BQRC provides expertise in areas of statistical experimental design, randomization, analysis and statistical and stochastic modeling. Some specific areas of expertise include longitudinal data analysis, design of experiments, modeling of infectious diseases, analysis of data from studies with drop-outs, misclassification, proxy reliability and validity, recurrent count data, and interim analyses of clinical trials, and Bayesian methods.
The Center currently offers support with:
Study Design and Power Analysis. Feasibility study and sample size based on the state of the art methodology such as multi-stage and adaptive designs. In addition, we design and perform randomization, sensitivity and simulation studies to evaluate study design properties, and sample sizes needed to achieve study objectives, endpoints and control selection.
Statistical Analysis. The data analysis plan is provided in the protocol (before data collection takes place) and followed. Assumptions underlying the methods are assessed and the most appropriate statistical method is used for analysis. Beyond major statistical software packages such as SAS, Splus, Stata, StatXact and East, more complex statistical and bioinformatics tool are developed for specific research project (in R or Matlab or SAS).
Interim Analyses and Data and Safety Monitoring for Clinical Trials. Analyses and adaptive designs (including Bayesian designs) consistent with statistical principles for multiple testing and interim analyses.
Biostatistics Training. Introductory seminars are provided on biostatistics tailored to clinical investigators and medical fellows. The goal is to enhance the understanding of biostatistical concepts and thus to improve clinical protocols.
Reports and Publications. Data analysis is typically summarized in a statistical report in a form appropriate for manuscripts.
The center has collaborated extensively with UMB investigators. In Fiscal Year 2010, it has collaborated with over 144 UMB investigators from SOM, SOP, SOD and SON for 257 projects related to their study design and statistical analysis. It leads the biostatistics core for multiple multi-investigator grants. In addition, the center serves as the Statistical Coordination Center for the Randomized, Double-Blind, Placebo-Controlled Multicenter Trial of the Efficacy and Safety of Apricoxib in Combination with either Docetaxel or Pemetrexed in Non-Small Cell Lung Cancer Patients; and statistical analysis center for Predictive and Prognostic Biomarkers and Racial Survival Disparities in Patients Receiving Induction chemotherapy for Locally Advanced Squamous Carcinoma of the Head and Neck From Three Large Randomized Multi-Center Trials.