Epidemiology

Fall 2019 Course Offerings
BIOE 720-701 Biostatistics for Public Health - for students in the Certificate in Clinical Research program Nhu Quynh Tran
Start date:2017-08-14End date:2017-12-15
Time: Place: Duration: Credit:3
This course provides an introduction to the use of statistical techniques in biomedical and public health research. The course will cover common descriptive statistics including the mean, median, and standard deviation as well as techniques for testing hypotheses (analysis of variance, t-tests, regression, nonparametric methods) and issues in sampling and design of experiments. The class will be taught using online methods and is open only for students enrolled in programs of the Tennessee Consortium for Public Health Workforce Education. (online, lecture)
BIOE 727 Principles of Epidemiology Pam Connor, PhD
Start date:2017-08-14End date:2017-12-15
Time: Place: Duration: Credit:3
This online course introduces the basic principles and methods of epidemiology and demonstrates their applicability in the fields of public health and clinical research. Topics to be covered include the historical perspective of epidemiology, measures of disease occurrence and association, study design, disease screening, and causal inference. Study design content will cover experimental, cohort and case-control studies as well as challenges in design and analysis including bias, confounding and random error. Students will be expected to participate in discussion boards, complete weekly homework assignments, and take a mid-term and final exam. (online, lecture)
BIOE 800 Master's Thesis and Research Pamela Connor
Start date:2017-08-14End date:2017-12-15
Time: Place: Duration: Credit:variable
Research performed under the direction and supervision of the respective student's Research Advisor, in partial fulfillment of the requirements for the degree of Master of Science. (didactic, research)
BIOE 804 Master's Project Simonne Nouer
Start date:2017-08-14End date:2017-12-15
Time: Place: Duration: Credit:variable
Students will work on their master?s project in conjunction with advisor and master?s committee. Research-based course. Credit variable (1-6) as assigned by instructor. (didactic, research)
BIOE 805 Using R for Biostatistics I Zoran Bursac, PhD, MPH
Start date:2017-08-14End date:2017-12-15
Time: Place: Duration: Credit:1
This course will introduce optional statistical software computing associated with topics discussed in Biostatistics I. The primary statistical software will be R. R is an extremely versatile and powerful statistical package that is becoming very popular among researchers in virtually every research realm. Topics will include but not limited to inputting data, calculation of descriptive statistics, t-tests, confidence intervals, chi-square test, analysis of variance (ANOVA), simple and multiple regression, and non-parametric methods. This course is designed to enrich computing skills. Simultaneous or past enrollment in Biostatistics for Health Sciences I is not required, but is highly recommended. Students should have a background in fundamental statistics. Students must provide their own notebook computer. (didactic, lecture)
BIOE 810 Independent Study Simonne Nouer
Start date:2017-08-14End date:2017-12-15
Time: Place: Duration: Credit:variable
An in-depth study of some aspect of epidemiology in which the student has special interest. Study is done independently with faculty approval and supervision. (didactic, independent)
BIOE 811 Biostatistics for the Health Sciences I Betsy Tolley, PhD
Start date:2017-08-14End date:2017-12-15
Time: Place: Duration: Credit:4
This course provides students with an introduction to descriptive statistics, probability and probability distributions, estimation, and one and two sample hypothesis testing, including paired and unpaired situations, for normally distributed and ordinal data. Students will also be introduced to one-way analysis of variance, including multisample inference, one-way ANOVA, fixed-effect and random effects models, and intraclass correlation coefficients. This course also includes a mandatory statistical computing laboratory that uses SAS for data analysis throughout the semester. (online, lecture lab)
BIOE 812 Fundamentals of Epidemiology Simonne S. Nouer, MD, PhD
Start date:2017-08-14End date:2017-12-15
Time: Place: Duration: Credit:3
The course introduces the basic principles and methods of epidemiology and demonstrates their applicability in the field of public health. Topics to be covered include the historical perspective of epidemiology, measures of disease occurrence and of association, clinical epidemiology, disease screening, causal inference, and study design. (online, lecture)
BIOE 813 Fundamentals of SAS for Epidemiology Jim Y. Wan, Ph.D.
