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Topic: Cluster sampling

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	PlanetMath: cluster sampling
		single-stage cluster sampling or one-stage cluster sampling: a sample is taken from the primary sampling units, in which all of the secondary sampling units are considered.
		second-stage cluster sampling, two-stage cluster sampling, or emphsubsampling: a sample is taken from the primary sampling units; then within each primary sampling unit, a sample is taken from their secondary sampling units.
		This is version 1 of cluster sampling, born on 2005-08-01.
	planetmath.org /encyclopedia/ClusterSampling.html (172 words)

	Cluster sampling - Wikipedia, the free encyclopedia
		The main difference between cluster sampling and stratified sampling is that in cluster sampling the cluster is treated as the sampling unit so analysis is done on a population of clusters (at least in the first stage).
		In stratified sampling, a random sample is drawn from each of the strata, whereas in cluster sampling only the selected clusters are studied.
		The main objective of cluster sampling is to reduce costs by increasing sampling efficiency (This contrasts with stratified sampling where the main objective is to increase precision.).
	en.wikipedia.org /wiki/Cluster_sampling (389 words)

	Statistics Glossary - Sampling
		Random sampling is a sampling technique where we select a group of subjects (a sample) for study from a larger group (a population).
		Cluster sampling is a sampling technique where the entire population is divided into groups, or clusters, and a random sample of these clusters are selected.
		Cluster sampling is typically used when the researcher cannot get a complete list of the members of a population they wish to study but can get a complete list of groups or 'clusters' of the population.
	www.cas.lancs.ac.uk /glossary_v1.1/samp.html (1270 words)

	Sampling (statistics) - Wikipedia, the free encyclopedia
		Sampling is that part of statistical practice concerned with the selection of individual observations intended to yield some knowledge about a population of concern, especially for the purposes of statistical inference.
		The sampling frame must be representative of the population and this is a question outside the scope of statistical theory demanding the judgement of experts in the particular subject matter being studied.
		In survey sampling, many of the individuals identified as part of the sample may be unwilling to participate or impossible to contact.
	en.wikipedia.org /wiki/Sampling_(statistics) (1776 words)

	Web page link to the first
		Area probability sampling, also called cluster sampling, is a sampling technique in which the population of interest is divided into groups, or clusters, and then a random sample of clusters is drawn to represent the population of interest.
		Since the primary sampling unit (PSU) is a cluster of elements located in proximity to one another as opposed to the PSU being the individual element in the population, cluster sampling offers a time and cost efficient way to sample a population that is spread across a large geographic area(1).
		Sampling is done only at the first phase and once the sample of clusters is selected every listing unit within each of the selected clusters is included in the sample(1).
	www.musc.edu /bmt738/McGreevy/subone.htm (517 words)

	Multistage sampling - Wikipédia
		Multistage sampling nyaeta bentuk kompleks tina cluster sampling.
		Using all the sample elements in all the selected clusters may be prohibitively expensive or not necessary.
		In stratified sampling, a random sample is drawn from all the strata, where in cluster sampling only the selected clusters are studied, either in single stage or multi stage.
	su.wikipedia.org /wiki/Multistage_sampling (191 words)

	Statistics Finland - Quality guidelines - Sampling Methods
		The basic sampling method is simple random sampling (SRS), which is a self-weighting sampling design, meaning that all the elements in a population have an equal probability of being included in the sample.
		Sample size is affected by various determinants: the precision at which parameter estimates are required, the way in which small domains and sub-domains are to be covered (i.e.
		An example of cluster sampling would be a study of work conditions where the firms/enterprises are selected first and their employees are then selected for the examination.
	www.stat.fi /tk/tt/laatuatilastoissa/lm020500/pe_en.html (601 words)

	PA 765: Sampling
		Repeated systematic sample has the side benefit that the variability in the subsample means for a given variable is a measure of the variance of that estimate in the entire sample.
		Multi-stage or cluster sampling is where the researcher divides the population into strata, samples the strata, then stratifies the samples, and then resamples, repeating the process until the ultimate sampling units are selected at the last of the hierarchical levels.
		Technically, cluster sampling is where all subjects at the lowest hierarchical level (ex., all students in a school) are sampled for each primary sampling unit (PSU's, which are the second-lowest hierarchical level, such as schools or Census blocks), whereas multistage sampling is where only a random sample of lowest hierarchical level subjects are selected.
	www2.chass.ncsu.edu /garson/pa765/sampling.htm (4752 words)

	Statistics Glossary - sampling
		When we sample a population with several strata, we generally require that the proportion of each stratum in the sample should be the same as in the population.
		Cluster sampling is a sampling technique where the entire population is divided into groups, or clusters, and a random sample of these clusters are selected.
		Cluster sampling is typically used when the researcher cannot get a complete list of the members of a population they wish to study but can get a complete list of groups or 'clusters' of the population.
	www.stats.gla.ac.uk /steps/glossary/sampling.html (1219 words)

