Statistical Analysis in Medicine: A Practical Blog for Doctors and Researchers

This blog is the result of many years of working with doctors, PhD candidates and medical researchers.

The idea of creating a blog about statistical analysis and medical statistics did not appear overnight.

The Idea for This Blog Had Been Developing for Years

The idea of creating this blog about statistical analysis and medical statistics did not emerge suddenly. It grew out of many years of working with doctors, PhD candidates and researchers who repeatedly came to me with a very similar problem.

They had a well-designed study and valuable data, often collected through months or even years of demanding work. Yet the statistical analysis did not produce satisfactory conclusions, or the methods used were questioned during the publication process.

The topics discussed on this blog therefore arise directly from the real problems I encounter in my everyday work.

Over time, I began to notice a recurring pattern. Statistical analysis for medical research was often treated as the final stage of a project—something that simply had to be completed, frequently under considerable time pressure.

In reality, statistical analysis plays a crucial role in determining whether study results will be considered reliable and whether a manuscript will successfully pass peer review.

This blog was created at the point where good medicine meets properly conducted statistical data analysis. It is a place where I want to show what medical statistics looks like in practice and how it can be used consciously and effectively throughout the entire research process—not only after the data have already been collected.

Important methodological decisions should be made during the study-planning stage. These include determining the appropriate sample size, designing the database, deciding how variables will be collected and considering the potential expectations of reviewers and scientific journals.

This is how research is conducted in reputable academic institutions, and it is this approach that I want to present on this blog.

This Is Not Another Statistics Textbook

This blog is not intended to be another statistics textbook.

You will not find an encyclopaedic collection of definitions or an exhaustive theoretical review of statistical methods here. Specialist textbooks already fulfil that role, and relevant sources will be provided whenever appropriate.

Nor will this blog reduce statistical analysis to oversimplified rules such as “always use test X.” In medical statistics, this type of approach frequently leads to methodological errors and problems during the publication process.

This will also not be a collection of theoretical discussions detached from research practice. Statistical analysis for scientific research is valuable only when it addresses genuine research questions.

That is why this blog will focus on real problems encountered in medical and clinical research.

This Blog Is Based on My Professional Experience

This will be a practical and focused blog about statistical analysis in medicine, based on real research projects and genuine methodological challenges.

I want to explain:

• how to make appropriate statistical decisions in specific research projects;
• how to apply medical statistics in accordance with current publication standards;
• how to prepare a statistical analysis for a scientific paper so that it can withstand peer review.

I am not interested in simply repeating basic definitions. I am interested in the point at which genuine doubts and methodological questions arise:

• Was the statistical analysis performed correctly?
• Is the statistical methodology described clearly enough in the manuscript?
• Do the results of the statistical analysis lead to conclusions that are clinically meaningful?

A properly conducted statistical analysis helps determine whether a research hypothesis is supported by the data and what the findings mean for the safety and effectiveness of patient care.

Statistics should not be reduced to artificial examples, such as calculating the average number of legs of a person walking a dog. In medical research, statistical decisions have real consequences.

Why I Believe This Blog Is Worth Creating

I sincerely admire every doctor who, in addition to the demands of caring for patients, decides to undertake scientific research.

My husband is a doctor, so I have had the opportunity to observe many of the difficulties—and sometimes absurdities—that accompany both clinical work and academic research. This has also helped me understand the time limitations and practical challenges faced by medical professionals.

When I established Statystyka dla Ciebie, I treated the company as my own project from the very beginning—a place that would operate according to my principles.

I drew on more than ten years of experience in managerial positions within an international corporation, where working with data and explaining numbers in accessible language were part of my everyday responsibilities.

This professional experience allowed me to apply, verify and further develop the knowledge I had gained while studying Quantitative Methods and Information Systems at the SGH Warsaw School of Economics.

The name of the programme may sound intimidating, but its practical purpose is straightforward: learning how to work with data, understand numbers and use them to support informed decisions.

I know how valuable doctors’ time is. I also understand that most medical professionals have not received extensive training in statistics and may approach statistical concepts differently from people with a quantitative background.

My goal is therefore to help doctors and researchers understand medical statistics and use it effectively in practice. Unfortunately, statistical analysis is rarely completely straightforward. In many cases, there is no single automatic or universally correct answer.

Throughout my career, I have seen many excellent research projects in which statistical analysis was the weakest element. This was not because the study itself had been poorly designed, but because medical statistics had been treated as an additional requirement—or even as a necessary evil.

I have also seen how a carefully planned and properly conducted statistical analysis can completely transform the quality of a scientific paper and the way it is received by reviewers.

Statistical analysis for medical research is not merely a formality. It is a tool that often determines whether study results are credible, clinically meaningful and suitable for publication.

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