts, and tools used to conduct research at the interface of chemistry and biology. Topics include enzymology, characterization of drug-target interactions, mechanism-based inhibitor design, assay design and development, targeting kinases and GPCRs, biopharmaceuticals, gene therapy, nucleic-acid binding agents, information-based drugs, chemical tools to study epigenetics, harnessing biosynthetic pathways for chemical diversity, and other recent advances and techniques in drug discovery.

CBMC 804B: Foundations of Chemical Biology Journal Club.
Prerequisites: Enrollment in CBMC 804A.

This course is a series of presentations by students that run in concert with CBMC 804A.

Biology Core Course
Each student has the option to choose one 3- or 4-credit hour course on campus that is focused on biological systems or techniques.  A good starting point to find such a course is the BBSP website. Some examples include PHCO701 (Introduction to Molecular Pharmacology), BIOC706 (Biochemistry of Human Disease), GNET631 (Advanced Molecular Biology), CBIO643 (Cell Structure and Function) and CBIO893 (Advanced Cell Biology).

PHRS 802: Drug Development and Professional Skills Development
Prerequisites: None.

This course provides an interdisciplinary environment for students from each of the four Divisional PhD programs in UNC Eshelman School of Pharmacy. Students will learn about the general process of drug development and develop associated professional skills.

Elective Course: Students have the option to take one elective course of their interest. There is no requirement on the number of credit hours of the course. Students typically choose a course that provides specific skills and knowledge their thesis work needs.

PHRS 994: Research in Pharmaceutical Sciences (Thesis Research)
The students begin to register 3 credit hours PHRS 994 each semester once they have chosen the thesis adviser. Guidelines for the thesis research are described in the PHRS 994 syllabus.

This DPMP Ph.D. in Pharmaceutical Sciences track has an emphasis in pharmacoengineering, an emerging discipline that integrates engineering methods with pharmaceutical sciences. Pharmacoengineers apply the latest experimental approaches from life sciences, chemistry, and physics in conjunction with theoretical and quantitative methods from engineering, mathematics, and computer science to solve problems in medicine and drug therapies.

We believe in the importance of in-depth training of students both in pharmaceutical sciences and modern engineering, mathematics, and computer science, as well as in the conduct of original research leading to the doctoral dissertation. Thus, we have designed the curriculum to offer rigorous and comprehensive training in the key principles of pharmaceutical sciences and engineering yet maintain a high degree of flexibility for students to tailor the coursework to their specific interests suitable to their research projects.

The program is among the first of its kind in the country and is a joint effort between the UNC Eshelman School of Pharmacy’s Division of Pharmacoengineering and Molecular Pharmaceutics and the Joint Department of Biomedical Engineering at UNC-Chapel Hill and North Carolina State University.

Students work at the interface of engineering and pharmaceutical sciences to develop safer and more effective medicine and medical technologies. It provides students not only with a strong knowledge base in both pharmaceutical sciences and engineering, but also a highly interdisciplinary research experience. Students have the flexibility to work with any of more than two dozen outstanding faculty members with expertise in a variety of fields within pharmacy and engineering.

Math/Applied Math Electives

Engineering Electives

Other courses can fulfill these electives upon petition by the student and approval by the director of graduate studies or the student’s Ph.D. advisory committee.

For students admitted in even years (e.g. 2024):

• Core Courses for Students (Clinician and Non-Clinician Track)

For students admitted in odd years (e.g. 2025):

• Core Courses for Students (Clinician and Non-Clinician Track)

Pharmaceutical Policy and Economics Concentration

The Pharmaceutical Policy and Economics concentration prepares students to learn about pharmaceutical policy in the US and abroad and analyze the impact of such policy. Students learn how to select the optimal study design to answer a research question and, through research rotations and practica, gain skills in primary data collection and secondary data analysis. Students in this concentration can tailor their coursework to develop expertise in the methodologies and content of greatest interest to them.

REQUIRED COURSEWORK FOR PHARMACEUTICAL POLICY AND ECONOMICS CONCENTRATION

(* denotes that course is required for all DPOP PhD students)

STATISTICS COURSES

Students are required to take a minimum of 9 credit hours of statistical coursework. A number of departments offer statistical courses. Students are encouraged to review the following statistical series and select the series that is of greatest interest to them. Different departments teach using different statistical software programs, so students should consider this when selecting a statistical series. 

