Hello friends! I love to wrangle data and conduct sophisticated analyses to develop models that inform decision making. I'd love to help your data tell it's story!
Research Strategy is a big part of the overall research plan. It describes the rationale for the research and the experiments used to accomplish each specific aim. It addresses Significance, Innovation, and Approach around each specific aim. Further it addresses Preliminary Studies, Progress Reports, or other sections related to Human Subjects, Vertebrate Animals, Select Agents, and others. Research Strategy addresses the big picture: Can your research move your field forward?
We are passionate about data science and want to help your research or business! We can help with the following: Selection of research design and data collection methods. Whether questionnaires, surveys, observational, or data from documents and records, we can recommend and help with a research design and data collection method that affords you the best opportunity to address your research or business objectives. Research data organization, secure storage, and sharing.
Biostatistics and Reporting are a critical part to any regulated clincal trial. We have master the use of RStudio in combination with SAS (for 21 CFR Part 11 compliant aspects) to support Phase I and Phase II clinical trials as a Statistical Programmer and Regulatory Biostatistician. We can support these major areas: Study design and protocol development Statistical Consulting Sample Size Calculations Randomization Schemas Statistical Analysis Plans (SAP) Data Safety and Monitoring Board (DSMB) Support Study Design and Protocol Development We are experienced with the knowledge to develop optimal trial designs and write protocols for clinical development programs.
We leverage Reproducible Research, which… ties specific instructions to data analysis and experimental data so that scholarship can be recreated, better understood and verified. Packages in R for this purpose can be split into groups for: literate programming, package reproducibility, code/data formatting tools, format convertors, and object caching. The primary way that R facilitates reproducible research is using a document that is a combination of content and data analysis code.