STATISTICAL PROGRAMMING

At Selsoft, we offer a niche statistical programming service to ensure proper statistical analysis and reporting are reliable with the study protocol, the statistical analysis plan, and compliance with sponsor processes. Our experts have extensive experience in industry standard statistical programming languages and keep current with the latest statistical techniques in the literature, as well as those accepted by the regulatory authorities across the globe (FDA, EMA, Japan, etc..).

We can provide a range of services to support statistical programming needs, including:

Statistical programming:

This involves writing and testing programs for analyzing clinical trial data, including the development of tables, listings, and figures for clinical study reports.

Statistical analysis plan (SAP) development:

This involves developing a detailed plan for statistical analysis, outlining the methods, procedures, and techniques that will be used to analyze the data collected in a clinical trial.

Data summaries and exploratory analysis:

This includes generating descriptive statistics, graphical displays, and exploratory data analysis to understand the characteristics of the data and identify trends, patterns, and potential outliers.

Inferential analysis:

This includes hypothesis testing, confidence intervals, and other statistical methods to draw conclusions about the study population and the effect of the intervention.

Subgroup analysis:

This involves analyzing data by subgroups to explore differences in treatment effect and to identify potential factors that may influence treatment response.

Safety data analysis:

This involves analyzing safety data, such as adverse events, to assess the safety profile of the study drug or device.

Survival analysis:

This includes analyzing time-to-event data, such as overall survival or progression-free survival, to assess the efficacy of the intervention.

Bayesian analysis:

This involves using Bayesian methods to analyze data, which can provide more informative and interpretable results than traditional frequentist methods.

Meta-analysis:

This involves combining data from multiple studies to provide a more comprehensive assessment of the efficacy and safety of a treatment.

Simulation and modeling:

This involves using statistical models to simulate and predict outcomes based on different scenarios and assumptions, which can be useful for decision-making and planning.

These micro services can be combined and customized to meet the specific needs of each client and study, and Selsoft can provide expertise and guidance in selecting the appropriate statistical methods and techniques for each analysis.