Recommended Statistics Sequence Courses:

• HPM 881. Linear Regression Models (3 credits). Permission of instructor required (with exception of HPM PhD students). Prerequisite: BIOS 600 or equivalent background in probability theory/statistics for students lacking the prerequisite. Required preparation, matrix algebra, derivatives, logs/exponentials, and Stata. This course is an introduction to linear regression models. Topics include least squares regression, multicollinearity, heteroscedasticity, autocorrelation, and hypothesis testing.
• HPM 882. Advanced Methodology for Health Policy and Management Research

 (3 credits). Prerequisite: HPM 881, or permission of the instructor. Research methodology as applied to understanding problems in health care delivery. Topics include simultaneous equation models, factor analysis, limited dependent variables, and an introduction to event history analysis.

• HPM 883. Analysis of Categorical Data (3 credits) Prerequisite: HPM 881 and HPM 882 or equivalent. This course is an introduction to the analysis of categorical data using maximum likelihood estimation (MLE) and other non-linear techniques and specification tests. Topics covered include models in which the dependent variable is not continuous, including logit, probit, censored data, two-part, and count models.

OR

• ECON 700. Basic Quantitative Techniques (3 credits) Topics from linear algebra, calculus, linear and nonlinear programming, and the theory of difference and differential equations with applications to economics. (Summer)
• ECON 770. Introduction to Econometric Theory (3 credits) Probability theory, expectation, conditional expectation, modes of convergence, limit and interchange theorems, and the asymptotics of maximum likelihood, generalized method of moments and efficient method of moments. (Fall)
• ECON 771. Econometrics (3 credits) Standard first year course in econometric theory and methods. Topics include least squares and maximum likelihood, asymptotic theory, classic inference, GMM, seemingly unrelated regression, endogeneity bias, and multi-stage least squares. (Spring)
• ECON 870. Advanced Econometrics (3 credits) ECON 870 constitutes a one-semester treatment of the fundamental theory of econometrics. Topics covered include asymptotic distribution theory, linear and nonlinear models, specification testing techniques, and simultaneous equations models. Prerequisites: ECON 770, 771, and MATH 547.

Alternative Statistics Sequence Courses:

Biostatistics

• BIOS 600. Principles of Statistical Inference (3 credits). Required preparation, knowledge of basic descriptive statistics. Major topics include elementary probability theory, probability distributions, estimation, tests of hypotheses, chi-square procedures, regression, and correlation.
• BIOS 545. Principles of Experimental Analysis (3 credits). Permission of the instructor for nonmajors. Required preparation, basic familiarity with statistical software (preferably SAS able to do multiple linear regression) and introductory biostatistics, such as BIOS 600. Continuation of BIOS 600. Analysis of experimental and observational data, including multiple regression and analysis of variance and covariance.
• BIOS 665. Analysis of Categorical Data (3 credits). Prerequisites, BIOS 545, 550, and 662; or permission of the instructor for students lacking the prerequisites. Introduction to the analysis of categorized data: rates, ratios, and proportions; relative risk and odds ratio; Cochran-Mantel-Haenszel procedure; survivorship and life table methods; linear models for categorical data. Applications in demography, epidemiology, and medicine.

SOCIOLOGY (Uses Stata)

• SOCI 708. Statistics for Sociologists (4 credits) Provides an introduction to probability theory, descriptive statistics, inferential statistics, and the algebra of expectations. Emphasis is on elements useful to research sociologists, including bivariate regression and correlation.
• SOCI 709. Linear Regression Models (4 credits) The course presents regression analysis and related techniques. The major topics are the assumptions of the regression model, dummy variables and interaction terms, outlier diagnostics, multicollinearity, specification error, heteroscedasticity and autocorrelation. The final section introduces path analysis, recursive models, and nonrecursive systems.
• SOCI 711. Analysis of Categorical Data (3 credits) Perquisite, permission of the instructor. Introduction to techniques and programs for analyzing categorical variables and nonlinear models. Special attention is given to decomposition of complex contingency tables, discriminant function analysis, Markov chains, and nonmetric multidimensional scaling.
• SOCI 717. Structural Equations with Latent Variables (3 credits) Prerequisite, SOCI 708 or permission of the instructor for students lacking the prerequisite. This course examines models sometimes referred to as LISREL models. Topics include path analysis, confirmatory factor analysis, measurement error, model identification, nonrecursive models, and multiple indicators.
• SOCI 718. Longitudinal and Multilevel Data Analysis (3 credits) Prerequisite SOCI 709 or 711. This course provides an introduction to event history analysis or survival analysis, random effects and fixed effects models for longitudinal data, multilevel models for linear and discrete multilevel data, and growth curve models.

