Data Analysis
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Heterogeneity and homogeneity of treatment effects: what biomedical researchers need to know

In biomedical research, recognizing and interpreting heterogeneity and homogeneity of treatment effects is crucial. Embracing both concepts allows for a comprehensive understanding of treatment…
Data Analysis

Understanding Kendal’s Tau: a handy tool for exploring statistical relationships

Biomedical researchers often find themselves navigating through complex statistical methods to make sense of their data. One such method that can be incredibly useful in analyzing relationships…
Data Storage & Management

5 Precautions Biomedical Researchers Should Take When Analyzing Data from a Large Public Registry

Biomedical researchers can use these tips to navigate big data with the help of a biostatistician.  Researchers should to assess the data quality, identify potential sources of bias or confounding,…
Data Analysis

A handy guide to Bayesian Neural Networks for biomedical researchers

Read this blogpost to understand what Bayesian Neural Network is, its advantages, and challenges.
Data Analysis

5 Tools to make meta-analysis easier for biomedical researchers

This article sheds light on various tools tailored for biomedical researchers, each equipped with unique features and functionalities.
Data Analysis

Understanding the Sequential Multiple Assignment Randomized Trial (SMART): A guide for biomedical researchers

This blogpost breaks down Sequential Multiple Assignment Randomized Trial (SMART) and explores why it's becoming a game-changer for biomedical researchers.
Data Analysis

What is propensity score weighting? A quick guide for biomedical researchers

This blogpost will act like a guide for biomedical researchers by explaining the principle behind propensity score weighting along with its advantages and disadvantages.
Data Analysis

Using bayesian statistics in prognostic research: An overview for biomedical researchers

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 Bayesian methods employed in…
Data Analysis

Exploratory analysis of multi-omics datasets: A handy guide for biomedical researchers

In this blogpost, we’ll take a look at how such analyses can be conducted, with a step-by-step explanation of the process.
Data Analysis

An introduction to multiple imputation by chained equations for biomedical researchers

Biomedical research often deals with complex phenomena, and missing values can throw a wrench into our data analyses. This blogpost explains Multiple Imputation by Chained Equations (MICE), which…