	Cluster Sampling (Site not responding. Last check: 2007-10-09)
		, where single subjects are selected from the population, in cluster sampling the subjects are selected in groups or clusters.
		When all units of the selected cluster are interviewed, this is referred to as "one-stage cluster sampling".
		This type of sampling is referred to as "multistage sampling".
	www.ryerson.ca /~mjoppe/ResearchProcess/ClusterSampling.htm (217 words)

	Cluster Sampling: A False Economy?
		The lower the proportion of clusters which are sampled of all the clusters in the survey area, the greater the DE (and the lower the precision).
		The DE due to the clustering is calculated, firstly by working out the variance of the estimate of the national "% satisfied" as a clustered sample, using formula A1 given in Annex A.
		Consequently the number of clusters (n) is a key determinant of the size of the variance; a 2-fold increase in n leading to a 4-fold reduction in the variance (i.e.
	www.mori.com /pubinfo/aiz/cluster-sampling-a-false-economy.shtml (4564 words)

	Cluster Sampling
		Suppose that a survey is to be done in a large town and that the unit of enquiry is the individual household.
		Note that, unlike stratified sampling, the clusters are thought of as being typical of the population, rather than subsections.
		Note also that a cluster of units in one survey may be a unit in another, eg if household is the unit then cluster is group of households, if family member is unit then the cluster is household.
	www.cems.uwe.ac.uk /~pwhite/SURVEY1/node30.html (234 words)

	Fishery Bulletin: Applications in adaptive cluster sampling of Gulf of Alaska rockfish
		Systematic random sampling was conducted across the whole area to determine the lowest criterion value, and then a new systematic random sample was taken with adaptive sampling around each tow that exceeded the fixed criterion value.
		This uncertainty is likely due to their highly clustered distribution (Lunsford, 1999) and has led to two independent surveys (1998, 1999) to test the benefits of ACS in sampling POP.
		Samples were chosen systematically by longitude and distributed randomly by depth within each longitudinal strip.
	www.findarticles.com /p/articles/mi_m0FDG/is_3_101/ai_107524525 (1513 words)

	Cluster Sampling (Site not responding. Last check: 2007-10-09)
		Cluster sampling was devised in the United States of America to try to overcome the problems of cost and the lack of a satisfactory sampling frame.
		Instead of selecting a random sample scattered over a wide area, greater convenience can be obtained is a few geographical areas are selected at random and every single household in each area is interviewed.
		One way of trying to offset this tendency to bias is to increase the number of clusters in the hope that you will then include in your sample every important strata, but every increase in the number of clusters raises the cost of the survey.
	www.csm.uwe.ac.uk /~pwhite/SURVEY2/node13.html (334 words)

	Deltoid » Lancet study and cluster sampling (Site not responding. Last check: 2007-10-09)
		However, the top and bottom lines are further apart—the effect of using cluster sampling instead of stratified sampling is to increase the variation of the samples.
		The ratio of the sample sizes for which cluster sampling and simple random sampling give the same variation is called the design effect.
		This clumping of clusters was likely to increase the sum of the variance between mortality estimates of clusters and thus reduce the precision of the national mortality estimate.
	timlambert.org /2005/10/seixon (2881 words)

	Web Site for Perfectly Random Sampling with Markov Chains:
		In perfect sampling algorithms, a sample is drawn exactly from the stationary distribution of a chain, as opposed to methods that run the chain ``for a long time'' and create samples drawn from a distribution that is close to the stationary distribution.
		Some perfect sampling algorithms for point processes are based on an extension of CFTP known as coupling into and from the past; for completeness, we give a read-once version of coupling into and from the past, but it remains unpractical.
		Instead of obtaining a sample of this model with approximately the stationary distribution by Monte Carlo simulation, it is possible to obtain a result which is exactly distributed according to the stationary distribution.
	dimacs.rutgers.edu /~dbwilson/exact.html (14686 words)

	OECD Glossary of Statistical Terms - Cluster sampling
		OECD Glossary of Statistical Terms - Cluster sampling
		When the basic sampling unit in the population is to be found in groups or clusters, e.g.
		human beings in households, the sampling is sometimes carried out by selecting a sample of clusters and observing all the members of each selected cluster.
	stats.oecd.org /glossary/detail.asp?ID=3754 (136 words)

	Chicago Boyz: Comment on Cluster Sampling and LIMS: Part 1 (Site not responding. Last check: 2007-10-09)
		Therefore, a clustered sample with any number N points is more likely to underestimate a clustered, rare effect than a random sample with the same number of points.
		Sampling theory is hellish stuff (think of the Birthday Paradox; the whole subject is like that), which is why anyone who wants to get anything done in applied work tries to leave as much of it as possible to the software designers.
		And a sample of 30 balls from a population is a perfectly valid way to estimate the proportion of different colours in most cases.
	www.chicagoboyz.net /mt/mt-comments.cgi?entry_id=3035 (4401 words)

