Teaching

Department Of Biostatistics

Graduate Courses

The Biostatistics Department offers the following graduate and professional courses. Please check with the UNMC Graduate Studies Office to determine courses offered each semester. All prospective students who wish to register for graduate courses must apply for admission to the Graduate College.

BIOS 806 — BIOSTATISTICS I, 3 cr. Fall, annually. (Cross-listed as CPH 506) This course is designed to prepare the graduate student to understand and apply biostatistical methods needed in the design and analysis of biomedical and public health investigations. The major topics to be covered include types of data, descriptive statistics and plots, theoretical distributions, probability, estimation, hypothesis testing, and one-way analysis of variance. A brief introduction to correlation and univariate linear regression will also be given. The course is intended for graduate students and health professionals interested in the design and analysis of biomedical or public health studies; not intended for Ph.D. students enrolled in the Biostatistics Graduate Program.

BIOS 808— BIOSTATISTICS II, 3 cr. Spring, annually. (Cross-listed as CPH 650) This course is designed to prepare the graduate student to understand and apply advanced biostatistical methods needed in the design and analysis of biomedical and public health investigations. The major topics to be covered include multiple linear regression, analysis of covariance, logistic regression, and survival analysis. The course is intended for graduate students and health professionals interested in the design and analysis of biomedical or public health studies; not intended for Ph.D. students enrolled in the Biostatistics Graduate Program. Prereq: BIOS 806 or an equivalent statistics course. 

BIOS 810 — INTRODUCTION TO SAS PROGRAMMING, 3 cr. Fall, annually. (Cross-listed as CPH 651) An introduction to programming for statistical and epidemiologic analysis using the SAS Software System. Students will learn to access data from a variety of sources (e.g. the web, Excel, SPSS, data entry) and create SAS datasets. Data management and data processing skills, including concatenation, merging, and sub-setting data, as well as data restructuring and new variable construction using arrays and SAS functions will be taught. Descriptive analysis and graphical presentation will be covered. Concepts and programming skills needed for the analysis of case-control studies, cohort studies, surveys, and experimental trials will be stressed. Simple procedures for data verification, data encryption, and quality control of data will be discussed. Accessing data and summary statistics on the web will be explored. Through in-class exercises and homework assignments, students will apply basic informatics techniques to vital statistics and public health databases to describe public health characteristics and to evaluate public health programs or policies. Laboratory exercises, homework assignments, and a final project will be used to reinforce the topics covered in class. The course is intended for graduate students and health professionals interested in learning SAS programming and accessing and analyzing public use datasets from the web. Prereq: BIOS 806/CPH 506 or an equivalent introductory statistics course; EPI 821/CPH 621; and permission of instructor.

BIOS 818 — BIOSTATISTICAL METHODS II, 3 cr. Spring, annually. (Cross-listed as CPH 652) Analysis of continuous data and the interpretation of results. Major topics include simple and multiple linear regression, and analysis of variance (ANOVA). SAS statistical software will be used. Prereq: Permission of instructor; calculus (including differential and integral calculus); BIOS 806/CPH 506 Biostatistics I or BIOS 816/CPH 516 Biostatistical Methods I or an equivalent statistics course; BIOS 810/CPH 651 Introduction to SAS Programming, or equivalent experience with SAS programming.

BIOS 823 — CATEGORICAL DATA ANALYSIS I, 3 cr. Fall, annually. (Cross-listed as CPH 653) A survey of the theory and methods for the analysis of categorical response and count data. The major topics to be covered include proportions and odd ratios, multi-way contingency tables, generalized linear models, logistic regression for binary response, models for multiple response categories, and loglinear models. Interpretation of subsequent analysis results will be stressed. Prereq: Permission of instructor; BIOS 816/CPH 516 or equivalent course work (for example, calculus, BIOS 806/CPH 506 and BIOS 810/CPH 651 or equivalent experience with SAS programming).

BIOS 824 — SURVIVAL DATA ANALYSIS, 3 cr. Fall, annually. (Cross-listed as CPH 654) The course teaches the basic methods of statistical survival analysis used in clinical and public health research. The major topics to be covered include the Kaplan-Meier product-limit estimation, log-rank and related tests, and the Cox proportional hazards regression model. Interpretation of subsequent analysis results will be stressed. Prereq: Permission of instructor, calculus (including differential and integral calculus); BIOS 806/CPH 506 Biostatistics I or BIOS 816/CPH 516 Biostatistical Methods I or an equivalent statistics course; BIOS 810/CPH 651 Introduction to SAS Programming, or equivalent experience with SAS programming.