Start date:2017-08-14End date:2017-12-15
Time: Place: Duration: Credit:3
This course provides the foundation computing skills for independent analysis of epidemiologic data. Topics to be covered include an introduction to SAS as a research tool; Operating with SAS for Windows environment; Reading internal and external data into SAS; Working with variables and SAS functions; Using logical statements; Introducing SAS procedures - especially those that produce descriptive statistics; Performing simple inferential tests and power analysis; combining datasets; Reshaping data; and Introducing macro language. This course consists of 2 hour lecture and 1 hour laboratory session per week. (online, lecture lab)
BIOE 823 Randomized Clinical Trials Mathilda Coday
Start date:2017-08-14End date:2017-12-15
Time: Place: Duration: Credit:3
This course will allow the student to understand and analyze the many critical facets of the most precise design for clinical studies in humans: randomized clinical trials. Using a case-based approach, students will learn the importance of precise hypothesis description, selection of an at risk cohort for study, and the power of randomization in helping balance the study groups on a number of known and unknown confounding factors. Important issues with regard to subject recruitment, patient management, and data quality control will be emphasized. Students will learn to perform their own sample size calculations and use actual statistical packages to outline real clinical trial results data. (hybrid, lecture)
BIOE 848 Professional Experience and Prior Learning Assessment Simonne Nouer
Start date:2017-08-14End date:2017-12-15
Time: Place: Duration: Credit:variable
This course recognizes that work experience can provide valuable learning experiences that can complement learning acquired through formal education. This course offers an assessment of experiential learning, performed through the construction of a portfolio, that emphasizes the connection between learning from work experience, practice skills, continuing education, clinical investigatory knowledge, and its translational application to research. This course cannot be repeated. Variable credit 1-3 hours. (didactic, lecture)
BIOE 850 Categorical Data Analysis Mehmet Kocak
Start date:2017-08-14End date:2017-12-15
Time:9:00 A.M.-10:30 A.M.Place:Preventive Medicine SAS LabDuration:Once a week for 10 weeks with 1 hour face-to-face in each meeting, with 2 hours of course materials provided each week online. Credit:2
This course is a 2-credit hour hybrid course, where the students will receive 2-hour worth of online course materials and will have a weekly one-hour face-to-face session with the instructor. The course begins with an introduction and review of most common discrete random variables and their probability distributions, followed by a brief discussion of ‘parameter estimation’ as a general concept in Theoretical Statistics. Then, we introduce the concept of inferential statistics by discussing one-sample confidence interval and hypothesis testing for one- and two-sample designs, which includes the definition of and testing for statistical independence through the most commonly used chi-square-based tests for 2x2, Rx2, 2xC, and RxC contingency tables and sets of (stratified) contingency tables. Then, the generalized linear model is introduced as the backbone for model building that focuses on the estimation of effects of one or more predictors on a binary response variable or on a count variable, including model inference and model diagnostics checking. Specific topics for the modeling of categorical data include logistic regression for dichotomous and polytomous response, conditional logistic regression, generalized estimating equations, and generalized linear mixed modeling for models with random effects. In addition, the course will explore log-linear modeling for count data. The relation of the various approaches and procedures using SAS will be demonstrated. The course focuses on application of the above approaches to observational and clinical trial designs. At the end of the semester, a letter grade will be assigned to each student according to the following system of grades, with equivalent quality point value, is adopted: A (4-0); A- (3.67); B+ (3.33); B (3.00); B- (2.67); C+ (2.33); C (2.00); C- (1.67); D (1.00); and F (0) (as specified at http://www.uthsc.edu/grad/CollegeInfo/index.php?page=Bylaws#Grading). (hybrid, lecture)
