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Biostatistics
Biostatistics

Welcome to the Ƶ Division of Biostatistics

While most people feel the volume of data and information that is generated through research, clinical trials, experiments and surveys is overwhelming, our faculty and staff views each data point as a vital piece to a life-changing puzzle. By carefully organizing and categorizing each insight, we are laying a strong foundation for the future of medical research. The Biostatistics division of MCW’s Data Science Institute is focused on harnessing the power of “Big Data” to design and support cutting-edge clinical trials, experiments and surveys; architect research grant proposals; and develop new treatments to improve healthcare and change the lives of patients and their families.
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Research

Discover the many research opportunities that are available within the Biostatistics PhD program.

Learn about our research
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Education

Our Biostatistics PhD program is a highly collaborative unit that is integral in the design of numerous research projects within MCW and its affiliates.

Learn about our Biostatistics PhD Program
Epidemiology Data Resource Center (EDRC)

About Biostatistics

The Division of Biostatistics is committed to helping health scientists, students, and community members conduct and understand specialized statistical analyses.

Learn about our division
Biostatistics Consulting

Consulting Service

We offer a vast array of biostatistical consulting services to both internal and external partners.

Learn about our Bioconsulting Service

Statistical Resources

Need statistical help? Utilize our statistical resources or contact the Biostatistics Consulting Service.
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Statistical Software by Faculty and Collaborators

Opening documents:
Left-click to open documents.
If left-click does not work, try right-clicking and "save-as" or "open in new".

If you have any software questions or are having trouble downloading, then please email Dan Eastwood (eastwood@mcw.edu) with the name of the file you need and I will email it to you directly.

November 2013

July 2011
Linear & Logistic Mixed Model Implementation

Manual (PDF)
Makefile
Normal.h
Normal.c
Normal-Uniform.h
Normal-Uniform.c
Logistic.h
Logistic.c
Logistic-Uniform.h
Logistic-Uniform.c
Onetime.h
Onetime.c
gls_cholmod.h

January 2011
SAS macros for estimation of direct adjusted cumulative incidence curves under proportional subdistribution hazards models

CIFCOX (TXT)
CIFSTRATA (TXT)

January 2009
Truncated normal sampler (TXT): For generating truncated normal random variates. A text file containing R functions for implementing, testing and comparing a new rejection sampler with the inverse CDF method
August 2008

CHANGEPOINT (TXT): For the implementation of the Cox-type regression on cumulative incidence function with a time change-point by Xiaolin Fan, PhD
CHANGEPOINT Readme (PDF): Quick reference guide

CIF
: (TXT)For the implementation of estimated cumulative incidence function without covariates under the competing risks setting by Xiaolin Fan, PhD.
CIF Readme: (PDF) Quick reference guide
CIFCOX (TXT): For the implementation of the Cox-type regression on cumulative incidence function under the competing risks settings by Xiaolin Fan, PhD
CIFOX Readme: (PDF): Quick reference guide

TWOLEVEL
 (TXT): For the implementation of the two-level hierarchical for the Cox-type regression on cumulative incidence function under the competing risks setting by Xiaolin Fan, PhD
TWOLEVEL Readme (PDF): Quick reference guide
March 2008

STRUCTDPM: (TXT) C code for implementing bayesian semiparametric modeling of genetic association studies of quantitative traits in the presence of population stratification
Instruction file for program: STRUCTDPM_readme (PDF)
See also: Tech Report 55 (PDF)

August 2007 
SAS macro for adjusted survival curves: (TXT)
Instructions: A SAS Macro For Estimation Of Direct Adjusted Survival Curves Based On A Stratified Cox Regression Model (PDF): by Xu Zhang, Fausto R. Loberiza, John P. Klein, and Mei-Jie Zhang.
July 2007
SAS macros to find pseudo-values for censored data (TXT)
R functions to find pseudo-values for censored data (TXT)
Instructions for pseudo-value functions/macros:
SAS and R Functions to Compute Pseudo-values for Censored Data Regression (PDF) by John P Klein, Mette Harhoff, Per Kragh Andersen, and Sergey Tarima

SAS Macro for the Additive Hazards Model (TXT)
Quick Reference Guide To Additive Macro (TXT)

SAS Macro for the Semiparametric Gamma Frailty Model (TXT)
Quick Reference Guide To Gamma Frailty Macro (TXT)

SAS Macro for the Semiparametric Positive Stable Frailty Model (TXT)
Quick Reference Guide To Positive Stable Frailty Macro (TXT)

SAS Macro for Score Test of Homogeneity for Survival Data (TXT)
Quick Reference Guide to Score Test of Homogeneity for Survival Data (PDF)

SAS Macro For Cumulative Incidence Functions (TXT)
Quick Reference Guide To SAS Macro For Cumulative Incidence Functions (TXT)

SAS Macro to Estimate Haplotype Frequencies under the Assumption of Hardy-Weinberg Proportions (HAPEM)
Quick Reference Guide to the HAPEM macro (DOCTXTPDF)

Biostatistics Lecture Series Videos

Past Biostatistics lectures are available for viewing on the . Currently there are over 20 educational videos ranging from basic statistical topics to more advanced topics, such as Survival Analysis.

