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The Master of Public Health in Applied Biostatistics (MPH-AB) program is designed for students wanting a broad education in the field of public health, augmented with specialization in biostatistics and informatics. In addition to coursework in four other core areas of public health, students learn a variety of commonly used statistical methods as well as their application in public health and medical research. Coursework, a practicum, and a capstone project provide experience with design, collection, management, analysis, interpretation and presentation of health data.
The Applied Biostatistics concentration in the MPH program (MPH/AB) targets students interested in a broader exposure to areas of public health, with specialization in biostatistics and analysis. The concentration is flexiable and requires 15-24 credits of biostatistics courses, but does not require the statistical theory sequence BIOS 6631/32. The MPH/AB does not prepare students for PhD work in Biostatistics.
Graduates look forward to rewarding careers in local, state and federal agencies, health and medical centers, pharmaceutical companies and research institutions, working in areas such as heart and lung disease, cancer, dental health, genetics, and infectious diseases, among others. This degree targets public health workers and researchers wishing to strengthen their analytic skills, and is particularly useful in combination with a previous research degree or experience. Students with strong skills, training and interest in mathematics and a desire to work primarily as biostatisticians in health care and biological settings should consider the MS in Biostatistics program.
|Required MPH Core Courses|
||Applied Biostatistics I
||Occupational & Environmental Health
||Social & Behavioral Factors & Health
||Health Systems Management Policy
||Foundations in Public Health
|Required Concentration Courses|
||Applied Biostatistics II
||Advanced Data Analysis
||SAS Database Design & Management
|Minimum of 3 Credits from the Following:|
||Statistical Consulting I
||Statistical Consulting II
||Latent Variable Methods
||Applied Survival & Longitudinal Analysis
||Statistical Theory I
||R in Data Science
||Causal Analytics in Public Health
||Intro to Python Programming
||Practical Data Wrangling
||Design of Clinical Trials
||Introduction to Public Health Informatics
|Identifier and Competency
||Description of Assessment
|MPH -BIOS 1: Translate a study’s scientific question or aims into testable statistical hypotheses and propose and apply appropriate statistical methods to test those hypotheses.
||Projects 0-4. All 5 written projects in 6623 assess the student’s ability to translate an investigator’s research questions into statistically testable hypotheses and to develop appropriate analysis plans. Projects 0-4 include performing the analyses and reporting results. |
Study Design Module Worksheet 5 addresses linking research questions to statistical hypotheses and appropriate analysis plans.
|MPH -BIOS 2: Fit and interpret models for continuous outcome data (normal linear model), categorical outcome data (logistic regression), and time-to-event data (Cox regression).
|6602: Assignments 1-4 and Exams 1 and 2 assess fitting linear regression models. Assignments 7 and 8 and Exam 3 assesses logistic regression. Assignment 9 and Exam 3 assess Cox regression.
6623: Regression Module Worksheets 1-3 and Correlated Data Module Worksheets 1-3 include exercises on interpreting the results from multivariable linear regression and mixed models.
Projects 0 and 1 assess fitting and interpreting multiple linear regression models. Project 2 assess fitting and interpreting linear mixed models. Project 3 assesses fitting and interpreting logistic regression models.
|MPH -BIOS 3: Apply concepts of multiple regression, including confounding, statistical interactions, model selection, model fit, and regression diagnostics, in fitting and evaluating statistical models.
|6602: Assignments 2, 3, 7 and 8 assess confounding and interaction terms. Assignment 5 assesses regression diagnostics. Assignments 6 and 7 assess model fit and model selection.
These concepts appear on all three course exams.
6623: Regression Module Worksheet 4 addresses variable selection and model building. Model diagnostics and fit are covered in Regression Module Worksheets 1-4 and Correlated Data Module Worksheets 1-3. Evaluating interactions is covered in Regression Module Worksheet 3.
All 5 projects involve consideration of potential confounders and developing strategies for variable selection. Projects 0-3 also include assessing model fit and reviewing regression diagnostics. BIOS 6623
|MPH -BIOS 4: Apply scientific and statistical principles of sampling, bias, confounding, and sample size estimation to design or interpret basic public health or biomedical studies.
||Study Design Module Worksheets 1, 3, and 4 address power and sample size calculations. In Project 4 students perform power and sample size calculations for a sample NIH grant.
Missing Data Module Worksheets 1-3 address the potential influence of missing data on statistical analyses.
Project 3 assesses the student’s ability to evaluate the potential for bias in a study due to missing data.
|MPH -BIOS 5: Use computer software for data management (data entry, access, and data manipulations), as well as for summarizing, analyzing and displaying research results
||The course has the following structure:
Part 2: Importing & Exporting Data
Part 3: Variable-Level Manipulations
Part 4: Data Set Manipulations
Part 5: Data cleaning, creating reports & figures
Each part has several assignments which assesses student competency on the topics. The topics are assessed formally on the midterm exam, final exam, and quizzes.
|MPH -BIOS 6: Use the principles of hypothesis testing and estimation of population parameters to draw inferences from quantitative data and communicate verbally and in writing those inferences and their statistical and scientific interpretation to non-statistical scientists.
||Study Design Module Worksheets 1 and 2 address communicating with non-statistical scientists.
Written reports and oral presentations for Projects 0-5 assess the student’s ability to effectively communicate statistical methods and analysis results with statisticians and non-statistical scientists.
Sarah Schmiege, PhD
Colorado School of Public Health
Office & Hours:
CU Anschutz Medical Campus, Fitzsimons Bldg, 3rd Floor
Monday-Friday, 8:00 a.m.-4:30 p.m.
NOTE: Students considering an MPH in Applied Biostatistics may take either the more advanced sequence (Biostatistical Methods BIOS 6611 or BIOS 6612) or the introductory sequence (Applied Biostatistics BIOS 6601 or BIOS 6602). BIOS 6611 requires the following prerequisites: Calculus 1 and 2 with at least a B; a previous course in applied probability and statistics with at least a B; coursework or experience with a statistical package (e.g. SAS, R, Stata, SPSS); linear algebra is highly recommended and will be used extensively in the course.