Education (Uses SPSS)

• EDUC 710. Statistical Analysis of Educational Data I (4 credits). Studies descriptive and inferential statistics for educational research, including an introduction to fundamentals of research design and computer data analysis. (Fall & Summer)
• EDUC 784. Statistical Analysis of Educational Data II (4 credits). Prerequisite, EDUC 710 or permission of the instructor. A linear model approach to the analysis of data collected in educational settings. Topics include multiple regression, analysis of variance, and analysis of covariance, using computer packages. (Spring & Summer)
• EDUC 884. Statistical Analysis of Educational Data III (3 credits). An extension of the general linear model to analysis of educational data with multiple dependent variables, with computer applications. (Fall & Summer)
• EDUC 888. Introduction to Structural Modeling (3 credits). Introduces structural equation modeling with both observed and latent variables. Applications include confirmatory factor analysis, multiple group analyses, longitudinal analyses and multitrait-multimethod models. (Spring)

Social Work

• SOWO 916. Structural Equation Modeling (3 credits). In this course, students will learn fundamental concepts and skills to conduct structural equation modeling and will learn how to apply these techniques to social work research.
• SOWO 917. Longitudinal and Multilevel Analysis (3 credits) This course introduces statistical frameworks, analytical tools, and social behavioral applications of three types of models: event history analysis, hierarchical linear modeling (HLM), and growth curve analysis.
• SOWO 918. Applied Regression Analysis and Generalized Linear Models (3credits) Prerequisite, permission of the instructor. This course introduces statistical frameworks, analytical tools, and social behavioral applications of OLS regression model, weighted least-square regression, logistic regression models, and generalized linear models.

ELECTIVE COURSES

Strongly Recommended: Additional methods training that can count toward the 9-credit elective requirement. We highly recommend students in the pharmaceutical policy and economics concentration take advanced methods courses beyond the requirements listed above. Students should consult regularly with their advisor to select from many available options. A number of graduate level elective courses that are relevant are offered at UNC. We list several below but encourage students to review course offerings each semester to find courses that match their research and career interests.

Health Policy and Management

• HPM 715. Health Economics for Policy and Management (3 credits).Provides training in the theory of health economics and applies this theory to important issues in health policy and management.
• HPM 757. Health Reform: Political Dynamics and Policy Dilemmas (3 credits). This course focuses on the political and policy dynamics of health care reform.
• HPM 758.Underserved Populations and Health Reform (3 credits). Students will gain an understanding of how the changes in the health care market affect care for underserved populations and will develop strategies to ensure that the needs of these populations are met.
• HPM 759.Health Policy Development and Advocacy for Health Leaders (2 credits). Executive Doctoral Program in Health Leadership (DrPH). The course will familiarize students with the history of health reform in the US, explore issues in health policy, analyze the impact of health politics on policymaking.
• HPM 762.Quality of Care (3 credits). The quality of health care in the US has garnered significant attention. This course will examine: (1) the current state of the quality of care in the US; (2) approaches to assess quality of care, and (3) strategies that have been implemented or proposed to improve the quality of care.
• HPM 772. Techniques for the Economic Evaluation of Health Care (3 credits). This course provides an investigation of the theory, methods, and application of economic evaluation to health care. Topics include methods used to structure an economic evaluation, measure and summarize health outcomes and estimate their value to patients or to the public, and identify resources used and estimate their costs. Prerequisite, EPID 600.
• HPM 785 Advanced Decision Modeling (3). This course covers advanced decision modeling methods in health care, including probabilistic sensitivity and value of information analysis, economic evaluation using clinical trial data, and discrete event simulation and agent-based/system dynamics modeling techniques. The course teaches analytical techniques and interpretation as well as and state-of-the-art best practices. Prequisite: HPM 772.
• HPM 815. Graduate Health Economics Seminar (1 credit). Permission of the instructor. Discussion of recent papers in health economics. Students must have solid knowledge of graduate microeconomics theory and econometrics.

