Excel in analysis with support from the UF Pepper Center Biostatistics Core
The central functions of research design and statistical analysis are concentrated in the Biostatistics Core. Our dedicated team of experts are here to offer a central hub of expertise in a vast array of statistical approaches. We help to ensure that your research journey is backed by solid statistical foundations.
What sets us apart? Research Core 3 (RC3) ensures that research on aging and mobility loss uses appropriate research designs and statistical analysis methods, with special emphasis on validity, efficiency, and simplicity.
- longitudinal data
- missing values
- causal inference
- complex image processing
- dynamic disease screening
- data quality control
- biomarker discovery
- genetics and genomics data analysis
We also serve as the binding agent across all Cores.
Collaboration with All Cores
Our collaboration knows no bounds as we team up with collaborating Cores:
- Pilot and Exploratory Studies Core (PESC): to ensure that appropriate research designs and statistical methods are used in the Older Americans Independence Center (OAIC) pilot, exploratory, and research development studies.
- Research Education Core (REC): to train early-stage faculty and University of Florida OAIC Scholars on the conduct and analysis of research with older adults.
- Clinical Research Core (RC1): to develop data capture systems, forms design, data management, data-quality checking, data security, study design, randomization, and analyses.
- Metabolism and Translational Science Core (RC2): to analyze biomarkers with special attention to correcting skewness and dealing with missing data.
- Digital Health and Artificial Intelligence Core (RC4): to provide statistical analysis of clinical data from the UF Health research data repository and data from real-time online activity or mobility monitoring.
- All OAIC Investigators: to ensure that the valid, efficient, and state-of-the art study designs and data analysis methods are used in all extramurally funded projects.
Join us as we pave the way for impactful and sound research practices. Your journey to research excellence accelerates with support from the Biostatistics Core.
Biostatistics Core
Core 3 Services
Services include support for analysis and research, and best practices for research design.
Types of analyses
- Regression analysis for cross-sectional data
- Time to event data
- Longitudinal data analyses
- Missing data correction
- Causal inference
- Measurement error and misclassification
- Corrections for non-compliance and dropout Intention To Treat (ITT) analysis
- Sample size and power estimations
- Circadian rhythm characterization and summarization
- Image processing
- Dynamic disease screening
- Genetics and genomics data analysis
Examples of services regularly provided
- Adjustment for pre-randomization levels of baseline factors, in order
- Ensure that the analysis will match the design and the estimated variances will not be positively biased
- Adjust for chance imbalances in important prognostic factors not used in the stratification
- Improve the precision of the group comparisons by accounting for that part of the variance due to the variability in the baseline values
- Improve the acceptability of the results and to limit criticism of final publications (that any difference, or lack of differences, was due to chance imbalances in pre-intervention values).
Validity, efficiency, simplicity
The RC3 ensures that studies use appropriate research designs and statistical analysis methods, with special emphasis on validity, efficiency, and simplicity.
- Create operational definitions for outcome variables and other covariates to be measured
- Analyze pilot/exploratory studies to obtain data useful for planning future studies
- Provide pre-study and pre-proposal study design guidance: perform power analyses, calculate appropriate sample size for testing intervention effects, and develop statistical analysis plans
- Generate randomization schemes
- Assist with monitoring of the recruitment, adherence, and retention of subjects for OAIC studies
- Develop and review procedures and forms for data collection
- Design the data-management system to include Web-based applications, prepare and install software at the data collection sites, and train site staff to use the software
- Design and implement quality control procedures for data collection and processing
- Perform appropriate statistical analysis
- Develop new biostatistical methodology for the design and analysis of OAIC studies as needed
- Collaborate with the Research Education Core (REC) to provide training to early-stage faculty and OAIC REC Scholars on basic statistical methods and tools for analyzing data derived from research with older adults
- Monitor and measure protocol deviations and assess their potential impact on OAIC studies
- Assist writing and interpreting statistical results for research dissemination
- Direct connection to other advanced biostatistical resource programs at UF (i.e., CTSI-BERD, BQS at UF Health Cancer Center, BCL in Biostatistics Department) and with other OAICs across the nation.
Core Leadership
