Biostatistics
The UNM Cancer Center Biostatistics Shared Resource (BSR) offers biostatistical collaboration and support for study design, statistical analysis, clinical trials, grant preparation and methodological development. We provide expertise in the design and analysis of genetic studies, including next-generation sequencing, methylation, and gene expression research.
The Biostatistics Shared Resources is located in the Cancer Research Facility (CRF), on the Ground Floor. Phone: 505-925-1119 • Fax: 505-272-2570
Introduction to BIOSTATS101:
Spring 2024 is NOW OPEN for Enrollment
BIOSTATS 101: Principles of Biostatistics and Data Science for Cancer Researchers at UNMCCC is a diverse program presented in a 7-lecture series hosted by the Biostatistics Shared Resource. The lectures introduce the basic principles of biostatistics and quantitative data science. Free to UNMCCC Members, Clinicians, Fellows, Cancer Researchers, and Cancer Biology Students.
Weekly course held by Zoom 4-5 pm MDT
Tuesdays, April 9th-May 21st
Biostatistics Shared Resource
Director, Biostatistics Shared Resource
Email Dr Pankratz
Office: CRF G019
Office Phone: 505-272-3718
To acknowledge use of this shared resource, please include the following in your publications:
This research was partially supported by 猎奇重口Comprehensive Cancer Center Support Grant NCI P30CA118100 and the Biostatistics shared resource.
The goals of the UNMCC Biostatistics Shared Resource (BSR) are to:
- Provide UNMCC members with biostatistical support for clinical trials and the four Research Programs by consulting to develop appropriate research hypotheses and develop efficient study designs, along with determination of appropriate sample sizes for the proposed studies.
- Support Cancer Center Clinical Components, including protocol review and monitoring of clinical trials conducted within UNMCC, and thereby ensuring high data quality, study integrity and patient safety.
- Conduct and summarize statistical analyses, including preparing summary reports, providing up-to-date statistical analyses, and assisting in the preparation of abstracts and manuscripts that will disseminate the knowledge gained through the CCSG research activities.
- Develop critical statistical methodology when currently available approaches prove insufficient to address the analysis of data from research projects.
- Provide education and dissemination about resource technologies and services by offering short course lecture series and workshops on fundamental biostatistical topics for cancer researchers.
The UNMCC Biostatistics Shared Resource (BSR) collaborates with Cancer Center investigators to
- Develop and define appropriate research objectives, hypotheses, and endpoints
- Select efficient study designs
- Determine appropriate sample sizes
- Propose appropriate statistical methods for analyses, including for the interim and final analyses
- Define stopping rules
- Devise blinding and randomization plans for clinical studies
- Plan and write statistical sections of grants and protocols
- Statistical analysis of pilot and study data
- Work with data management staff for efficient database design and quality
Request Biostatistics Support
Request a consultation with the Biostatistics Shared Resource using the form below.
To request support from the Biostatistics Shared Resource, please complete this form. Your request will be reviewed promptly and we will schedule a meeting to discuss your project, including outlining how and when the resource can assist you.
Biostatistics Support
To request support from the Biostatistics Shared Resource, please complete our request form. Your request will be reviewed promptly and we will schedule a meeting to discuss your project, including outlining how and when the resource can assist you.
Guidelines for Working with the Biostatistics Shared Resource (BSR)
- BSR provides support to 猎奇重口Cancer Center members through collaborations in which Biostatisticians become long-term collaborators within research teams through the support of grant funding.
- Any exceptions to this model can be discussed through an introductory meeting with the BSR Director.
- Please provide sufficient lead time for our work. All requests are unique and a precise timeline will be estimated during initial meeting.
Examples of time guidelines are:
- Letter of support for grant application: 1 week
- Internal grant application: 1 month
- External grant application: 3 months
- Statistical analysis for manuscript/abstract/presentation: 1- 3 months
What to expect after request submission:
- Request will be reviewed promptly and investigators will be contacted to set up a meeting to further discuss proposal with assigned statistician.
- Initial meeting will include a discussion outlining how the BSR can assist you, determine a timeline, establish a scope of work.
- All grant proposals that include a BSR statistician require a Grant Proposal Letter of Intent (LOI) for Biostatistical Support signed by the investigator and lead statistician prior to submission
- A Letter of Agreement for Biostatistical Support is completed prior to initiating project work
Biostatistics Faculty and Staff
Professor of Internal Medicine
Director, UNMCCC Biostatistics Shared Resource
Cancer Research Facility (CRF) G19
505-272-3718
Email Dr Pankratz
Research Interests
Statistical genetics and genetic epidemiology, Statistical methods in Epidemiology, Methods for the analysis of Longitudinally Collected Data, Survival Analysis, Risk models and risk prediction
Education and Training
PhD, Statistics, Rice University
MS, Statistics, Brigham Young University
Co-Director, UNMCCC Biostatistics Shared Resource
Director of Clinical Trial Biostatistics
Cancer Research Facility (CRF) G13
505-272-2963
Email Dr. Wu
Research Interests
Statistical methods in cancer clinical trial design, Single-arm phase II survival trial design, Bayesian adaptive randomized umbrella and platform trial design, Group sequential trial design, Screened selection design, Multi-arm multi-stage trial design, Cancer Immunotherapy Trial design, Survival analysis, Likelihood inference, Asymptotic theorem.