Public Policy

• PLCY 716. Politics and Public Policy Theory (3 credits). Students build a theoretical foundation about the politics of policymaking. We examine the governmental institutions and actors that make policy decisions, incentive structures, and influences that shape these decisions as well as the macro-environment within which policy demands arise and policy decisions are made.
• PLCY 788. Advanced Economic Analysis for Public Policy I (3 credits). This course introduces microeconomic theory using multivariate calculus and constrained optimization. Topics covered include consumer theory, producer theory, market equilibrium, taxes, and market power. Applied public policy examples are incorporated.
• PLCY 789. Advanced Economic Analysis for Public Policy II (3 credits). This course provides further applications of economic theory to public policy including risk and uncertainty, information economics, general equilibrium and welfare policy, externalities, public goods and taxation, and game theory. Prerequisite, PLCY 788.

Economics

• ECON 698. Philosophy, Politics, and Economics: Capstone Course (3 credits) Permission of the department. This capstone course advances PHIL 384, focusing on such theoretical and philosophical issues as the analysis of rights or distributive justice and the institutional implications of moral forms.
• ECON 810. Game Theory I (3 credits) Noncooperative games in strategic and extensive form, with perfect and imperfect information. Other topics from: information economics, mechanism design, auctions, repeated games, bargaining, bounded rationality, learning, evolutionary games, cooperative games.
• ECON 840. Advanced Finance: Expenditure (3 credits) Analysis of market failure and reasons for public spending, cost-benefit analysis and program budgeting, public decision making, redistribution and fiscal equity, intergovernmental transfers.
• ECON 850. Health Economics (3 credits). Measurement and modeling of the demand for medical care, the demand for and supply of health insurance, and the incorporation of health, medical care, and health insurance in determining both short and long run labor supply. Prerequisites: ECON 710 (Advanced Microeconomic Theory) and 771 (Econometrics); permission of the instructor for students lacking the prerequisites.
• ECON 851. Health Economics for Developing Countries (3 credits). Major topics are: how health and development are related, the demand for health services, cost-benefit and cost-effectiveness analysis, and methods for financing health care in developing, resource-constrained nations. Prerequisites: ECON 710 (Advanced Microeconomic Theory) and 771 (Econometrics); permission of the instructor for students lacking the prerequisites.
• ECON 873. Microeconometrics (3 credits). Limited dependent variable models such as binary outcome models, multinomial outcome models, and censored and truncated outcome models. Count data models. Duration models. Panel data analysis. Prerequisite: ECON 870.
• ECON 880. Labor Economics I (3 credits). Analysis of short- and long-run aspects of supply and demand of labor, including empirical analysis of labor force behavior of males, females, blacks, and whites. Microeconomic effects of marriage, fertility, mobility on labor supply, and macroeconomic effects of unemployment on inflation. Prerequisite: ECON 710; permission of the instructor for students lacking the prerequisite.
• ECON 881. Labor Economics II (3 credits). This course covers a range of topics in labor economics, with a unifying theme of understanding how economics informs policies for alleviating inequality. Topics include social interactions, education, early childhood intervention, and discrimination.

Pharmaco-Epidemiology Concentration

The pharmaco-epidemiology concentration prepares students to interpret and apply state-of-the-art epidemiologic approaches to study utilization and comparative effectiveness/safety of healthcare interventions using a variety of complex data sources (e.g., administrative healthcare claims, electronic health records, and registries). Students in this concentration can tailor their coursework to develop expertise in the methodologies of greatest interest to them, focused on quantitative methods, including predictive analytics and causal inference.

Through completion of the required course work listed below, students who complete the PhD in DPOP with a concentration in pharmaco-epidemiology will also fulfill the requirements for a Minor in Epidemiology from the UNC Gillings School of Global Public Health. Prior to enrollment in your first semester of classes, you will coordinate with your advisor to formally declare your intention to minor, which you can opt out of at a later time if desired.

REQUIRED COURSEWORK FOR PHARMACO-EPIDEMIOLOGY CONCENTRATION

(* denotes that course is required for all DPOP PhD students)

BIOSTATISTICS COURSES

Students in the pharmaco-epidemiology concentration are required to take a minimum of 6 credit hours in biostatistics classes. In addition to the formal biostatistics requirement detailed below, students should consult with their advisor to develop a specific plan for advanced methods training.

