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Data Analysis

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In the vast ocean of statistical methods, biomedical researchers often find themselves at a crossroads when choosing between traditional frequentist statistics and the…
Choosing between Frequentist and Bayesian statistics: a guide for biomedical researchers
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With advancements in technology and data analytics, personalized medicine has witnessed a surge in interest, offering the potential to revolutionize patient care. Among…
Enhancing Healthcare: Power of Bayesian Methods in Personalized Medicine
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Biomedical researchers conducting simulation studies should consider several key statistical aspects to ensure the validity and reliability of their findings. Here, we…
In this blog post, we have broken down the concept of joint modeling in simple terms and explained its significance for biomedical researchers.
A handy guide to joint modeling for biomedical researchers
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Sampling methods play a significant role in ensuring the representativeness and reliability of our findings. Two main approaches in sampling are non-probability and…
Understanding sampling methods: Non-probability vs. probability sampling
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In scientific research, statisticians and researchers continually seek the most robust and informative methods to analyze data. The integration of Bayesian and…
Navigating the best of both worlds: using both Bayesian and frequentist statistics in your study
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In the world of biomedical research, where every piece of data holds valuable insights, statistical tools like the Method of Moments play a crucial role. By demystifying…
In this blogpost, we describe some valuable strategies for biomedical researchers eager to enhance their analytical prowess.
In this blogpost, we will explore the usefulness of Bayesian methods in prognostic research, highlight the challenges in statistical analysis, and delve into some common…
To ensure the validity and reliability of your findings, it's essential to take specific precautions during statistical analysis. This blogpost lists 10 key precautions…