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Our PhD program prepares graduates for leadership positions in academia, industry, and government sectors. Students develop solid research skills, enabling them to conduct high quality research directed at improving the use and cost-effectiveness of pharmaceutical products, technology, and services in society.

We study the effectiveness and costs of medications, how patients take their medications, and the impact of drug policies on health outcomes in diverse populations. Our research focuses on health outcomes and how to support medication taking at the individual, practice, and system level. Key challenges our Division addresses include:

  • Ensuring that all people have the knowledge, skills, and resources to use the medications they need
  • Personalized medication treatment to ensure optimal effectiveness, safety and value in real world settings.
  • Promoting informed and shared decision making so that prescribed medication regimens reflect patients’ values, preferences and needs.

Addressing these complex issues requires an interdisciplinary approach with innovative use of a variety of data sources, including administrative records, primary survey data, and community stakeholders.

Our Curriculum

Students receive two years of didactic training in research methods with closely mentored supervision on research projects throughout the program. The curriculum consists of three concentrations:

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.

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)

Topic/course Credit hours
* DPOP 803. Social and Behavioral Aspects of Pharmaceutical Use

(Fall Semester Odd Years)

3
* DPOP 806. Pharmaceutical Policy (Fall Semester Even Years) 3
* DPOP 872. Proposal Writing (Fall Semester Even Years) 3
* PHRS 815. Implementation Science (New course! Number to be determined) 1.5
* PHRS 801. Ethics (Fall Semester) 1
* PHRS 899. DPOP Student and Faculty Seminar (Fall and Spring Semesters) 4
* PHRS 994. Doctoral Dissertation 6
* EPID 710. Fundamentals of Epidemiology (Fall Semester Odd Years) 5
EPID 765. Methods and Issues in Pharmacoepidemiology (Spring Semester) 3
Statistics (see notes below) 9
Electives (see notes below) 9
Minimum required total 48.5
 

 

 

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.

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)

Topic/course Credit hours
* DPOP 803. Social and Behavioral Aspects of Pharmaceutical Use 3
* DPOP 806. Pharmaceutical Policy 3
* DPOP 872. Proposal Writing 3
* PHRS 815. Implementation Science (New course! Number to be determined) 1.5
* PHRS 801. Ethics 1
* PHRS 899. DPOP Student and Faculty Seminar 4
* PHRS 994. Doctoral Dissertation 6
* EPID 710. Fundamentals of Epidemiology 5
   EPID 705. Introduction to Deductive and Probability Logic in Epidemiology 2
   EPID 715. Theory and Quantitative Methods in Epidemiology 4
   EPID 716. Epidemiologic Data Analysis 3
* EPID 765. Methods and Issues in Pharmacoepidemiology 3
   Biostatistics courses (see below for recommendations and options) 6
   Electives (see below for recommendations and options) 9
Minimum required total 54.5

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 1st 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.

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)

Topic/course Credit hours
* DPOP 803. Social and Behavioral Aspects of Pharmaceutical Use 3
* DPOP 806. Pharmaceutical Policy 3
* DPOP 872. Proposal Writing 3
* PHRS 815. Implementation Science (New course! Number to be determined) 1.5
* PHRS 899. DPOP Student and Faculty Seminar 4
* PHRS 801. Ethics 1
* PHRS 994. Doctoral Dissertation 6
* EPID 710. Fundamentals of Epidemiology 5
EPID 765. Methods and Issues in Pharmacoepidemiology 3
Scale Development Methods (HBEH 853) OR Patient Reported Outcomes Measurement and Application (HPM 794) 3
Statistics 9
Electives 9
Minimum required total 51.5
3

 

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)

Our Faculty

DPOP has 12 faculty members and 37 adjunct faculty members. Several faculty are located on the Asheville campus.

Faculty are trained in public health and have expertise in: pharmacoepidemiology, genomic epidemiology, health behavior and behavior change (including the effects of patient-provider communication, risk communication, and health literacy on health behavior), comparative effectiveness research, pharmaceutical policy, and pharmacoeconomics.

DPOP faculty receive funding through the National Institutes of Health, Agency for Health Care Research and Quality, Centers for Disease Control, Department of Veterans Affairs, and the Patient Centered Outcomes Research Institute as well as a number of private foundations including the Robert Wood Johnson Foundation, the American Cancer Society, the American Lung Association, and industry. Faculty also serve as advisors to numerous professional, federal, and state health and advocacy organizations.

DPOP is one of the few programs in the country with faculty who are trained in public health and that has an active research program in pharmaceutical outcomes and policy that is housed in a school of pharmacy.

DPOP Primary Faculty

Delesha Miller Carpenter

(828) 250-3916

dmcarpenter@unc.edu

Delesha Carpenter, PhD, MSPH, is an associate professor and Executive Vice Chair in the Division of Pharmaceutical Outcomes and Policy. Her research focuses on developing trainings to improve patient-provider communication about sensitive issues, like suicide and substance abuse use disorders. She also runs an active research program in inhaler technique education and mHealth. She is especially interested in improving access to healthcare services in rural areas and directs a practice-based research network for rural community pharmacists.

