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

Biostatistics Shared Resource

V. Shane Pankratz, PhD

Director, Biostatistics Shared Resource

Email Dr Pankratz
Office: CRF G019
Office Phone: 505-272-3718

Administrative Assistant: Jennifer Giannelli
Email: JGiannelli@salud.unm.edu
Phone: 505-925-7478

To acknowledge use of this shared resource, please include the following in your publications:

This research was partially supported by UNM Comprehensive Cancer Center Support Grant NCI P30CA118100 and the Biostatistics shared resource.

The goals of the UNMCC Biostatistics Shared Resource (BSR) are to:

  1. 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.
  2. 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.
  3. 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.
  4. Develop critical statistical methodology when currently available approaches prove insufficient to address the analysis of data from research projects.
  5. 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 UNM 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

Pankratz ImageProfessor 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

Kang ImageAssociate 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 Publications

Luo ImgeAssistant 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 Publications 

Research Professor Internal Medicine
Research Incubator Building, 1st Floor
505-272-4037
E-mail Dr. Davis

Research Interests
Statistical methods in research, Applications of inverse regression in biosensor calibration, Best statistical practices

Education and Training
PhD Statistics, Johns Hopkins Univ
MS Statistics, Univ. of Florida

View Publications

Boyce ImageResearch 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  

Li ImageAssistant Professor of Mathematics and Statistics
Science and Math Learning Center, 308
E-mail Dr. Li

Research Interests 
Bayesian methods, spatial survival analysis, recurrent events modeling, reliability and Bayesian nonparametric priors

Education and Training
PhD Statistics, University of South Carolina
BS Statistics, Wuhan University, China

Associate Research Scientist
Department of Pharmaceutical Sciences
College of Pharmacy
1000 Stanford Blvd.
505-272-7391
E-mail: tozechowski@salud.unm.edu

Education and Training
PhD  Child Development and Family Studies, Purdue University
MS   Human Development and Family Studies, Purdue University

Research Interests
Analyses of clinical processes, mediators, and outcomes in randomized trials; causal modeling and inference; item response theory; Bayesian statistics; mixed-effects and latent variable models for longitudinal data; applications of multiple imputation for missing data problems.

Graduate Research Assistant
Cancer Research Facility (CRF) G-22
Email: XiGao@salud.unm.edu

Research Interests
Survival Analysis, Machine Learning, Big Data Analysis, Statistical Methodology

Education and Training
MS Statistics, University of New Mexico
BS Mechanical Engineering and Minor in Mathematics, University of New Mexico
BE Ship Engineering, Dalian Maritime University

Graduate Research Assistant
Cancer Research Facility (CRF) G-22
Email: wangld@unm.edu

Research Interests
Statistical Genomics, Machine Learning, Statistical Computation.

Education
MS Statistics, University of New Mexico
MS Computer Science, University of New Mexico
MS Chemistry, University of New Mexico
MS Biology, Beijing University of Technology
BE Material Engineering, University of Science and Technology, Beijing

PhD Candidate in Statistics
Graduate Research Assistant
Cancer Research Facility (CRF) G-35
Email: jessieli@unm.edu

Research Interests
Statistical Genomics, Statistical Epidemiology, Statistical Methodology

Education and Training
MS Statistics, University of New Mexico
MS Chemistry, University of New Mexico
MS Pesticide, China Agricultural University
BE Chemical Engineering, Dalian University of Technology

Biostatistics 101 Course

Understanding biostatistics is paramount for cancer research. BIOS 101: Principles of Biostatistics and Data Science for Cancer Researchers at UNM Comprehensive Cancer Center (UNMCCC) is a diverse program presented in a series of nine lectures. The lectures introduce the basic principles of biostatistics and quantitative data science.


There is not a Biostatistics 101 Course scheduled at this time. If you would like to attend one in the future, please email Dr. Huining Kang.

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 October 5. To register, please email the administrative assistant.

*Note: Students wanting to attend only some of the lectures must still register for the course.

Who should take this course?

Clinicians, Fellows, Cancer Researchers, and Cancer Biology Students.

Note: Only UNM Health Science Center employees and faculty are eligible. If you are not a UNM 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: 50% Homework, 50% Attendance. Students must attend a minimum of eight of the 10 lectures to receive a passing attendance grade.

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.