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Related Concept Videos

Sampling Plans01:23

Sampling Plans

Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Stratified Sampling Method01:16

Stratified Sampling Method

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...
Sampling Methods: Overview01:06

Sampling Methods: Overview

A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of sampling...
Systematic Sampling Method01:17

Systematic Sampling Method

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...
Cluster Sampling Method01:20

Cluster Sampling Method

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...
Random Sampling Method01:09

Random Sampling Method

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...

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Related Experiment Video

Updated: Jun 3, 2026

A Tactile Automated Passive-Finger Stimulator (TAPS)
19:44

A Tactile Automated Passive-Finger Stimulator (TAPS)

Published on: June 3, 2009

Optimal sampling strategy development methodology using maximum a posteriori Bayesian estimation.

A Franciscus van der Meer1, Marco A E Marcus, Daniël J Touw

  • 1Maastricht University Medical Centre, Maastricht, The Netherlands. f.vander.meer@mumc.nl

Therapeutic Drug Monitoring
|March 9, 2011
PubMed
Summary
This summary is machine-generated.

Maximum a posteriori Bayesian (MAPB) estimation offers a flexible approach to pharmacokinetic parameter estimation. This review details MAPB-based optimal sampling strategy development and assesses their clinical transferability and performance compared to regression methods.

Related Experiment Videos

Last Updated: Jun 3, 2026

A Tactile Automated Passive-Finger Stimulator (TAPS)
19:44

A Tactile Automated Passive-Finger Stimulator (TAPS)

Published on: June 3, 2009

Area of Science:

  • Pharmacokinetics
  • Pharmacometrics
  • Bayesian Statistics

Background:

  • Maximum a posteriori Bayesian (MAPB) estimation is a robust method for individual pharmacokinetic parameter estimation.
  • Optimal sampling strategies (OSS) are crucial for accurate pharmacokinetic parameter estimation, particularly for immunosuppressants and anticancer agents.
  • Existing OSS development methodologies are diverse and require comprehensive review.

Purpose of the Study:

  • To provide a comprehensive overview of optimal sampling strategy (OSS) development using MAPB pharmacokinetic parameter estimation.
  • To evaluate the clinical transferability of published OSSs.
  • To compare sampling strategies derived from MAPB estimation versus multiple regression analysis.

Main Methods:

  • Review of methodologies for OSS development, focusing on MAPB estimation.
  • Analysis of OSS components: prior distributions, reference value determination, optimal sampling time identification, and validation.
  • Comparative assessment of MAPB-derived OSSs against multiple regression analysis-derived OSSs.

Main Results:

  • MAPB estimation provides accurate and flexible pharmacokinetic parameter estimation.
  • Published OSSs frequently lack sufficient data for clinical transferability.
  • MAPB estimation demonstrates comparable predictive performance to multiple regression analysis but offers superior flexibility.

Conclusions:

  • MAPB estimation is a valuable tool for developing and applying optimal sampling strategies in pharmacokinetics.
  • Further efforts are needed to enhance the clinical transferability of developed OSSs.
  • MAPB-based OSSs present a flexible alternative to traditional regression-based approaches.