In your 1^st semester, there are two recommended options (choose one only):

• BIOS 600. Principles of Statistical Inference (3 credits). Major topics include elementary probability theory, probability distributions, estimation, hypothesis testing, chi-square procedures, regression, and correlation.
• BIOS 662. Intermediate Statistical Methods (4 credits). Principles of study design, descriptive statistics, and sampling from finite and infinite populations, with particular attention to inferences about location and scale for one, two, or k sample situations. Both distribution-free and parametric approaches are considered. Gaussian, binomial, and Poisson models, one-way and two-way contingency tables, as well as related measures of association, are treated.

In your 2nd semester, there is one recommended biostatistics course:

• BIOS 545. Principles of Statistical Inference (3 credits). Continuation of BIOS 600; the analysis of experimental and observational data, including multiple regression, and analysis of variance and covariance.

Starting in your 3rd semester, you should work with your advisor to select additional methods courses that best align with your interest and training needs. The section below on elective courses can serve as a useful starting point for some of those decisions.

ELECTIVE COURSES

Strongly Recommended: Additional methods training that can count toward the 9-credit elective requirement. We highly recommend students in the pharmaco-epidemiology concentration take advanced methods courses beyond the requirements listed above. Students should consult regularly with their advisor to select from many available options. Recommended additional methods courses include (but are not limited to):

• DPOP/EPID 766. Epidemiologic Research Using Healthcare Databases (3 credits). This course focuses on how healthcare utilization data are generated and how to use databases to identify study populations and conduct epidemiologic studies of utilization patterns and comparative effectiveness/safety of prescription drugs and healthcare services. A major component of this course is an independent (or small group) project using IBM Watson Marketscan claims data.
• EPID 718. Analytic Methods in Observational Epidemiology (3 credits). This course covers general epi concepts and applications, including logistic regression, binomial regression, model building strategy, additive and multiplicative interaction, and graphical exploration of data.
• EPID 722. Epidemiologic Analysis of Time-to-Event Data (4 credits). This course covers epidemiologic analysis of time-to-event data and emphasizes weighing threats to the accuracy of inferences.

Other recommended electives for students in the pharmaco-epidemiology concentration. A number of graduate level elective courses that are relevant to the pharmaco-epidemiology concentration are offered at UNC. We list several below but encourage students to review course offerings each semester to find courses that are of greatest interest to them. A long list is provided below, but it is not exhaustive; you can work with your advisor to help select optimal courses for your trajectory.

• EPID 719. Readings in Epidemiologic Methods. (1 credit)
• EPID 731. Systematic Review and Meta-Analysis (1)
• EPID 733. Clinical Trials in Epidemiology (3)
• EPID 735. Cardiovascular Epidemiology (3)
• EPID 742. Biomarkers in Population-Based Research (2)
• EPID 743. Genetic Epidemiology: Methods and Applications (3)
• EPID 750. Fundamentals of Public Health Surveillance (3)
• EPID 751. Emerging and Re-Emerging Infectious Diseases (3)
• EPID 753. Prevention and Control of Infectious Diseases at the Level of the Community (3)
• EPID 754. Advanced Methods in Infectious Disease Epidemiology (3)
• EPID 755. Introduction to Infectious Disease Epidemiology (3)
• EPID 756. Control of Infectious Diseases in Developing Countries (3)
• EPID 757. Epidemiology of HIV/AIDS in Developing Countries (3)
• EPID 760. Vaccine Epidemiology (3-4)
• EPID 764. Hospital Epidemiology (1-2)
• EPID 770. Cancer Epidemiology and Pathogenesis (3)
• EPID 771. Cancer Epidemiology: Survivorship and Outcomes (3)
• EPID 772. Cancer Prevention and Control Seminar (3)
• EPID 775. Advanced Cancer Epidemiology: Classic and Contemporary Controversies in Cancer Causation (2)
• EPID 785. Environmental Epidemiology (3)
• EPID 786. Community-Driven Epidemiology and Environmental Justice (2)
• EPID 787. Advanced Environmental Epidemiology (3)
• EPID 790. Intervention Epidemiology (2)
• EPID 795. Introduction to Public Health Informatics (1)
• EPID 813. Nutritional Epidemiology (3)
• EPID 814. Obesity Epidemiology (3)
• EPID 826. Introduction to Social Epidemiology (3)
• EPID 827. Social Epidemiology: Design and Interpretation (2)
• EPID 851. Reproductive and Perinatal Epidemiology (3)
• EPID 853. Advanced Topics in Perinatal and Pediatric Epidemiology (2)

Although it may not be used toward the elective requirement, DPOP students in the pharmaco-epidemiology concentration are strongly encouraged to attend EPID 893, the Pharmacoepidemiology Seminar. Offered every semester, this is a weekly seminar to explore current problems in pharmacoepidemiology and share research in a friendly but formal environment. Students may enroll in this 1-credit seminar as many times as they wish, but enrollment is not required in order to attend the seminar.

