Description

The purpose of this certificate is to provide all University of Iowa graduate students a mechanism to recognize a substantial biostatistics emphasis in their course work.  A number of graduate students already incorporate substantial training in biostatistics into their MS or PhD programs, and this certificate will provide formal recognition.

In exceptional circumstances, an individual who is not currently in a University of Iowa graduate program, but who has completed a graduate degree in a scientific area or a health related professional degree such as an MD, PharmD or equivalent, and who is currently involved in biomedical research, may also apply for admission to the Certificate Program.

For example, a postdoctoral scholar, or a fellow or resident with an MD degree, may want to enrich their postdoctoral training with additional courses in biostatistics.  Such applicants will need to apply to the Graduate College for admission as a “Graduate Non Degree Seeking Student” as well as to the Certificate Program.  Applicants are expected to have approval of their supervisor.  Credits earned as a “Graduate Non Degree Seeking Student” are transferable to a graduate program such as the Certificate with approval of the Department of Biostatistics.  If questions, please contact biostatistics@uiowa.edu for information before completing the application.

This certificate can not be completed by distance education.

Qualifications for Admission

Graduate students at the University of Iowa in degree programs outside of Biostatistics are eligible to apply.   Applications for this Certificate Program will require the signature of the student’s academic adviser from his/her home department, as well as a proposed Plan of Study showing the course requirements to be fulfilled.

Enrollment in the Certificate Program is limited by capacity.  Applicants who have already completed at least one of the required courses and whose research will be advanced by training in biostatistics will be given priority for admission.

• Biostatistics Certificate Application (pdf)

Requirements for the Certificate

An approved Plan of Study including at least 14 s.h. credits in Biostatistics is very important for this Certificate, since some of the courses require special permission to enroll, have specific prerequisites, and/or are offered less than annually.  The minimum acceptable grade for each course used to fulfill certificate requirements is a B-; the minimum cumulative GPA requirement for the 14 s.h. Certificate Program is 3.0.  A student must have at least one course to complete prior to admission to the program (certificates will not be awarded retrospectively for course work already completed).

At least 5 s.h. of the Plan of Study must be solely dedicated to the Certificate. If a waiver is granted on a required core course, then additional elective credits must be completed to replace the waived course, so that the total remains at 14 s.h.  The Certificate will typically be awarded at the end of the semester the course requirements are completed.  It should be noted that the Certificate Program in Biostatistics is generally not a step towards receiving an MS or PhD in Biostatistics, but will enhance completion of the student’s primary graduate degree and independent research.

Certificate Course Requirements (14 s.h. total)

Required “Core” Courses (6 s.h.)

•  BIOS:4120 Introduction to Biostatistics (3 s.h.)
  Application of statistical techniques to biological data including: descriptive statistics, probability and distributions, sampling distributions, nonparametric methods, hypothesis tests, confidence intervals, analysis of categorical data, and simple linear regression. Designed for non-biostatistics majors and MPH students. Prerequisite:  college algebra or ALEKS score of 65% or higher. Offered fall and spring semesters and summer session.
• BIOS:5120 Regression Modeling and ANOVA in the Health Sciences (3 s.h.)
  Continuation of BIOS:4120.  Correlation, simple and multiple linear regression, confounding, interactions, model selection, single and multiple factor ANOVA (analysis of variance) models, contrasts, multiple comparisons, nested and block designs, and an introduction to mixed models. Designed for non-biostatistics majors.  Prerequisites: BIOS:4120. Same as STAT:5610. Offered spring semesters.

Elective Courses (8 s.h. chosen from the following) 

• BIOS:4510 Data Science Foundations in R (2 s.h.)
  Introduction to use of R tools for data wrangling and communication tasks commonly encountered in biostatistics; topics include preparation and manipulation of analytic datasets, data visualization, tabular summaries, and reporting. Offered fall and spring semesters.
• BIOS:5130 Applied Categorical Data Analysis (3 s.h.)
  Analysis of proportions, risk measures, and measures of association; Mantel-Haenszel method; logistic regression for binary responses and for matched data; logistic regression for multi-category responses; analysis of count data (Poisson regression and negative binomial regression); analysis of clustered data (generalized estimating equations and generalized linear mixed effects model). Special topics include the application of propensity score methods. Designed for non-biostatistics majors.  Prerequisites: BIOS:5120.  Offered fall semesters
• BIOS:6210  Applied Survival  Analysis (3 s.h.)
  Nonparametric, parametric, and semi-parametric methods for time-to-event data; types of censoring; Kaplan-Meier estimation; Cox proportional hazards models, including methods for assessing adequacy of the proportional hazards assumption; time varying covariates; sample size calculations for comparison of two or more groups.  Focus on analysis of real data sets and examples using statistical software.  Prerequisites: BIOS:5120 or BIOS:5720.  Offered spring semesters.
• BIOS:6310  Introductory Longitudinal Data Analysis  (3 s.h.)
  Introduction to statistical models and estimation methods for outcome variables (normal and non-normal) clustered or measured repeatedly in time or space. Focus on applications and computer software methods for ANOVA based methods, hierarchical linear models, linear mixed models, correlated regression models, generalized estimating equations, and generalized linear mixed models. Prerequisites: STAT:3200 or BIOS:5120 or equivalent. Same as STAT:6550.  Offered fall semesters.
• BIOS:6420/EPID:6420 Survey Design and Analysis (3 s.h.)
  Methodological issues regarding design, sampling approach, implementation, analysis, and interpretation of surveys and questionnaires in public health research. Prerequisites: EPID:4400 and BIOS:5120.  Offered spring semesters of even years.
• BIOS:6650/EPID:6655 Causal Inference (3 s.h.)
  Causal inference overview, emphasis on inference in observational research; conceptual issues (e.g., counterfactuals, causal graphs, time-varying treatments/confounding), methods (e.g., inverse probability weighting, doubly robust estimators), and related applications (e.g., causal mediation analysis, quantitative bias analysis); for advanced biostatistics or epidemiology students. (BIOS:5720 and BIOS:5730) or (EPID:6400 and EPID:5241 and EPID:5610). Offered spring semesters.

Other courses in Biostatistics as approved by the Director of Graduate Studies in Biostatistics.