Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Controls in Experiments

Controls in Experiments

When conducting an experiment, it is crucial to have control to reduce bias and accurately measure the dependent variables. It also marks the results more reliable. Controls are elements in an experiment that have the same characteristics as the treatment groups but are not affected by the independent variable. By sorting these data into control and experimental conditions, the relationship between the dependent and independent variables can be drawn. A randomized experiment always includes a...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

A scientific comparison of the EFLM Vision and RiskGATOR software: a unified path towards value-based, patient-centered laboratory medicine.

Clinical chemistry and laboratory medicine·2026

Same author

Estimation of the Effective Dose of Phenylephrine Infusion for Preventing Spinal Anesthesia-Induced Hypotension in Elective Cesarean Deliveries: A Randomized Controlled Trial.

Cureus·2025

Same author

Space Oncology: A Comprehensive Scoping Review.

Wilderness & environmental medicine·2025

Same author

The Impact of Climate Change on Laboratory Medicine: A Global Health Perspective.

Clinical chemistry·2025

Same author

Data-driven discovery of associations between prescribed drugs and dementia risk: A systematic review.

Alzheimer's & dementia (New York, N. Y.)·2025

Same author

Evaluation of Point-of-care Ultrasound of Airway to Predict Difficult Laryngoscopy and Intubation in Intensive Care Unit Patients.

Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine·2025

Same journal

Invasive urothelial carcinoma in association with surface low-grade papillary urothelial carcinoma: clinical and pathologic insights from a rare entity.

American journal of clinical pathology·2026

Same journal

CEACAM1 expression by immunohistochemistry in B-cell lymphomas and plasma cell myeloma.

American journal of clinical pathology·2026

Same journal

Comprehensive multicriteria life cycle assessment of biopsy processing in a surgical pathology department.

American journal of clinical pathology·2026

Same journal

Prognostic significance of Myb protein and its downstream target genes in lacrimal gland adenoid cystic carcinoma.

American journal of clinical pathology·2026

Same journal

Mismatch repair protein "nonclassic expression loss" pattern in colorectal cancer: an important staining pattern that is not well understood.

American journal of clinical pathology·2026

Same journal

Musculoskeletal pain in medical laboratory personnel: a cross-sectional study.

American journal of clinical pathology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Dec 10, 2025

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling

Published on: June 23, 2022

COVID-19 Testing.

Zoe C Brooks¹, Saswati Das²

¹AWEsome Numbers, Worthington, Canada.

American Journal of Clinical Pathology

|August 29, 2020

Summary

This summary is machine-generated.

Understanding the probability of false-positive and false-negative SARS-CoV-2 test results is crucial for managing patient risk and healthcare costs. Accurate testing metrics, like sensitivity and specificity, help mitigate these risks.

Keywords:

Clinical CoVID-19 Coronavirus Cost False-negative False-positive Metrics Prevalence Risk SARS-CoV-2 Sensitivity Specificity

More Related Videos

Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots

Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots

Published on: February 11, 2022

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

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

Published on: February 16, 2022

Related Experiment Videos

Last Updated: Dec 10, 2025

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling

Published on: June 23, 2022

Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots

Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots

Published on: February 11, 2022

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

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

Published on: February 16, 2022

Area of Science:

Infectious Disease Diagnostics
Clinical Laboratory Science
Health Economics

Background:

Accurate diagnosis of SARS-CoV-2 relies on molecular, antigen, and antibody testing.
Sensitivity (PPA) and specificity (PNA) are key metrics for evaluating diagnostic test performance.
Predictive values assess the probability of true positives and negatives based on test results.

Purpose of the Study:

To demonstrate the impact of false-positive and false-negative results on patient risk and clinical costs.
To highlight the importance of reporting probabilities of false results and associated costs.
To provide a framework for calculating these risk metrics.

Main Methods:

Utilizing sensitivity (PPA) and specificity (PNA) as primary metrics for test evaluation.
Incorporating prevalence, PPA, and PNA to determine the likelihood and cost of false test results.
Calculating risk metrics including probability of false positives and negatives.

Main Results:

Molecular and antigen tests are effective during the acute phase of SARS-CoV-2 infection.
Serologic assays are valuable for detecting antibodies in recovering or recovered individuals.
Each testing method for SARS-CoV-2 has distinct advantages and limitations.

Conclusions:

Reporting the probability of false-positive and false-negative results offers significant value for patient care and healthcare economics.
Risk metrics can be derived from PPA, PNA, prevalence, cost, and the Reff number.
This approach aids in better risk assessment and cost management in SARS-CoV-2 diagnostics.