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

Cluster Sampling Method01:20

Cluster Sampling Method

12.0K
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...
12.0K
Convenience Sampling Method00:55

Convenience Sampling Method

9.0K
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.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
9.0K
Stratified Sampling Method01:16

Stratified Sampling Method

12.1K
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. 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.
To choose a stratified sample, divide the population into groups called strata and then take a...
12.1K
Choosing Between z and t Distribution01:25

Choosing Between z and t Distribution

2.8K
The z and the Student t distribution estimate the population mean using the sample mean and standard deviation. However, to decide which distribution to use for a calculation, one needs to determine the sample size, the nature of the distribution, and whether the population standard deviation is known. If the population standard deviation is known and the population is normally distributed, or if the sample size is greater than 30, the z distribution is preferred. The Student t distribution is...
2.8K
Systematic Sampling Method01:17

Systematic Sampling Method

10.4K
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...
10.4K
Random Sampling Method01:09

Random Sampling Method

11.2K
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. Among the various sampling methods used by...
11.2K

You might also read

Related Articles

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

Sort by
Same author

Ketamine Dosing Across Clinical Indications: A Narrative Review Organized by Proposed NMDA-Related Mechanisms.

Journal of clinical pharmacology·2026
Same author

Tobramycin pharmacokinetic and pharmacodynamic targets in people with cystic fibrosis.

British journal of clinical pharmacology·2026
Same author

Sex-specific differences in amygdala resting-state functional connectivity with trait anxiety.

Neuropsychology·2026
Same author

Posaconazole in Saliva: Feasibility of a Noninvasive Monitoring Approach in Immunocompromised Children.

The Pediatric infectious disease journal·2026
Same author

Suicidal Ideation Effectiveness and Safety Outcomes from the Ketamine for Adult Depression Study (KADS).

Archives of suicide research : official journal of the International Academy for Suicide Research·2026
Same author

Effect of ketamine on anxiety: findings from the Ketamine for Adult Depression Study - RETRACTION.

The British journal of psychiatry : the journal of mental science·2026
Same journal

Optimizing Subcutaneous Antibody Dosing Regimens Through Operating Space Maps: rHuPH20 Case Study.

Journal of pharmacokinetics and pharmacodynamics·2026
Same journal

Mechanistic modeling of FcRn-dependent IgG drug interactions: Clinical applications and dosing implications.

Journal of pharmacokinetics and pharmacodynamics·2026
Same journal

Comparing heavy-tailed residual error models for outlier handling in population PK modeling.

Journal of pharmacokinetics and pharmacodynamics·2026
Same journal

Personalized prophylactic therapy optimization in hemophilia A using a hybrid PK-PD-TTE model and deep RL.

Journal of pharmacokinetics and pharmacodynamics·2026
Same journal

Pediatric oral cavity physiologically based pharmacokinetic model to predict pharmacokinetics of mucoadhesive atropine gel to treat sialorrhea.

Journal of pharmacokinetics and pharmacodynamics·2026
Same journal

Exposure-safety analyses of talazoparib in combination with enzalutamide in patients with metastatic castration-resistant prostate cancer (mCRPC) in the TALAPRO-2 trial.

Journal of pharmacokinetics and pharmacodynamics·2026
See all related articles

Related Experiment Video

Updated: Jul 19, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.6K

Optimal sample selection applied to information rich, dense data.

David Wang1, Tak Hung2, Noelyn Hung3

  • 1Department of Anaesthesia, Waikato Hospital, Hamilton, New Zealand. david.wang@waikatodhb.health.nz.

Journal of Pharmacokinetics and Pharmacodynamics
|August 10, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a retrospective optimal selection strategy for analyzing dense data, particularly for quantifying unbound drug concentrations from plasma samples. This method efficiently maximizes information gain from limited resources.

Area of Science:

  • Pharmacokinetics
  • Data Science
  • Analytical Chemistry

Background:

  • Dense data presents challenges, categorized as information-poor (Type 1) and information-rich (Type 2).
Keywords:
Dense dataOptimal designSample selection

More Related Videos

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.6K
Sampling Soils in a Heterogeneous Research Plot
07:11

Sampling Soils in a Heterogeneous Research Plot

Published on: January 7, 2019

34.6K

Related Experiment Videos

Last Updated: Jul 19, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.6K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.6K
Sampling Soils in a Heterogeneous Research Plot
07:11

Sampling Soils in a Heterogeneous Research Plot

Published on: January 7, 2019

34.6K
  • Type 1 data may require thinning to reduce computational and statistical issues like autocorrelation.
  • Type 2 data benefits from optimal design strategies to maximize information extraction.