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

What are Estimates?01:06

What are Estimates?

6.9K
It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
The estimate for the mean of a sample is denoted by ͞x, whereas the mean of the population is designated as μ. Further, parameters such...
6.9K
Estimation of the Physical Quantities01:05

Estimation of the Physical Quantities

6.7K
On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
6.7K
Confidence Intervals01:21

Confidence Intervals

8.6K
An unbiased point estimate is often insufficient to predict a population estimate, such as population mean or population proportion. In this scenario, a confidence interval is used. A confidence interval is an estimate similar to a  sample proportion. However, unlike the point estimate which is a single value, the confidence interval  contains a range of values. These values have lower and upper limits, known as confidence limits, and can be designated as L1 and L2, respectively.
A...
8.6K
Prediction Intervals01:03

Prediction Intervals

2.5K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
2.5K
Estimating Population Mean with Unknown Standard Deviation01:22

Estimating Population Mean with Unknown Standard Deviation

8.4K
In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the...
8.4K
Estimating Population Mean with Known Standard Deviation01:16

Estimating Population Mean with Known Standard Deviation

9.1K
To construct a confidence interval for a single unknown population mean μ, where the population standard deviation is known, we need sample mean as an estimate for μ and we need the margin of error. Here, the margin of error (EBM) is called the error bound for a population mean (abbreviated EBM). The sample mean is the point estimate of the unknown population mean μ.
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate +...
9.1K

You might also read

Related Articles

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

Sort by
Same author

Nine-valent human papillomavirus vaccine: implications for cervical elimination.

The Lancet. Infectious diseases·2026
Same author

SPIRIT 2025 statement: updated guideline for protocols of randomised trials.

Lancet (London, England)·2026
Same authorSame journal

Qualitative research - Part 1.

Perspectives in clinical research·2026
Same author

Patient and public involvement in cancer care and research: the Indian perspective.

Ecancermedicalscience·2026
Same author

Addressing low-value care (LVC) in Asia: a narrative review of Choosing Wisely and other initiatives across Asia.

BMJ open quality·2026
Same author

Nor-ursodeoxycholic Acid for Metabolic Dysfunction-associated Steatotic Liver Disease: Is There Enough Evidence for Clinical Use? A Critique of a Phase III Trial and Regulatory Endorsement of the Drug.

Journal of clinical and experimental hepatology·2026
Same journal

Cross-tool evaluation of artificial intelligence-drafted informed consent documents: A 3-level study.

Perspectives in clinical research·2026
Same journal

Preparing for central drugs standard control organization ethics committee inspections in India: A review of regulatory expectations and readiness strategies.

Perspectives in clinical research·2026
Same journal

Competencies and operations of research ethics committee members and the protection of research participants: A scoping review.

Perspectives in clinical research·2026
Same journal

The Consolidated Standards of Reporting Trials Statement-2025: New epoch for improving the transparency of randomized trials reporting.

Perspectives in clinical research·2026
Same journal

Cost analysis and drug utilization pattern in diabetic patients attending outpatient at tertiary care teaching hospital in South Gujarat.

Perspectives in clinical research·2026
See all related articles

Related Experiment Video

Updated: Nov 5, 2025

Psychophysically-anchored, Robust Thresholding in Studying Pain-related Lateralization of Oscillatory Prestimulus Activity
07:28

Psychophysically-anchored, Robust Thresholding in Studying Pain-related Lateralization of Oscillatory Prestimulus Activity

Published on: January 21, 2017

7.1K

Understanding estimands.

Nithya Jaideep Gogtay1, Priya Ranganathan2, Rakesh Aggarwal3

  • 1Department of Clinical Pharmacology, Seth GS Medical College and KEM Hospital, Mumbai, Maharashtra, India.

Perspectives in Clinical Research
|May 20, 2021
PubMed
Summary
This summary is machine-generated.

The International Council for Harmonisation (ICH) E9 (R1) guideline introduces Estimands to manage intercurrent events in clinical trials. This concept improves the interpretation of treatment efficacy in regulatory submissions and clinical practice.

Keywords:
Clinical trialsdrug developmentestimandhypotheticalregulatory

More Related Videos

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

7.1K
Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

12.2K

Related Experiment Videos

Last Updated: Nov 5, 2025

Psychophysically-anchored, Robust Thresholding in Studying Pain-related Lateralization of Oscillatory Prestimulus Activity
07:28

Psychophysically-anchored, Robust Thresholding in Studying Pain-related Lateralization of Oscillatory Prestimulus Activity

Published on: January 21, 2017

7.1K
Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

7.1K
Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

12.2K

Area of Science:

  • Clinical Trials Methodology
  • Regulatory Science
  • Biostatistics

Background:

  • Randomized controlled trials (RCTs) are crucial for evaluating intervention efficacy, comparing treatments against standard care or placebo.
  • Intercurrent events can complicate outcome assessment and interpretation in clinical trials.
  • The International Council for Harmonisation (ICH) E9 (R1) guideline introduced the Estimand concept to address these challenges.

Purpose of the Study:

  • To explain the concept of Estimands and their significance in clinical trial design and analysis.
  • To discuss the impact of Estimands on regulatory trial protocols and statistical analysis plans.
  • To explore the application of Estimands in routine clinical practice.

Main Methods:

  • Discussion of the Estimand framework as defined by ICH E9 (R1).
  • Analysis of how Estimands influence the definition of treatment effects and handling of intercurrent events.
  • Exploration of the practical implementation of Estimands in trial protocols and statistical analysis plans.

Main Results:

  • Estimands provide a structured approach to define the treatment objective considering intercurrent events.
  • The Estimand concept necessitates clear articulation of the treatment's effect of interest in trial protocols.
  • Sensitivity analyses are integral to assessing the robustness of trial results under different Estimand assumptions.

Conclusions:

  • The adoption of Estimands enhances the clarity and interpretability of clinical trial results for regulatory approval.
  • Estimands are expected to standardize the handling of intercurrent events, improving consistency in trial design and analysis.
  • The principles of Estimands have relevance beyond regulatory trials, potentially informing real-world evidence studies and clinical practice.