3 D Statistical Learning  

1. Discovery Call (30 minutes)

•  Initiate the process with a virtual, complimentary discussion to delve into your data landscape and understand the intricacies of the problem at hand.
• Uncover your needs and expectations to tailor our approach accordingly. 

2. Problem Definition and Quantification:

• If the problem isn’t crystal clear, we work collaboratively to quantify it, ensuring a precise understanding.
• Specify research questions to crystallize the focus of our analysis.

 3. Hypothesis Formulation:

• Conduct an in-depth data exploration to inform hypothesis formulation.
• Translate insights into quantifiable hypotheses, laying the foundation for a strategic approach.

 4. Sophisticated Data Analysis:

• Leverage state-of-the-art statistical software and methodologies to conduct a rigorous analysis.
• Apply advanced statistical methods to extract meaningful patterns and correlations.

5. Customized Reporting:

• Craft bespoke reports and dashboards that provide a clear and visually compelling representation of the analyzed data.
• Ensure the presentation aligns with your organizational objectives and communication preferences.

6.  Results Delivery and Assessment:

• Present the results comprehensively, walking you through the discovered insights and their implications.
• Facilitate an interactive assessment, gathering your feedback to refine our findings further.

Individuals and organizations seeking to derive valuable insights from data encompass our potential client base. The following are examples of common clients we serve:

• Pharmaceutical Industries and Contract Research Organizations (CROs): Engaging in statistician tasks, including Statistical Analysis Plan development.
• Medical Device Companies: Providing statistical and analysis planning support for medical device trials.
• Doctoral Students, Medicine Students, Epidemiology Students, Psychology Students, etc.: Offering statistical analysis services for their theses.
• Master and Bachelor Students: Assisting in the statistical analysis and comprehension of their master’s and bachelor’s theses.
• University Chairs: Collaborating on statistical modeling initiatives.
• Research Institutes: Providing statistical consulting services.
• Student Groups: Conducting specialized training in statistics, R, SAS, or machine learning.
• Industries: Delivering continuous statistical and machine learning training for ongoing professional development.

Our expertise ranges from the design of clinical phase I-IV trials (statistical input to study protocols, writing of statistical analysis plans, randomization, sample size calculation) and data analysis with SAS and R.  High quality standards are ensured by independent validation (e.g. independent review, code review or double programming). Our statistics experts supported numerous clients in submissions to FDA and EMA.

I have solid experience in  complex study designs (e.g. adaptive, Bayesian BLRM, outcome depending switching/crossover, biomarker) and the implementation of complex methods in macros (RPSFT, IPE, IPCW). 

In summary, here are my services:

• Clinical trial planning (phases I-IV)
• Trial and project statistician tasks
• Sample size calculation
• Randomisation (including emergency envelopes)
• Statistical programming with SDTM and ADaM (SAS, R)
• Validation (e.g. SAS: source code review, double programming)
• Interim analyses
• Survival analysis

For the analyses, CDISC standards with ADaM datasets are used to ensure traceability, reproducibility, and compatibility across studies. If necessary, I consult on the anonymisation of clinical data.