Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Observational Studies01:11

Observational Studies

10.8K
Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One...
10.8K
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

243
Body:Bioequivalence experimental study designs are crucial methodologies used in evaluating and comparing the bioavailability of different drug products. These designs are categorized into various types: completely randomized, randomized block, repeated measures, cross and carry-over, and Latin square designs.Completely randomized designs involve randomly allocating treatments to all subjects participating in the experiment. This allocation is achieved by assigning unique random numbers to...
243
Naturalistic Observations02:30

Naturalistic Observations

17.0K
If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
17.0K
Clinical Trials01:16

Clinical Trials

10.2K
Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
10.2K
Clinical Trials: Overview01:11

Clinical Trials: Overview

4.7K
Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
4.7K
Trial and Error and Algorithm01:12

Trial and Error and Algorithm

403
A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light...
403

You might also read

Related Articles

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

Sort by
Same author

Alcohol Intake and Health Study: No Protective Effect at Low Levels, With Mortality Increasing to 1 in 25 at 14 Drinks Per Week.

Journal of studies on alcohol and drugs·2026
Same author

Leveraging the Electronic Health Record for Early Detection of Pancreatic Cancer Among 9.4 Million US Veterans.

Clinical and translational gastroenterology·2026
Same author

Trends in Colon Cancer Colectomy Volume and Inpatient Costs, 2018-2023: A Medicare Analysis.

The Journal of surgical research·2025
Same author

Emergency Department Utilization by Veterans for Low-Acuity Conditions After Virtual Care Expansion.

JAMA network open·2025
Same author

Racial and ethnic disparities in buprenorphine retention and treatment outcome in a longitudinal cohort of U.S. veterans with opioid use disorder.

The American journal of drug and alcohol abuse·2025
Same author

Incorporating local ancestry information to predict genetically associated DNA methylation in admixed populations.

Briefings in bioinformatics·2025

Related Experiment Video

Updated: Jan 25, 2026

Staining the Cytoplasmic Ca2+ with Fluo-4/AM in Apple Pulp
08:05

Staining the Cytoplasmic Ca2+ with Fluo-4/AM in Apple Pulp

Published on: November 6, 2021

5.1K

Effect Estimates in Randomized Trials and Observational Studies: Comparing Apples With Apples.

Sara Lodi1, Andrew Phillips2, Jens Lundgren3

  • 1Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts.

American Journal of Epidemiology
|May 8, 2019
PubMed
Summary

Comparing randomized trials and observational studies requires harmonizing protocols and data analysis. This 3-step method ensures accurate effect estimates for causal inference, as demonstrated in HIV treatment research.

Keywords:
antiretroviral initiationcausal inferenceper-protocol effecttarget trial

More Related Videos

Author Spotlight: Insights into the Use of Apple-Derived Cellulose Scaffolds for Bone Tissue Engineering
09:49

Author Spotlight: Insights into the Use of Apple-Derived Cellulose Scaffolds for Bone Tissue Engineering

Published on: February 23, 2024

2.7K
Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

1.2K

Related Experiment Videos

Last Updated: Jan 25, 2026

Staining the Cytoplasmic Ca2+ with Fluo-4/AM in Apple Pulp
08:05

Staining the Cytoplasmic Ca2+ with Fluo-4/AM in Apple Pulp

Published on: November 6, 2021

5.1K
Author Spotlight: Insights into the Use of Apple-Derived Cellulose Scaffolds for Bone Tissue Engineering
09:49

Author Spotlight: Insights into the Use of Apple-Derived Cellulose Scaffolds for Bone Tissue Engineering

Published on: February 23, 2024

2.7K
Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

1.2K

Area of Science:

  • Epidemiology
  • Biostatistics
  • Clinical Trial Design

Background:

  • Randomized trials (RCTs) and observational studies (OS) often yield non-comparable effect estimates due to design and analysis differences.
  • Direct comparison is crucial for robust causal inference in medical research.

Purpose of the Study:

  • To propose and illustrate a standardized 3-step procedure for harmonizing RCTs and OS to enable direct comparison of effect estimates.
  • To facilitate meaningful comparisons of causal effects derived from different study designs.

Main Methods:

  • Step 1: Harmonization of study protocols, including eligibility criteria, treatment strategies, outcomes, follow-up periods, and causal contrasts.
  • Step 2: Harmonization of data analysis methods to estimate the same causal effect.
  • Step 3: Sensitivity analyses to assess the impact of remaining discrepancies.

Main Results:

  • The proposed harmonization procedure was applied to compare antiretroviral therapy initiation strategies using the START RCT and the HIV-CAUSAL Collaboration OS.
  • The method facilitates a more direct comparison of effect estimates between the two study types.

Conclusions:

  • The 3-step harmonization procedure provides a robust framework for comparing effect estimates from RCTs and OS.
  • This approach enhances the reliability of causal inference by minimizing discrepancies between study designs and analyses.