Observational Studies

Analyzing real-world, observational data requires specialized statistical skills. Our biostatisticians work closely with RTI-HS outcomes researchers to design and analyze data from a wide range of study types, including surveys, cross-sectional or longitudinal non-interventional studies, registries, chart abstractions, and electronic medical records (EMRs). 

Registry and Database Analyses

Our biostatisticians have experience with multiple real-world data sources including electronic medical records, administrative claims, and registries and are knowledgeable in the unique designs and statistical techniques necessary to analyze studies using these types of data sources. Our researchers have the necessary expertise to define exposure, covariates, and outcomes, and to account for censoring and missing data. These observational studies require special consideration to address potential confounding, typically using methods such as propensity scores, when estimating risk measures of association. In addition, we assist researchers with assessing the best methods to achieve study objectives and can support interpretation of results and examination of potential biases so that you can be confident in using your results to make informed decisions.

Survey Analyses

Whether it is a simple survey or a complex multi-stage survey design, our statisticians have extensive experience in the planning and analysis of surveys including survey sampling and weighting.  We understand that analyses of complex sample surveys require the use of appropriate statistical software that accounts for the sample design so that the results accurately answer your research questions about the population of interest.