BIOE 864 Data Science 2: Statistical Methods for Observational Studies Fridtjof Thomas
Start date:2017-08-14End date:2017-12-15
Time: Place: Duration: Credit:1
This second course in data science Data Science 2: Statistical Methods for Observational Studies focuses on statistical approaches in data science, especially those relating to observational studies. This course can also be chosen independently for those students that wish to learn about observational studies in general. Students will learn about the distinction of causal analysis vs. association studies and the consequences for appropriately choosing statistical methods for data analysis. Sources of bias in observational studies and statistical methods to tackle these are discussed. This 1 credit course is taught with hands-on exercises and the student is expected to be comfortable with algorithmic approaches and computer programming. (didactic, lecture)
BIOE 865 Linear Regression Methods for the Health Sciences Betsy Tolley, PhD
Start date:2017-08-15End date:2017-10-05
Time:Tuesday & Thursday, Noon - 2 PMPlace:Room 400, 66 North Pauline StreetDuration:16 meetings of 2 hours each Credit:2
In this course, students will learn how multiple linear regression models are derived, use software to implement them, learn what assumptions underlie the models, learn how to test whether data meet those assumptions and what can be done when those assumptions are not met, and develop strategies for building and understanding useful models. (hybrid, lecture)
BIOE 866 Linear Mixed Models Tamekia Jones
Start date:2017-08-14End date:2017-12-15
Time:Tuesday & Thursday, 1-3 pmPlace: Duration:14 lectures for 2 hours each Credit:2
This course provides the advanced skills necessary for independent statistical analysis of epidemiologic and clinical data containing clustered observations and random effects. Topics to be covered include unrestricted and restricted maximum likelihood estimation, Akaike’s information criterion, standard general linear models, linear random effects models, linear covariance pattern models, and linear random coefficient models. The course focuses on applications requiring flexible modeling of variance and covariance structures for clustered data when observations from a common cluster are correlated. The approaches covered in the course are particularly relevant for analysis of hierarchical and longitudinal data having Gaussian distributed error (, lecture)
BIOE 867 Data Science I Robert Davis
Start date:2017-08-14End date:2017-12-15
Time: Place: Duration: Credit:2
This first course in data science Data Science 1: Using Electronic Medical Record Data for Clinical Research is an opportunity to gain ‘hands-on’ experience analyzing data to answer specific research questions. Methods and theoretical issues introduced in earlier courses will be covered, but with a focus on practical analysis issues with actual data. Students work in small groups (2-3) on separate research topics, with each group using a different dataset that we provide. Data will come from CERNER Health Facts, the UTHSC Enterprise Data Warehouse and other data sources. This 2 credit course is taught with hands-on exercises and the student is expected to be comfortable with computer programming. (didactic, lecture)
Spring 2020 Course Offerings
BIOE 728 Health Behavior Intervention Karen Derefinko
Start date:  2019-01-07    End date:  2019-05-08
Time:  Online/access depends upon student schedule   Place:  Online   Duration:  16 Credit:  3
This course introduces the theory and methods of interventions for health behaviors, and demonstrates their applicability in the fields of public health and clinical research. Topics to be covered include the applicable theories of health behavior change, the different mechanisms of intervention, empirical validation of intervention methods, the format of intervention methods, and the phases of validation (efficacy, effectiveness, and dissemination). Students will be expected to participate in discussion boards, complete weekly homework assignments, and take a mid-term and final exam. (online, lecture)
BIOE 750 Fundamentals of Clinical Investigation Mace Coday, Ph.D.
