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 firstname.lastname@example.org for information before completing the application.
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.
Requirements for the Certificate
An approved Plan of Study including at least 15 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 15 s.h. Certificate Program is 3.0. A minimum of 6 s.h. of certificate course work must be completed after formal acceptance into the program (certificates will not be awarded retrospectively for course work already completed).
In accordance with Graduate College rules, no more than 6 s.h. of the Certificate may be credited to any other university degree or credential. At least 6 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 15 s.h. The Certificate will typically be awarded in the same semester as a student receives the graduate degree from his/her home department. 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 (15 s.h. total)
Required “Core” Courses (6 s.h.)
- BIOS:4120 (171:161) Introduction to Biostatistics (3 s.h.) [formerly BIOS:5110]
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 (171:162) 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 or BIOS:5110. Same as STAT:5610. Offered spring semesters and summer session.
Elective Courses (9 s.h. chosen from the following)
- BIOS:5310 (171:164) Research Data Management (3 s.h.)
Introduction to data management techniques and problems encountered in gathering and processing data from biomedical investigations. Introduction to SAS; techniques are taught in SAS. Recommendations: prior programming experience; C, C++, Python, Java, etc. Designed for non-biostatistics majors. Offered fall and spring semesters.
- BIOS:6310 (171:174 ) 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:6110 (171:241) 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 (171:242) 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.
- Other courses in Biostatistics, as approved by the Director of Graduate Studies in Biostatistics.