Related Experiment Video
Updated: Jun 18, 2026

Rapid Fractionation and Isolation of Whole Blood Components in Samples Obtained from a Community-based Setting
Published on: November 30, 2015
A review of the cluster survey sampling method in humanitarian emergencies
Shaun K Morris1, Claire K Nguyen
1Division of Infectious Diseases, The Hospital for Sick Children, The University of Toronto, Toronto, Ontario, Canada. shaun.morris@utoronto.ca
Abstract:
Obtaining quality data in a timely manner from humanitarian emergencies is inherently difficult. Conditions of war, famine, population displacement, and other humanitarian disasters, cause limitations in the ability to widely survey. These limitations hold the potential to introduce fatal biases into study results. The cluster sample method is the most frequently used technique to draw a representative sample in these types of scenarios. A recent study utilizing the cluster sample method to estimate the number of excess deaths due to the invasion of Iraq has generated much controversy and confusion about this sampling technique. Although subject to certain intrinsic limitations, cluster sampling allows researchers to utilize statistical methods to draw inferences regarding entire populations when data gathering would otherwise be impossible.
Related Concept Videos
Surveys
Systematic Sampling Method
Systematic sampling is one of the simplest methods...
Convenience Sampling Method
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...
Stratified Sampling Method
To choose a stratified sample, divide the population into groups called strata and then take a...
Cluster Sampling Method
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...
Sampling Plans
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...