Social and Behavioral Concentration

The Social Behavioral concentration prepares students to apply social behavioral theory in the design and evaluation of health interventions as well as in the study of multilevel factors that affect health behaviors and outcomes. Students learn how to ask impactful questions, select optimal study designs and research methods to answer those questions, and disseminate their research findings to diverse audiences. Through research rotations and practica, students gain skills in primary data collection and secondary data analysis. Students in this concentration can tailor their coursework to develop expertise in the methodologies of greatest interest to them, including quantitative and qualitative methods.

REQUIRED COURSEWORK FOR SOCIAL BEHAVORIAL CONCENTRATION

(* denotes that course is required for all DPOP PhD students)

STATISTICS COURSES

Students are required to take a minimum of 9 credit hours of statistical coursework. A number of departments offer statistical courses. Students are encouraged to review the following statistical series and select the series that is of greatest interest to them. Different departments teach using different statistical software programs, so students should consider this when selecting a statistical series.

SOCIOLOGY

• SOCI 708. Statistics for Sociologists (4 credits) Provides an introduction to probability theory, descriptive statistics, inferential statistics, and the algebra of expectations. Emphasis is on elements useful to research sociologists, including bivariate regression and correlation.
• SOCI 709. Linear Regression Models (4 credits) The course presents regression analysis and related techniques. The major topics are the assumptions of the regression model, dummy variables and interaction terms, outlier diagnostics, multicollinearity, specification error, heteroscedasticity and autocorrelation. The final section introduces path analysis, recursive models, and nonrecursive systems.
• SOCI 711. Analysis of Categorical Data (3 credits) Perquisite, permission of the instructor. Introduction to techniques and programs for analyzing categorical variables and nonlinear models. Special attention is given to decomposition of complex contingency tables, discriminant function analysis, Markov chains, and nonmetric multidimensional scaling.
• SOCI 717. Structural Equations with Latent Variables (3 credits) Prerequisite, SOCI 708 or permission of the instructor for students lacking the prerequisite. This course examines models sometimes referred to as LISREL models. Topics include path analysis, confirmatory factor analysis, measurement error, model identification, nonrecursive models, and multiple indicators.
• SOCI 718. Longitudinal and Multilevel Data Analysis (3 credits) Prerequisite SOCI 709or 711. This course provides an introduction to event history analysis or survival analysis, random effects and fixed effects models for longitudinal data, multilevel models for linear and discrete multilevel data, and growth curve models.

EDUCATION

• EDUC 710. Statistical Analysis of Educational Data I (4 credits). Studies descriptive and inferential statistics for educational research, including an introduction to fundamentals of research design and computer data analysis.
• EDUC 784. Statistical Analysis of Educational Data II (4 credits). Prerequisite, EDUC 710 or permission of the instructor. A linear model approach to the analysis of data collected in educational settings. Topics include multiple regression, analysis of variance, and analysis of covariance, using computer packages.
• EDUC 884. Statistical Analysis of Educational Data III (3 credits). An extension of the general linear model to analysis of educational data with multiple dependent variables, with computer applications.
• EDUC 888. Introduction to Structural Modeling (3 credits). Introduces structural equation modeling with both observed and latent variables. Applications include confirmatory factor analysis, multiple group analyses, longitudinal analyses and multitrait-multimethod models.

SOCIAL WORK

• SOWO 916. Structural Equation Modeling (3 credits). In this course, students will learn fundamental concepts and skills to conduct structural equation modeling and will learn how to apply these techniques to social work research.
• SOWO 917. Longitudinal and Multilevel Analysis (3 credits). This course introduces statistical frameworks, analytical tools, and social behavioral applications of three types of models: event history analysis, hierarchical linear modeling (HLM), and growth curve analysis.
• SOWO 918. Applied Regression Analysis and Generalized Linear Models (3 credits) Prerequisite, permission of the instructor. This course introduces statistical frameworks, analytical tools, and social behavioral applications of OLS regression model, weighted least-square regression, logistic regression models, and generalized linear models.