Video Topics & Abstract Brochure
Contains the entire listing of Biostatistics lecture videos and abstracts.
Printable Video Topics & Abstract Brochure (PDF)

Video Topics, Abstracts, YouTube Links, PowerPoints
Below you can find the full listing of video topics, abstracts, direct video links to YouTube, and each lecture's accompanying PowerPoint.

Analyzing Discrete Data: Describing discrete (categorical) data; graphical display; measure of association for binary outcomes; risk difference, relative risk, odds ratios; tests of association; Chi-square tests; Fisher’s exact test; introduction to logistic regression model View Analyzing Discrete Data presentation (PDF)

ANOVA: Comparing More Than Two Treatments: Techniques for comparing the mean responses of two or more treatment groups (one way ANOVA); comparison of two factors (two way ANOVA); multiple comparisons View ANOVA presentation (PDF)

Basic Concepts of Bayesian Statistics: What is Bayesian statistics; interpretation and assignment of probability; calibration of probability; conditional probability; Bayes Theorem; prior, posterior and predictive distributions; inference and prediction conditioned on full information; when Bayesian methods are particularly useful; individualized medicine; hierarchical and complex stochastic modeling; pooling of information; substantial extra-data information; adaptive clinical trials. View Basic Concepts of Bayesian Statistics presentation (PDF)

Biostatistics Questions & Database Basics: Resources available in the Biostatistics Consulting Service; basic questions when planning a study; basic concepts of how to create a research database; types of data; spreadsheet vs. database View Biostatistics Questions & Database Basics presentation (PDF)

Choosing Statistical Software: Introduction to some of the most commonly used statistical packages; comparison of the capabilities, availability, cost, and ease of use of the packages View Choosing Statistical Software presentation (PDF)

Common Errors in Linear Regression: Linear regression components, use graphs to check linear regression assumptions, linearity, constant variance, normality, outliers, multicollinearity, remedies View Common Errors in Linear Regression presentation (PDF)

Concepts on the Way from Data to Decisions: Hypothesis formulation; study-to-study variation; tests of hypothesis; type I and II errors; confidence intervals; planning a study View Concepts on the Way from Data to Decisions presentation (PDF) | View Applets (XLSX)

Designing Clinical Trials: Dose-finding phase I designs; phase II designs; determination of sample size; the use of two stage designs View Designing Clinical Trials presentation (PDF)

Getting Help for Your Biostatistics Questions & Database Basics: Resources available in the Biostatistics Consulting Service; basic questions when planning a study; basic concepts of how to create a research database; types of data; spreadsheet vs. database View Getting Halp for Your Biostatistics Questions & Database Basics presentation (PDF)

Introduction to Survival Analysis: Censoring and truncation; Kaplan-Meier estimators; log rank tests; competing risks; cumulative incidence functions View Introduction to Survival Analysis presentation (PDF)

Introduction to Survival Analysis (11.8.13): Survival analysis; time-to-event data; event of interest in studies (e.g. death, recurrence of disease, development of complications after treatment); methods for partial data; regression methods; methods used to analyze competing risks data View Introduction to Survival Analysis (11.8.13) presentation (PDF)

Logistical Regression: Simple logistic regression models for binary data; interpretation of regression coefficients in simple logistic regression; multiple logistic regression models; estimation and inference for logistic regression models; odds ratios; models for association; models for prediction/classification
View Logistical Regression presentation (PDF)

View Logistic Regression presentation (PDF)

Longitudinal Analysis: Longitudinal studies; design for longitudinal studies; analysis for longitudinal studies; correlation between measurements; statistical methods to address correlation; missing data mechanism View Longitudinal Analysis: Longitudinal Studies presentation (PDF)

Matched Studies in Medical Research: The use of retrospective and prospective matching; Methods for comparison of treatment in matched studies with binary or continuous outcome; paired vs. unpaired t-tests; McNemar’s test View Matched Studies in Medical Research (PDF)

Multiple Comparisons: Problem of multiple testing; familywise error rates; false discovery rates; multiple testing strategies; subgroup analysis; interim analysis View Multiple Comparisons presentation (PDF)

Paired Data Analysis: Paired t-test; Sign Test; Wilcoxon Sign rank test; McNemar’s test
View Paired Data Analysis presentation (PDF)

Propensity Scores: Definition of propensity score; the background and motivation of developing propensity score method; propensity score estimation method; propensity score matching; estimating treatment effect using propensity including matched pair analysis and regression adjustment and stratification
View Propensity Scores presentation (PDF)

Reading Medical Literature: The main parts of a statistical paper; review of basic statistical concepts; reading the statistical methods and results section.

