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Mixed effects models are statistical tools designed to handle complex data structures commonly encountered in biomedical research. Let’s take a look at some of the most…
- Marisha Fonseca
- November 1, 2023
In this blogpost, we’ll break down Principal Components Analysis (PCA) in simple terms, explore its applications in biomedical research, discuss its advantages and…
- Marisha Fonseca
- October 19, 2023
In this blogpost, we'll demystify how Bayesian statistics can revolutionize your approach to meta-analysis.
- Marisha Fonseca
- October 23, 2023
In this blog post, we’ll explore five key trends that are currently shaping statistical analysis in the field.
- Marisha Fonseca
- August 1, 2023
Performing cross-validation correctly can help ensure that you get robust and reliable results. Here we discuss the how's and why's of cross-validating your data. …
- Marisha Fonseca
- September 8, 2023
Statistical analysis is an integral part of biomedical research, but it’s often difficult to choose the right test to run. In this guide, we’ll delve into when and how…
- Marisha Fonseca
- September 4, 2023
In this blog post, we’ll break down what Regression Discontinuity Design (RDD) is, how it works, and explore some fascinating applications of RDD in answering pressing…
- Marisha Fonseca
- October 16, 2023
Predicting trends is an important part of biomedical research. In this blogpost, we have explained everything about time-series forecasting which can help you make…
- Marisha Fonseca
- October 30, 2023
Read this article to understand heteroskedasticity and homoskedasticity in order to assess the quality of data, make informed decisions about statistical methods, and…
- Marisha Fonseca
- October 11, 2023
T-test is a simple yet powerful tool that helps you compare the means of two groups, making it a fundamental test in biomedical research. This post covers some key…
- Marisha Fonseca
- August 28, 2023