Education and Training
Postdoctoral, Fred Hutchinson Cancer Research Center
PhD, Statistics, University of Toronto
MS, Statistics, York University
Associate Professor of Internal Medicine
Cancer Research Facility (CRF) G-17
505-272-4195
E-mail Dr. Kang
Research Interests
Statistical modeling and analysis for high dimensional genomics data, Statistical methods for biomarker evaluation and clinical prediction.
Education and Training
PhD Statistics, University of New Mexico
MS Statistics, University of New Mexico
MS Applied Mathematics, Beijing University of Posts and Telecommunications
BS Mathematics, Beijing University of Posts and Telecommunications
View
Assistant Professor
Cancer Research Facility (CRF) G15
505-272-8704
E-mail Dr. Luo
Research Interests
Statistical genomics and genetic epidemiology, high-dimensional data reduction, next generation sequencing studies, genome wide association studies, gene-set/pathway analysis, genomic clinical trials
Education and Training
PhD Public Health (Biostatistics), The University of Texas School of Public Health
MS Mathematics, Fudan University, China
BS Applied Mathematics, Wuhan University, China
View
Research Scientist
Cancer Research Facility (CRF) G-22
505-272-9578
E-mail Boyce
Research Interests
Health disparities, population- based research, survey research, and nutritional epidemiology.
Education and Training
MPH Epidemiology/Biostatistics, Tufts University School of Medicine
MS Nutrition, Tufts University Friedman School of Nutrition Science and Policy
BA Biochemistry, Knox College
Research Scientist
Cancer Research Facility (CRF) G-22
505-272-6038
E-mail Kosich
Research Interests
Health equity, environmental epidemiology, statistical methods in epidemiology
Education and Training
MPH Epidemiology, University of Pittsburgh
BS Chemistry, Harvey Mudd College
BS Sociology, Harvey Mudd College
Research Scientist
Cancer Research Facility (CRF) G-22
Email: dkanda@salud.unm.edu
Research Interests
clinical trials, population-based research, environmental epidemiology, statistical methods in research
Education and Training
DrPH Biostatistics, Georgia Southern University
MPH Biostatistics, Georgia Southern University
B.Pharmacy, Ahmadu Bello University, Nigeria
Biostatistics 101 Course
Understanding biostatistics is paramount for cancer research. BIOSTATS 101: Principles of Biostatistics and Data Science for Cancer Researchers at UNMCCC is a diverse program presented in 7-lecture series hosted by the Biostatistics Shared Resource. The lectures introduce the basic principles of biostatistics and quantitative data science and are intended for Clinicians, Fellows, Cancer Researchers, and Cancer Biology Students who are interested in engaging in research, in the process of learning biostatistical applications, or for those who desire a refresher course. Types of data, descriptive statistics, estimation, hypothesis testing, correlation/regression, survival analysis, sample size calculation, and guidelines for statistical genomic data analysis will be taught in this course series.
Next course will run weekly from April 9th to May 21st, 2024. For questions, email tboyce@salud.unm.edu.
Understanding biostatistics is paramount for cancer research. BIOS 101: Principles of Biostatistics and Data Science for Cancer Researchers at 猎奇重口Comprehensive Cancer Center (UNMCCC) is a diverse program presented in a series of seven lectures. The lectures introduce the basic principles of biostatistics and quantitative data science and are intended for those who are interested in engaging in research, in the process of learning biostatistical applications, or for those who desire a refresher course.
Questions? E-mail to tboyce@salud.unm.edu (Tawny Boyce).
This course covers basic statistical methods.
The lectures are intended for those who are in the process of learning biostatistical applications or for those who desire a refresher course. This course will cover:
- types of data
- descriptive statistics
- estimation
- hypothesis testing
- correlation/regression
- survival analysis
- sample size calculation
- guidelines for statistical genomic data analysis
Some classes will introduce basic theory and its application using computing tools or free software.
Course Goal
The goal of this class is to introduce the basic statistical concepts and methods for cancer research.
Course Format
The course will consist of both lecture and hands-on instruction. The lecture materials (slides) will be posted before each class.
Registration Policy
There is no fee for this lecture series. However, students should be registered before April 5, 2024, via email to tboyce@salud.unm.edu (Tawny Boyce).
*Note: Some students may want to take only selective lectures, please specify this request when registering
Who should take this course?
Clinicians, Fellows, Cancer Researchers, and Cancer Biology Students.
Note: Only Health Science Center employees are eligible. If you are not a 猎奇重口HSC faculty or staff member, please contact the Coordinator prior to the registration deadline.
Course Prerequisites
None
Credit policy
No credit for this course.
Homework
Students will receive a homework assignment of 5 questions each week. The homework assignment will be counted as a test to gauge the student’s understanding of the material.
Grade
The Pass or Fail grade will be calculated as follows: Homework (6 of 7) AND Attendance (6 of 7) = Pass.
Certification
Students who complete and pass the course will be awarded a certificate.
Course evaluation
At the end of each class, students are requested to fill out and submit an evaluation form for the lecture.