Premium
A Review of the Cluster Survey Sampling Method in Humanitarian Emergencies
Author(s) -
Morris Shaun K.,
Nguyen Claire K.
Publication year - 2008
Publication title -
public health nursing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.471
H-Index - 55
eISSN - 1525-1446
pISSN - 0737-1209
DOI - 10.1111/j.1525-1446.2008.00719.x
Subject(s) - cluster sampling , confusion , survey sampling , sampling (signal processing) , sample (material) , cluster (spacecraft) , population , survey methodology , data science , computer science , data quality , statistics , geography , operations research , psychology , medicine , environmental health , engineering , operations management , mathematics , metric (unit) , chemistry , filter (signal processing) , chromatography , psychoanalysis , computer vision , programming language
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.