Jennifer Elston Lafata

(919) 966-9480

jel@email.unc.edu

Jennifer Elston Lafata, Ph.D. is a Professor in the Division of Pharmaceutical Outcomes and Policy at the UNC Eshelman School of Pharmacy at the University of North Carolina at Chapel Hill. She also serves as the co-lead for the UNC Cancer Care Quality Initiative and Associate Director in the UNC Institute for Healthcare Quality Improvement. She conducts practice-integrated research to understand and improve patient-clinician communication and decision making, particularly in the context of cancer prevention and control.

Alan Kinlaw

(919) 966-2747

akinlaw@unc.edu

Alan Kinlaw, PhD, is an assistant professor in the Division of Pharmaceutical Outcomes and Policy. His research focuses generally on pharmaco-epidemiology and health services research that leverages large and high-dimensional secondary data, including healthcare claims data, clinical registry data, and electronic health records. He studies patterns of medication use and comparative effectiveness and safety, related to antibiotic stewardship as well as several other substantive areas.

Megan Roberts

(919) 843-4071

megan.roberts@unc.edu

Megan Roberts, PhD, is an assistant professor in the Division of Pharmaceutical Outcomes and Policy and the Director of Implementation Science in Precision Health and Society at the UNC Eshelman School of Pharmacy. Her research focuses on evaluating and improving the implementation of genomic medicine. In particular, she is interested in implementation research aimed at improving quality of care and reducing racial disparities in cancer prevention and treatment.

Amanda Anne Seyerle

(919) 962-6342

aseyerle@email.unc.edu

Amanda Seyerle, PhD, MSPH, is an assistant professor in the Division of Pharmaceutical Outcomes and Policy and faculty with the Carolina Health Informatics Program (CHIP).  Her primary research interests are in understanding the ‘omics of variable drug response and the role of ‘omics and gene-environment interactions in health disparities. A critical part of this work involves expanding existing genomics research to underserved populations so that policies surrounding personalized medicine are based on more representative samples.

Betsy Sleath

(919) 962-0079

betsy_sleath@unc.edu

Betsy Sleath, PhD, is the Regional Associate Dean for Eastern North Carolina and the George H Cocolas Distinguished Professor in the Division of Pharmaceutical Outcomes and Policy in the UNC Eshelman School of Pharmacy. She is a senior research fellow and director of the Child and Adolescent Health Program at the Cecil G Sheps Center for Health Services Research. She is also an adjunct professor of health policy and management and epidemiology at the UNC Gillings School of Global Public Health. She is the recipient of the 2018 Research Achievement Award in the Pharmaceutical Sciences from the American Pharmacists Association. Sleath and her team co-developed a website with youth for youth called “Information for the Evolving Teenager” (iuveo.org) that has tools they can use to be more involved in their health care.

Kathleen Thomas

(919) 966-3387

kathleen_thomas@unc.edu

Kathleen C Thomas, PhD is an Associate Professor in the Division of Pharmaceutical Outcomes and Policy, Senior Fellow at the UNC Cecil G Sheps Center for Health Services Research and Adjunct Associate Professor in Health Policy and Management, UNC Gillings School of Global Public Health. She is a behavioral economist and mental health services researcher whose work focuses on three areas: 1) patient self-efficacy interventions, 2) health insurance policy, and 3) disparities in access to care. She conducts patient-engaged work with multidisciplinary research teams and creative data compilation to accomplish scientific breakthroughs. The combined learning in these three areas is synergistic, with the goal to improve access and quality of mental health services. You can read more about her on-going research here.

Carolyn Thorpe

(919) 843-9834

ckalino@email.unc.edu

Carolyn Thorpe, PhD, MPH is an associate professor in the Division of Pharmaceutical Outcomes and Policy. She conducts research to evaluate and improve prescribing quality and safety and medication adherence in older adults with multiple chronic conditions.

Joshua M Thorpe

(919) 225-2747

joshua.thorpe@unc.edu

Joshua M. Thorpe, PhD, MPH, is an Associate Professor in the Division of Pharmaceutical Outcomes and Policy. He is the Principal Investigator (PI) or Co-Investigator (Co-I) on NIH-funded studies including appropriate medication use and prescription safety, regulating licensed nursing practice in nursing homes, and disparities in healthy behaviors and preventive health behaviors in older adults with responsibilities for elder care.

 


Our PhD Students and Postdoctoral Fellows

DPOP typically has between 9-15 PhD students and postdoctoral fellows, who work with faculty during research rotations, and a research and teaching practicum. During their first year, students form a Student Advisory Committee (SAC). This committee provides the student with an interdisciplinary perspective, because SACs involve DPOP faculty and faculty from across campus.

Students are also partnered with a faculty advisor who can help each student personalize their experiences to suit the student’s unique interests, needs and talents.

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