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Cluster sampling. A group of twelve people are divided into pairs, and two pairs are then selected at random. In statistics, cluster sampling is a sampling plan used when mutually homogeneous yet internally heterogeneous groupings are evident in a statistical population. It is often used in marketing research.
In statistics, multistage sampling is the taking of samples in stages using smaller and smaller sampling units at each stage. [1] Multistage sampling can be a complex form of cluster sampling because it is a type of sampling which involves dividing the population into groups (or clusters). Then, one or more clusters are chosen at random and ...
For this reason, cluster sampling requires a larger sample than SRS to achieve the same level of accuracy – but cost savings from clustering might still make this a cheaper option. Cluster sampling is commonly implemented as multistage sampling. This is a complex form of cluster sampling in which two or more levels of units are embedded one ...
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some specific sense defined by the analyst) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistical ...
Graphic breakdown of stratified random sampling. In statistics, stratified randomization is a method of sampling which first stratifies the whole study population into subgroups with same attributes or characteristics, known as strata, then followed by simple random sampling from the stratified groups, where each element within the same subgroup are selected unbiasedly during any stage of the ...
Lohr's [42] is for ordinary least squares (OLS) and generalized least squares (GLS) estimators in the context of cluster sampling, using a random coefficient regression model. Lohr presents conditions under which the GLS estimator of the regression slope has a design effect less than 1, indicating higher efficiency.
[4]: 250 So, for example, if we have 3 clusters with 10, 20 and 30 units each, then the chance of selecting the first cluster will be 1/6, the second would be 1/3, and the third cluster will be 1/2. The pps sampling results in a fixed sample size n (as opposed to Poisson sampling which is similar but results in a random sample size with ...
Clustered standard errors assume that is block-diagonal according to the clusters in the sample, with unrestricted values in each block but zeros elsewhere. In this case, one can define X c {\displaystyle X_{c}} and Ω c {\displaystyle \Omega _{c}} as the within-block analogues of X {\displaystyle X} and Ω {\displaystyle \Omega } and derive ...