Our familiarity with biostatistics means we not only perform any standard analysis and plot using your clinical data, but also advise when your data demonstrate peculiarities that may require either additional analyses or post-estimation diagnostics, and even alternate methods—additional steps that have become increasingly important to getting your research or case description published. QandQ’s statistical consulting team also includes former academic journal editors, who know well that even the medical journals are now relying on peer reviews from methodologists in addition to the expert reviews of academics and clinicians.

QandQ can provide this specialized expertise at exactly the level you require. Because of our extensive work with clinicians, PhD-MDs, public health academics, and epidemiologists, we match you with the right team of academics and methodologists to perform the most rigorous analysis that your data will allow. While many of our biostatistics clients come to us with some level of familiarity with statistical analysis, QandQ team draws on our extensive experience to review and refine study designs so that enough data (and the right kind of data) are collected for clear and rigorous results.

In our biostatistics and epidemiological consulting work, at QandQ we provide a customized consulting and analysis service to every client: hospitals, government agencies, academic and research institutions, private corporations, and individual investigators. Drawing on a team of highly skilled biostatisticians and epidemiologists from an elite group of professors and academic researchers, our biostatistics and epidemiology division offers consultations and expertise on a range of relevant areas throughout the research and clinical trial processes, including effective data safety monitoring.

Because we understand the importance of ensuring a sound research design at the start of the process to ensure robust analyses and findings, our statistical consulting support is tailored to clients’ current needs and progress in the research and data collection process. In the early stages of development, these services include the following:

• Grant research, writing, and editing (including literature search)
• IRB submission
• Protocol review
• Methodology review and design
• Statistical sampling and validation
• Questionnaire/interview protocol development and expert review
• Feasibility analysis
• Pivotal study design for 510(k) applications

Once initial research and/or clinical trials are completed, we also provide assistance in the following areas:

• Statistical analysis and interpretation for any and all typical analytical procedures used in biostatistics research, such as:
  • Kaplan-Meier Survival Analysis
  • Cox Regression
  • Structural Equation Modeling (as implemented in MPLUS, AMOS and LISREL)
  • Multilevel Linear and Nonlinear Models
  • Bayesian Analysis based on Markov Chain Monte Carlo methods
  • Meta-analysis
  • Knowledge graphing for “big” dataset development (public health, epidemiology)
  • Machine learning estimation techniques for large scale and high dimensional public health and epidemiological datasets
• Additional support with qualitative analysis for any mixed methods studies or follow-up qualitative research (open-ended questionnaires, focus groups, or interviews)
• Manuscript editing based on journal reviewers’ feedback
• Third-party validation

Past and current clients include clinicians and investigators at the Cleveland Clinic, the Mayo Clinic, professors at schools of public health in some of the top research universities in the US, as well as numerous private practice clinicians working in most every field of medicine as well as veterinary medicine in the US, Europe, Australia, Qatar, India, South America, and Saudi Arabia.

Recent projects include the statistical analysis for a prestigious medical school’s large-scale study on the risks faced by organ transplant centers. We also consult regularly for groups of clinicians and individual investigators at the top research clinics in the US, including but not limited to Cleveland and Mayo, for the survival analysis and Cox regression analysis of multiple clinical datasets, meta-analyses including the development of large datasets for decades of research studies across numerous medical journals, and epidemiological inquiries using big data and cutting edge techniques such as knowledge graphing and random forest estimation.