Consequences of Violating Randomization in Cluster Sampling

Jason Parrott *

Wayne State University, Detroit, Michigan, USA.

Shlomo Sawilowsky

Wayne State University, Detroit, Michigan, USA.

*Author to whom correspondence should be addressed.


Abstract

Although not as efficient as simple random sampling, cluster sampling has been regarded as a valid sampling technique when the researcher is attempting to save cost. In order to do so, it is necessary that random selection occurs in all stages of sampling. This simulation study examines purposeful selection of cluster sampling in the second stage of a two stage cluster design.

Keywords: Cluster Sampling, Random Sampling, Monte Carlo Methods.


How to Cite

Parrott, Jason, and Shlomo Sawilowsky. 2014. “Consequences of Violating Randomization in Cluster Sampling”. Journal of Advances in Mathematics and Computer Science 4 (6):841-48. https://doi.org/10.9734/BJMCS/2014/6934.

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