HEALTH POLICY

• HPM 881. Linear Regression Models (3 credits). Permission of instructor required (with exception of HPM PhD students). Prerequisite: BIOS 600 or equivalent background in probability theory/statistics for students lacking the prerequisite. Required preparation, matrix algebra, derivatives, logs/exponentials, and Stata. This course is an introduction to linear regression models. Topics include least squares regression, multicollinearity, heteroscedasticity, autocorrelation, and hypothesis testing. Students wishing to enroll in the HPM 881-883 sequence are strongly encouraged to enroll in HPM 880 (Mathematical and Statistical Tutorial) in the preceding fall semester.
• HPM 882. Advanced Methodology for Health Policy and Management Research (3 credits). Prerequisite: HPM 881, or permission of the instructor. Research methodology as applied to understanding problems in health care delivery. Topics include simultaneous equation models, factor analysis, limited dependent variables, and an introduction to event history analysis.
• HPM 883. Analysis of Categorical Data (3 credits) Prerequisite: HPM 881 and HPM 882 or equivalent. This course is an introduction to the analysis of categorical data using maximum likelihood estimation (MLE) and other non-linear techniques and specification tests. Topics covered include models in which the dependent variable is not continuous, including logit, probit, censored data, two-part, and count models.

BIOSTATISTICS

• BIOS 600. Principles of Statistical Inference (3 credits). Major topics include elementary probability theory, probability distributions, estimation, hypothesis testing, chi-square procedures, regression, and correlation.
• BIOS 545. Principles of Statistical Inference (3 credits). Continuation of BIOS 600; the analysis of experimental and observational data, including multiple regression, and analysis of variance and covariance.
• BIOS 665. Analysis of Categorical Data (3 credits). Prerequisites, BIOS 545, 550, and 662; or permission of the instructor for students lacking the prerequisites. Introduction to the analysis of categorized data: rates, ratios, and proportions; relative risk and odds ratio; Cochran-Mantel-Haenszel procedure; survivorship and life table methods; linear models for categorical data. Applications in demography, epidemiology, and medicine.

ELECTIVE COURSES

Strongly Recommended: Additional methods training that can count toward the 9-credit elective requirement. We highly recommend students in the social behavioral concentration take advanced methods courses beyond the requirements listed above. Students should consult regularly with their advisor to select from many available options. A number of graduate level elective courses that are relevant to the social behavioral concentration are offered at UNC. We list several below but encourage students to review course offerings each semester to find courses that are of greatest interest to them.

Health Behavior

• HBEH 753. Qualitative Research Methods (3 credits)
• HBEH 754. Advanced Qualitative Research Methods in Health Behavior and Health Research (3 credits)
• HBEH 756. Social and Peer Support in Health: An Ecological and Global Perspective (3 credits)
• HBEH 795. E-Health (3 credits)

SOCIAL WORK

• SOWO 921. Qualitative Research Methods. (3 credits)
• SOWO 922. Advanced Topics in Causal Inference: Propensity Score and Related Models.

 (3 credits)

SOWO 923. Systemic Reviews and Introduction to Meta-Analysis. (3 credits)

NURSING

• NURS 962. Conducting Systematic Reviews and Writing Specific Aims. (4 credits)
• NURS 976. Issues in Sampling and Design. (3 credits)
• NURS 977. Qualitative Approaches to Knowledge Development. (3 credits)
• NURS 979. Qualitative Analysis. (3 credits)

SOCIOLOGY

• SOCI 761. Questionnaire Design. (3 credits)
• SOCI 762. Case Studies in Surveys. (3 credits)
• SOCI 863. Sociology of Health, Illness, and Healing. (3 credits)

EPIDEMIOLOGY

• EPID 825. SOCIAL DETERMINANTS OF HEALTH: THEORY, METHOD, AND INTERVENTION

(3 credits)

HEALTH POLICY

• HPM 758. Underserved Populations and Health Reform (3 credits)
• HPM 830. Translational Health Disparities: Research, Practice & Policy (3 credits)