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Stratified Sampling Method

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.
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Random Sampling Method

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Related Experiment Video

Updated: Jul 6, 2026

Stereological Estimation of Dopaminergic Neuron Number in the Mouse Substantia Nigra Using the Optical Fractionator and Standard Microscopy Equipment

Stereological Estimation of Dopaminergic Neuron Number in the Mouse Substantia Nigra Using the Optical Fractionator and Standard Microscopy Equipment

Published on: September 1, 2017

Automatic sampling for unbiased and efficient stereological estimation using the proportionator in biological

J E Gardi¹, J R Nyengaard, H J G Gundersen

¹Stereology and Electron Microscopy Research Laboratory and MIND Center, University of Aarhus, Aarhus, Denmark. Jonathan.Gardi@ki.au.dk

Journal of Microscopy

|April 5, 2008

Summary

A new method, general proportionator sampling, improves tissue property quantification through unbiased estimation. This automatic image analysis technique is significantly more efficient than traditional sampling methods.

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Related Experiment Videos

Last Updated: Jul 6, 2026

Stereological Estimation of Dopaminergic Neuron Number in the Mouse Substantia Nigra Using the Optical Fractionator and Standard Microscopy Equipment

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Published on: September 1, 2017

Knowing What Counts: Unbiased Stereology in the Non-human Primate Brain

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Published on: May 14, 2009

Sampling Strategies and Processing of Biobank Tissue Samples from Porcine Biomedical Models

Sampling Strategies and Processing of Biobank Tissue Samples from Porcine Biomedical Models

Published on: March 6, 2018

Area of Science:

Quantitative biology
Biomedical imaging analysis
Stereology

Background:

Accurate quantification of tissue properties is crucial for biological research.
Traditional sampling methods can be inefficient and introduce bias.
Automated image analysis requires robust sampling strategies.

Purpose of the Study:

To introduce and evaluate the general proportionator sampling and estimation procedure for improved tissue property quantification.
To compare the efficiency of the proportionator method against traditional sampling techniques.

Main Methods:

The proportionator method utilizes non-uniform sampling with probability proportional to size (PPS).
Regions of interest are partitioned into fields of view, weighted by feature content.
Sampled fields of view are analyzed to provide unbiased estimation despite biased image analysis.

Main Results:

The proportionator method demonstrated strict unbiasedness in estimation.
In biological examples, the proportionator was at least eight times more efficient than meander sampling.
Efficiency was measured by a combination of precision and time.

Conclusions:

The general proportionator sampling and estimation procedure offers a significant advancement in quantitative tissue analysis.
This method enhances efficiency and accuracy in biological image quantification.
The proportionator is a superior alternative to traditional computer-controlled sampling for stereological studies.