At Statistician Next Door, I offer professional statistical consulting services to a variety of clients. My goal is to collaborate with each client to identify their specific needs and provide tailored services. Whether you are a company, researcher, or student, I can help by advising you on your statistical needs and/or performing the data analysis for you. My services include:
- Companies: Through data analysis, I can help you understand your current performance, predict future outcomes, and support your decision-making using advanced statistical techniques and data visualization tools.
- Researchers: I can assist in defining a clear and feasible research question, selecting appropriate statistical methods, and performing the data analysis. Additionally, I can help you interpret the results, report the findings, and communicate the implications of your research.
- Students: I can tutor you in the programming language R and explain concepts and applications of statistics through online tutoring. I cannot provide solutions for graded assignments.
- Custom Services: Please contact me with your statistical problem, and I might just be able to help you.
I am using the R programming language for all statistical analysis and can advise you on your own analysis in R as well.
Contact me today and let me help you with your data analysis needs.
About Me
I am your Statistician Next Door, a Peruvian-German native who studied mathematics and statistics in Germany and the Netherlands, and is currently residing in beautiful Austria with her family of three.
During my master’s studies, I gained initial experience in statistical consulting through coursework and an internship at the Leiden University Medical Center (LUMC). The results of this internship helped secure funding from the KWF Dutch Cancer Society for my PhD research at the Mathematical Institute of Leiden University, during which I closely collaborated with researchers from the LUMC as part of the Data Analysis and Survival for Personalised Oncology group. Apart from conducting my own research, I also provided consulting services to researchers at the LUMC. My dissertation was awarded the C.J. Kok Jury Award for best thesis by the Faculty of Science at Leiden University. After obtaining my doctorate, I pursued a postdoc at the Erasmus University Medical Center, where I provided consulting services to medical researchers as well.
My enjoyment of working on consulting projects inspired me to start my own statistical consulting business. This venture combines my desire for helping people, my passion for statistics, and the autonomy that comes with self-employment.
I am a native German speaker, but have done consulting work in English and Dutch, and have a conversational level in Spanish. I hope I can make you feel comfortable by communicating in your own language. Especially in statistics, communication is so important!
- Biostatistics
- Generalized linear models
- Mixed-models
- Survival analysis
PhD in Statistics
Universiteit Leiden, NL
MSc in Statistics
Universiteit Leiden, NL
BSc in Mathematics
Universität Bremen, DE
Advanced statistical models in medicine
I was part of the development of this important Personalized Sarcoma Care (PERSARC) prediction tool, with the aim of improving care of patients with high-grade soft tissue sarcoma. Multiple statistical models have been developed and updated as the project grew larger and more international Data could be collected. The models are available for clinical practice through an app for androis and ios.
Mar 15, 2021
I contributed to several projects that applied multi-state models to clinical data. One key project focused on identifying risk factors for patients with Ewing sarcoma. A multi-state model, like the one shown on the left, can capture multiple health events a patient may experience. It allows for the modeling of risk factors associated with each transition between different “states” in a patient’s health journey. Additionally, such models enable predictions for individual patients, helping inform clinical decision-making.
Aug 6, 2019
A dynamic prediction model for survival of patients with soft tissue sarcoma. After surgery patients can experience disease related events, such as local recurrence (LR) that change their predicted probability of survival. Even without experiencing such events, the fact that a patient is alive at e.g. 1 year past surgery, can have an effect on his survival probability. A dynamic prediction model is able to model the patient journey as they unfold in clinical practice. On the left, Panel C of Figure 2 shows how these probabilities change over time for a particular patient (Figure 2C. 5-year probability of death estimates for patients with different characteristics and at different states of disease progression (Rueten-Budde et al., 2018). Reprinted from Surgical Oncology, 27(4), 695-701.(https://doi.org/10.1016/j.suronc.2018.09.003)).
Sep 7, 2018
Rates depend on the type of work and the size of the project. After receiving the details of your project, I will send an offer and a timeline within a couple of business days.
To request my service, please email me a summary of your project or problem at info "at" statisticiannextdoor.com. In particular, please include the following information:
- Brief summary of project
- Project goal: what do you expect as outcome of this project?
- Type of analysis if already known
- Timeline: is there a specific deadline you are working towards?
Do not send any data by email!
Within a few business days, you will receive a tailored offer with a price and timeline indication.
Once you give the green light, we can move forward with our collaboration.