Start date:  2019-01-02    End date:  2019-06-30
Time:     Place:     Duration:  Credit:  3
This course will present an introduction to the different types of clinical research and practical methods that investigators can use in the conduct of multidisciplinary clinical research. Observational cohort studies, case-control studies, and Phase I-IV intervention-based randomized controlled clinical trials will be presented. Design distinctions, sampling and randomization procedures, data integrity, data-analysis concerns, and practical conduct for these investigative approaches will be examined. This course will also review ethical issues in conducting research in people, federal guidance for the conduct of clinical research, and the dynamic influence of behavior on the conduct of clinical research. This is an online course for the web-based Certificate in Clinical Research program. (online, lecture)
BIOE 800 Master's Thesis and Research Simonne Nouer
Start date:  2019-01-02    End date:  2019-06-30
Time:     Place:     Duration:  Credit:  variable
Research performed under the direction and supervision of the respective student's Research Advisor, in partial fulfillment of the requirements for the degree of Master of Science. (didactic, research)
BIOE 804 Master's Project Simonne Nouer
Start date:  2019-01-02    End date:  2019-06-30
Time:     Place:     Duration:  Credit:  variable
Students will work on their master?s project in conjunction with advisor and master?s committee. Research-based course. Credit variable (1-6) as assigned by instructor. (didactic, research)
BIOE 806 Using R for Biostatistics II Saunak Sen
Start date:  2019-01-02    End date:  2019-06-30
Time:     Place:     Duration:  Credit:  1
This course will introduce optional statistical software computing associated with topics discussed in Biostatistics II. The primary statistical software will be R. R is an extremely versatile and powerful statistical package that is becoming very popular among researchers in virtually every research realm. Topics will include but not limited to inputting data, calculation of descriptive statistics, statistical graphics, correlation, simple and multiple linear regression, general linear models, experimental designs, logistic regression, factorial analysis of variance and repeated measures. This course is designed to enrich computing skills. Simultaneous or past enrollment in Biostatistics for Health Sciences II is not required, but is highly recommended. Students should have a background in fundamental statistics. Students must provide their own notebook computer. (didactic, lecture)
BIOE 810 Independent Study Simonne Nouer
Start date:  2019-01-02    End date:  2019-06-30
Time:     Place:     Duration:  Credit:  variable
An in-depth study of some aspect of epidemiology in which the student has special interest. Study is done independently with faculty approval and supervision. (didactic, independent)
BIOE 821 Biostatistics for the Health Sciences II Elizabeth Tolley
Start date:  2019-01-02    End date:  2019-06-30
Time:     Place:     Duration:  Credit:  4
Second semester content pertains to methods of regression for observational and experimental data. Methods of analysis and hypothesis testing for three or more treatments are presented for various experimental designs and treatment combinations for normally distributed and ordinal data. Instruction includes helping the students attain mastery-level skill in programming with the SAS software system for statistical analysis of data. (online, lecture)
BIOE 822 Advanced Epidemiology Simonne Nouer
Start date:  2019-01-02    End date:  2019-06-30
Time:     Place:     Duration:  Credit:  4
This course provides the foundation skills for independent analysis of epidemiologic data. Topics to be covered include the analysis of vital statistics data, statistical analysis of simple epidemiologic measures, identification and control of confounding in epidemiologic data, model building using epidemiologic data, logistic regression, and proportional hazards modeling. At the end of the semester, students will be able to analyze data from matched and unmatched case-control studies, case-cohort studies, and traditional cohort designs. The course includes a mandatory statistical computing laboratory. (online, lecture)
BIOE 824 Genetic Epidemiology: Methods and Applications Khyobeni Mozhui
Start date:  2019-01-02    End date:  2019-06-30
Time:     Place:     Duration:  Credit:  3
This course provides the concepts and methods of genetic epidemiology that are relevant to studying the causes of complex human diseases and the impact of human genetic variation on disease prevention and treatment. The course includes methods of population- and family-based studies of genotype-phenotype associations; statistical techniques related to segregation analysis; linkage analysis and transmission disequilibrium test (TDT); approaches for assessing gene-gene and/or gene-environment interaction; and procedures for evaluating ethical, legal, and social issues, and public health implications of research and interventions. Emphasis is placed on distinguishing the appropriate applications, underlying assumptions, and reasonable interpretations of the methods presented. (didactic, lecture)