Methods for Equivalence and Non‐Inferiority Testing: Equivalence tests: tests designed to show two treatments have the same mean outcome; non-inferiority tests: tests to show a new treatment performs no worse than an existing test; confidence interval based tests

Simple Statistics & Graphics in Excel: Data entry; descriptive statistics (mean, median, etc.); statistical inference (t-test, ANOVA, regression); how to create and enhance graphs (line, pie, bar) in Excel View Simple Statistics & Graphics in Excel presentation (PDF)

Simple Statistics in Excel: Entering and managing data in Excel; descriptive statistics; statistical inference in Excel including t-test, simple regression models; data analysis add-in View Simple Statistics in Excel presentation (PDF)

Statistical Consideration in Grant Writing: Specific aims and hypotheses; specifying the study population; selecting a study design; defining outcome measures; sample size calculations; data analysis plan View Statistical Considerations in Grant Writing presentation (PDF)

Statistical Graphics in Excel: Types of graphs in Excel: pie charts, bar charts, histograms, line graphs, scatter diagrams; properties of a good graph; modifying default graphs 

Statistics, Probability & Diagnostic Medicine: Sensitivity; specificity, positive and negative predictive value; the likelihood ratio; the ROC curve View Statistics, Probability & Diagnostic Medicine presentation (PDF)

Simple Linear Regression: Simple linear regression; fitting a line to data; interpretation and prediction; confidence intervals and hypothesis testing; measuring the strength of association; model checking; binary predictions View Simple Linear Regression presentation (PDF)

Uses and Abuses of Non‐parametric Statistics: The sign and sign rank test for paired data; the Mann-Whitney Wilcoxon test for unpaired data View Uses and Abuses of Non-parametric Statistics presentation (PDF)

Web-Based Sample Size Calculation: Statistics hypotheses, significance level and statistical power; free online website for sample size and power calculations View Web-Based Sample Size Calculation presentation (PDF)

Writing a Protocol: Protocol rational for prospective and retrospective studies; elements of a protocol View Writing a Protocol presentation (PDF)

Datum-Biostatistics Newsletter
The Datum newsletter has been discontinued until further notice. 

Datum is the Biostatistics newsletter Key Function of the Clinical and Translational Science Institute (CTSI). Within an issue of Datum you will find in-depth descriptions of featured databases, statistical articles, examples of our collaborative work, illustrations of statistical methods you can use in your research or in understanding the literature, information about useful websites...and more!
Biostatistics YouTube Page

Past Biostatistics lectures are available for viewing on the . Currently there are over 20 educational videos ranging from basic statistical topics to more advanced topics, such as Survival Analysis.

SAS Installation Information
The Research Computing Center, available on InfoScope, administers MCW's site license for SAS.
Survival Analysis Techniques for Censored and Truncated Data

Preface (PDF)

SAS Macros
Errors (PDF) (First Edition)

Data Sets (txt files):

UNIX Help
How to convert DOS to UNIX files?
Use the command: dos2unix
Also: Use UNIX2DOS for converting UNIX to DOS file

Biostatistics Basic UNIX commands (PDF):
Printing in UNIX.
Using a USB drive from a SunRay terminal.
Changing the priority of a process.
Terminating processes using "kill".
Cleaning up SAS files and backup files.

CAPS' SAS Training and other resources
The Center for Advancing Population Science (CAPS) has additional available resources.
Biostatistics wiki

Contact Us

Division of Biostatistics
8701 Watertown Plank Rd.
Medical Education Building
MEB M1400
Milwaukee, WI 53226
(414) 955-8280

 

PhD Program
Medical Education Building
phdbiostatistics@mcw.edu

Biostatistics Consulting Service
Medical Education Building
consult@mcw.edu

Data Science Institute
8701 Watertown Plank Rd.
TBRC 4th Floor, Suite 4150
Milwaukee, WI 53226
dsi@mcw.edu
Department of Biostatistics Google map location