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

Sample Size Calculation01:19

Sample Size Calculation

3.3K
Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
3.3K
Group Design02:01

Group Design

8.9K
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
8.9K
Randomized Experiments01:13

Randomized Experiments

6.9K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
6.9K
Sample Proportion and Population Proportion01:20

Sample Proportion and Population Proportion

5.3K
Collecting samples or responses from an entire population takes significant time and effort, so a researcher collects responses from only a sample of that population. Suppose a study needs to collect information about a specific mobile application. After sample collection, the researcher analyzes the data and discovers that most individuals in the sample use that specific mobile application. The sample proportion measures the number of individuals in a sample who either use or don't use the...
5.3K
Systematic Sampling Method01:17

Systematic Sampling Method

10.2K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
Systematic sampling is one of the simplest methods...
10.2K
Cluster Sampling Method01:20

Cluster Sampling Method

11.9K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
11.9K

You might also read

Related Articles

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

Sort by
Same author

Antiseptic Cleansing to Reduce Vertical Transmission of Pathogens to Neonates: The NeoVT-AMR Randomized Clinical Trial.

JAMA network open·2026
Same author

CMV viraemia is associated with mortality among children with HIV starting antiretroviral therapy in sub-Saharan Africa.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America·2026
Same author

Intravenous Artesunate in Artemisinin-Resistant Severe Malaria in Uganda.

The New England journal of medicine·2026
Same author

Multicenter Validation of Clinical Sepsis Phenotypes.

JAMA network open·2026
Same author

Sample Size Calculation for the ROCI Design.

Statistics in medicine·2026
Same author

Impact of co-amoxiclav versus amoxicillin on the gastrointestinal microbiota in sub-Saharan children hospitalized with pneumonia.

npj antimicrobials and resistance·2026
Same journal

Interpretable Bayesian Modeling for Multireader Multicase Studies: Addressing Overdispersion and Limited Sample Size in Diagnostic Enhancement Evaluation.

Statistics in medicine·2026
Same journal

Adaptive Sequential Multiple Hypotheses Testing for Concomitant Vaccine Safety Surveillance.

Statistics in medicine·2026
Same journal

Novel Distance Regression for Repeated Outcomes With Missing Data: Applications to Longitudinal and Crossover Studies of Microbiome Beta-Diversity.

Statistics in medicine·2026
Same journal

Optimal Weighted Tests for Replication Studies and the 'Two-Trials Rule' With Multiple Hypotheses.

Statistics in medicine·2026
Same journal

Identifiable Copula-Double-Cox Models: A Fully Parametric Framework for Dependent Right-Censored Survival Data.

Statistics in medicine·2026
Same journal

Moving From Individualized Risk-Based Prevention to Benefit-Based Prevention: Estimating Individualized Life-Years Gained From Prevention Services as a Basis for Eligibility.

Statistics in medicine·2026
See all related articles

Related Experiment Video

Updated: Jun 21, 2025

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
00:04

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition

Published on: September 20, 2019

10.6K

Determining sample size in a personalized randomized controlled (PRACTical) trial.

Rebecca M Turner1, Kim May Lee2, A Sarah Walker1

  • 1MRC Clinical Trials Unit at University College London, London, UK.

Statistics in Medicine
|July 9, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces new methods for sample size determination in personalized randomized controlled trials (PRACTical). These methods help identify the most effective treatments for individual patients, reducing adverse outcomes in complex clinical settings.

Keywords:
clinical trialsmultiple treatmentspersonalized randomizationsample sizetrial design

More Related Videos

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.4K
Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities
10:26

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

3.9K

Related Experiment Videos

Last Updated: Jun 21, 2025

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
00:04

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition

Published on: September 20, 2019

10.6K
Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.4K
Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities
10:26

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

3.9K

Area of Science:

  • Clinical Trials
  • Biostatistics
  • Personalized Medicine

Background:

  • Standard-of-care is often lacking in complex clinical settings, necessitating personalized treatment approaches.
  • Personalized randomized controlled trials (PRACTical) randomize patients only among appropriate treatments.
  • Existing sample size calculation methods are not applicable to PRACTical designs.

Purpose of the Study:

  • To propose novel methods for determining sample size in PRACTical designs.
  • To quantify the benefits of using trial results for personalized treatment selection.
  • To inform clinical decisions and policy making in settings with multiple treatment options.

Main Methods:

  • Deriving sample size by evaluating information gain from trials of varying sizes.
  • Quantifying the reduction in adverse outcomes by selecting the top-ranked treatment.
  • Using simulations to assess performance measures, including treatment effectiveness and patient outcomes.

Main Results:

  • The proposed methods provide a framework for sample size calculation in PRACTical trials.
  • Simulations demonstrated the potential for reducing adverse outcomes by utilizing personalized treatment rankings.
  • The approach was applied to a neonatal sepsis antibiotic regimen trial (NeoSep1).

Conclusions:

  • The developed methods offer a relevant approach for sample size determination in personalized clinical trials.
  • This facilitates informed clinical decision-making by ranking treatments based on individual patient appropriateness.
  • The findings support the use of PRACTical designs in complex therapeutic areas with non-standardized care.