Related Experiment Video

Updated: Nov 5, 2025

Dynamic Monitoring of Seroconversion using a Multianalyte Immunobead Assay for Covid-19
08:48

Dynamic Monitoring of Seroconversion using a Multianalyte Immunobead Assay for Covid-19

Published on: February 16, 2022

3.1K

Beware of Biases in Observational Studies on Anti-Spike Monoclonal Antibodies

Giuseppe Lapadula1, Davide Paolo Bernasconi2, Alessandro Soria1

  • 1Infectious Diseases Unit, San Gerardo Hospital, Monza, Italy.

Clinical Infectious Diseases : an Official Publication of the Infectious Diseases Society of America
|May 20, 2021
PubMed
Abstract

No abstract available in PubMed .

More Related Videos

Using Reference Reagents to Confirm Robustness of Cytokine Release Assays for the Prediction of Monoclonal Antibody Safety06:37

Using Reference Reagents to Confirm Robustness of Cytokine Release Assays for the Prediction of Monoclonal Antibody Safety

Published on: September 15, 2023

831
In Vitro Methods for Comparing Target Binding and CDC Induction Between Therapeutic Antibodies: Applications in Biosimilarity Analysis07:25

In Vitro Methods for Comparing Target Binding and CDC Induction Between Therapeutic Antibodies: Applications in Biosimilarity Analysis

Published on: May 4, 2017

17.9K

Related Concept Videos

Bias01:22

Bias

Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
6.5K
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
892