Catalog of the most common designs used in biomedical studies

Organizing a study in a biomedical context involves several essential steps to ensure a well-designed and well-executed research project. We discuss the basic steps to follow when organizing such a study and highlight some of the more important points to consider in the process.

There are many possible designs for exploring questions in observational and experimental studies. Here, we present a basic catalog with examples so that you can start understanding the need for appropriate tools able of analyzing the results and providing a sound basis for evaluating the evidence from the available data.

Clinical trials are research studies conducted to evaluate the safety and effectiveness of medical treatments, interventions, drugs, devices, or therapies in humans. These trials are a crucial step in the process of developing and improving medical treatments and ensuring they meet rigorous scientific and ethical standards before they are widely available for clinical use.

Confidence intervals are fundamental for evaluating the evidence in any study. It is important to understand this concept and its interpretation.

We discuss several examples that help in the interpretation of a confidence interval

Here we present the basic confidence intervals for probabilities and means, including the estimation of differences among two groups. Those are basic tools for evaluating treatment effects.

In this chapter, the fundamental concepts of the contrast of hypotheses will be explored with the aim of identifying the most important elements of this process and recognizing the main variants of interests.

The **p-value** is a statistical measure used to assess the strength of evidence against a null hypothesis (\(H_0\)) in hypothesis testing. It represents the probability of obtaining a result as extreme as, or more extreme than, the observed data under the assumption that the null hypothesis is true.

Parametric and non-parametric tests are two major classes of statistical methods used to analyze data, each with distinct assumptions, advantages, and limitations. Their appropriate use depends on the nature of the data and the research questions at hand.

Relative risk (RR) and Odds Ratios (OR) are important risk measures in epidemiology. Here, we define these indexes and show their interpretation.

A two-arms clinical trial is a type of clinical study where participants are divided into two groups (or “arms”):

1. Treatment Group (Arm 1): Participants receive the experimental treatment or intervention.
2. Control Group (Arm 2): Participants may receive a placebo, standard treatment, or no intervention.

These trials are common in evaluating the efficacy and safety of new drugs, medical devices, or treatment protocols by directly comparing outcomes between the two arms.