BIOE 834 Epidemiology of Childhood Diseases Marion Hare, MD
Start date:  2019-01-02    End date:  2019-06-30
Time:     Place:     Duration:  Credit:  2
This course will provide an overview of the epidemiology of selected conditions and diseases affecting children as well as demonstrate the childhood origins of some adult chronic disease. For most of these conditions, information about the pattern of occurrence, data about risk factors and effectiveness of various preventive or therapeutic interventions will be discussed. Public use sources of information such as the National Health and Examination Survey (NHANES), National Ambulatory Medical Care Survey (NAMCS), CDC "Pink Book", Child and Adolescent Health Measurement Initiative (CAHMI) and Youth Risk Behavior Surveillance System (YRBSS) will be introduced and discussed. Additionally, some of the unique and challenging aspects of research in pediatric epidemiology such as issues of childhood growth and development, maternal (intrauterine) origins of disease and parental role in disease diagnosis and treatment will be introduced. In the last weeks of the course, students will be asked to synthesize the information presented in the course by identifying, presenting and evaluating the available epidemiological information on a childhood disease or condition of their choice. (hybrid, lecture)
BIOE 845 Biostatistics for Integrated Biomedical Sciences Śaunak Sen
Start date:  2019-01-02    End date:  2019-06-30
Time:     Place:     Duration:  Credit:  2
This is a graduate course in statistics for graduate students in biomedical sciences. Students will be able to: critically evaluate the statistical methods section of scientific papers, effectively design experiments and observational studies, display quantitative information in tables and figures, perform basic statistical analysis of studies, and identify when to seek additional help. (didactic, lecture)
BIOE 847 Advanced SAS Programming Mehmet Kocak
Start date:  2019-01-02    End date:  2019-06-30
Time:  Mondays, 9 A.M.   Place:  Preventive Medicine, SAS Lab   Duration:  In-class meeting: 1 Hour per week for 10 weeks. Two-hour video lectures will be provided each week. Credit:  2
This course provides advanced programming techniques in SAS/SQL, MACRO languages, and SAS Graphics. The natural flow of the course is intended to start with an introduction to simple SQL programming using a single dataset followed by discussions on how to work with multiple datasets with common primary key variables. Upon completing the SQL component, a smooth transition is planned to simple MACRO programming in SAS, which will be gradually advanced to more efficient yet complicated MACRO programming. This class is taught in a hybrid setting where we will have onsite review lectures in the SAS-laboratory in the Department of Preventive Medicine, and the students will be required to have a laptop with SAS access where they will work on hands-on practice of exercises from SAS SQL and MACRO Programing as well as SAS Graphics. (hybrid, lecture lab)
BIOE 848 Professional Experience and Prior Learning Assessment Simonne Nouer
Start date:  2019-01-02    End date:  2019-06-30
Time:     Place:     Duration:  Credit:  variable
This course recognizes that work experience can provide valuable learning experiences that can complement learning acquired through formal education. This course offers an assessment of experiential learning, performed through the construction of a portfolio, that emphasizes the connection between learning from work experience, practice skills, continuing education, clinical investigatory knowledge, and its translational application to research. This course cannot be repeated. Variable credit 1-3 hours. (didactic, clinical)
BIOE 868 Survival Analysis Fridtjof Thomas
Start date:  2019-01-02    End date:  2019-06-30
Time:     Place:     Duration:  Credit:  2
Survival analysis refers to the statistical approach to analyze the occurrence and timing of events. Students will gain familiarity with the characteristics of time-to-event data such as the presence of censoring and time-varying covariates, and will learn to master the necessary statistical techniques to design and analyze studies with survival data, including the construction and interpretation of Kaplan-Meier estimates and the Cox proportional hazards model. This course also extends the standard Cox model by introducing time-varying covariates and stratification as a way of dealing with non-proportionality of hazards. The course utilizes the software SAS and especially PROC LIFETEST and PROC PHREG. This 2 credit course is taught with hands-on exercises and the student is expected to bring his/her own computer with a fully functional SAS installation. (didactic, lecture)
Event times are U.S. Central time zone

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