BIOS 825 — CORRELATED DATA ANALYSIS, 3 cr. Spring, annually. (Cross-listed as CPH 655) A survey of the theory and methods for analysis of correlated continuous, binary, and count data. Major topics to be covered include linear models for longitudinal continuous data, generalized estimating equations, generalized linear mixed models, impact of missing data, and design of longitudinal and clustered studies. Interpretation of subsequent analysis results will be stressed. Concepts will be explored through critical review of the biomedical and public health literature, class exercises, two exams, and a data analysis project. Computations will be illustrated using SAS statistical software (SAS Institute Inc., Cary, NC, USA.). The course is intended for graduate students and health professionals who will be actively involved in the analysis and interpretation of biomedical research or public health studies. Prereq: Permission of instructor and BIOS 823/CPH 653.

BIOS 835 — DESIGN OF MEDICAL STUDIES, 3 cr. Spring, annually. (Cross-listed as CPH 517) This course is designed to prepare the graduate student to understand and apply principles and methods in the design of biomedical and public health studies, with a particular emphasis on randomized, controlled clinical trials. The major design topics to be covered include sample selection, selecting a comparison group, eliminating bias, need for and processes of randomization, reducing variability, choosing endpoints, intent-to-treat analyses, sample size justification, adherence issues, longitudinal follow-up, interim monitoring, research ethics, and non-inferiority and equivalence hypotheses. Data collection and measurement issues also will be discussed. Communication of design approaches and interpretation of subsequent analysis results also will be stressed. Concepts will be explored through critical review of the biomedical and public health literature, class exercises, and a research proposal. The course is intended for graduate students and health professionals interested in the design of biomedical or public health studies. Prereq: Permission of Instructor; BIOS 806/CPH506 or an equivalent introductory statistics course.

BIOS 896 — RESEARCH OTHER THAN THESIS, variable cr. Fall/Spring/Summer, annually. (Cross-listed as CPH 677) This course is for more advanced students who wish to pursue their research interests in selected areas of Medical Humanities.

BIOS 918 — BIOSTATISTICAL LINEAR MODELS: THEORY AND APPLICATIONS, 3 cr. This course on linear models theory includes topics on linear algebra, distribution theory of quadratic forms, full rank linear models, less than full rank models, ANOVA, balanced random mixed models, unbalanced models and estimation of variance components. Prereq: Linear algebra, BIOS 818, one year of mathematical statistics, and permission of instructor.

BIOS 921 — ADVANCED PROGRAMMING FOR SAS, 3 cr. The objective of this course is to prepare students in advanced SAS programming. The main topics comprise advanced SAS programming techniques, SAS macro programming, using SQL with SAS, and optimizing SAS programs, which are similar to those covered on the SAS Advanced Programmer Exam offered through the SAS Institute, Inc. Prereq: BIOS 810 or a similar course, and permission of instructor.

BIOS 924 — BIOSTATISTICAL THEORY AND MODELS FOR SURVIVAL DATA, 3 cr. The course teaches the statistical theory and models for survival data analysis used in biochemical and public health research. Major topics include parametric, nonparametric, and semiparametric theory and models. The statistical software SAS and R will be used. Prereq: STAT 980 and STAT 982-983 (provided by UNL) or equivalent, BIOS 824 or equivalent, and permission of instructor.

BIOS 925 — THEORY OF GENERALIZED LINEAR AND MIXED MODELS IN BIOSTATISTICS, 3 cr. This course focuses on the theory of generalized linear models for both continuous and categorical data. Major topics include generalized linear models, linear mixed models and generalized linear mixed models. Prereq: BIOS 918 or equivalent.

BIOS 935 — SEMIPARAMETRIC METHODS FOR BIOSTATISTICS, 3 cr. The fundamental theory and application of semi parametric methods in biomedical and public health studies. The major topics include additive semiparametric models, semiparametric mixed models, generalized semiparametric regression models, bivariate smoothing, variance function estimation, Bayesian semiparametric regression and spatially adaptive smoothing. Prereq: BIOS 925, familiarity with the software R and SAS, and permission of instructor.

BIOS 941 — ESSENTIALS OF BIOSTATISTICAL CONSULTING, 2 cr. This course is designed to provide the graduate student with a fundamental understanding and insight into the practice of biostatistical consulting and give students practice in the skills required to become an effective consultant. Major topics include an overview of biostatistical consulting, communication skills, methodological aspects including design and analysis considerations, documentation and preparing reports. Prereq: Minimum of 3 graduate-level statistics of biostatistics courses and permission of instructor.