	FROGLOG 55 - Adaptive Cluster Sampling for Amphibians
		FROGLOG 55 - Adaptive Cluster Sampling for Amphibians
		DEFINITION Adaptive Cluster Sampling (ACS) designs are statistical strategies for the selection of initial random (unrestricted or restricted) samples of plots, areas, transects, or traps that allow for inclusion of all relevant observations (animals, calls, signs) in the vicinity of the initial sample.
		In conventional amphibian field sampling, once the random selection has been made, the amphibian fieldworker is not allowed to look beyond the pre-determined boundaries of the samples or final population estimates will be biased (see Heyer et al., 1994, especially Chapters 2 and 6).
	www.open.ac.uk /daptf/froglog/FROGLOG-55-4.html (1168 words)

	Sampling (statistics)
		One of the sampling methods below is then applied to each stratum separately, maintaining the same balance in numbers as exists in the population and resulting in an improvement in precision.
		Cluster sampling locates the frame in areas of concentrated habitation.
		It guarantees that the sample is representative of the frame but is infeasible in many practical situations.
	www.sciencedaily.com /encyclopedia/sampling__statistics_ (1222 words)

	Cluster Sampling (Site not responding. Last check: 2007-10-09)
		In cluster sampling the units sampled are chosen in clusters, close to each other.
		Within each cluster units are then chosen by simple random sampling or some other method.
		Ideally the clusters chosen should be dissimilar so that the sample is as representative of the population as possible.
	www.mis.coventry.ac.uk /~nhunt/meths/cluster.html (145 words)

	Cluster sampling -- Facts, Info, and Encyclopedia article (Site not responding. Last check: 2007-10-09)
		Cluster sampling -- Facts, Info, and Encyclopedia article
		The main difference between cluster sampling and (The population is divided into subpopulations (strata) and random samples are taken of each stratum) stratified sampling is that in cluster sampling the cluster is treated as the sampling unit so analysis is done on a population of clusters (at least in the first stage).
		It is usually necessary to increase the total sample size to achieve equivalent precision in the (An expert at calculation (or at operating calculating machines)) estimators, but the savings in cost may make that feasible.
	www.absoluteastronomy.com /encyclopedia/c/cl/cluster_sampling.htm (352 words)

	Efficiency of adaptive cluster sampling for estimating density of wintering waterfowl (Site not responding. Last check: 2007-10-09)
		An evaluation of adaptive cluster sampling was based on a simulation experiment where samples were drawn from an enumeration of three species of waterfowl wintering in central Florida.
		Efficiency of adaptive cluster sampling relative to simple random sampling was highest when 1) the within-network variance was close to the population variance, and 2) the final sampling fraction was close to the initial sampling fraction.
		The evaluation was based on a simulation experiment for which the samples were drawn from an enumeration of ring-necked ducks (Aythya collaris), blue-winged teal (Anas discors), and green-winged teal (Anas crecca) in 5,000 km2 of central Florida.
	www.nbii.gov /metadata/mdata/brd-bib/usgs_brd_lsc_b_waterfowl.html (815 words)

	Adaptive Cluster Sampling for Forest Inventories
		Adaptive cluster sampling is shown to be a viable alternative for sampling forests when there are rare characteristics of the forest trees which are of interest and occur on clustered trees.
		An example is given in which the initial sample of trees is selected with probability proportional to tree basal area.
		If a characteristic of interest is observed on a sample tree, additional trees within a fixed distance of the sample tree are also included in the sample.
	www.srs.fs.usda.gov /pubs/viewpub.jsp?index=625 (198 words)

	Adaptive Cluster Sampling (ResearchIndex) (Site not responding. Last check: 2007-10-09)
		Abstract: fy C. The final sample consists of n1, not necessarily distinct clusters, one for each unit selected in the initial sample.
		If many of the units satisfy the condition, then the sample could consist of most of the units in the population, and hence be very costly.
		Thus, the design is most appropriate when the characteristic of interest is highly aggregated or clustered.
	citeseer.ist.psu.edu /408428.html (173 words)

	Web Accessibility Evaluation and Benchmarking Cluster
		The Unified Web Evaluation Methodology (UWEM1.1) is the result of a joint harmonization effort by 23 European organisations in three European projects combined in a cluster called the WAB Cluster.
		Within the WAB Cluster we are building an observatory for lare scale European evaluation and benchmarking of website accessibility.
		The coordination of the Cluster is provided by Eric Velleman, from Bartimeus Accessibility Foundation and a Cluster Board constituted by the 3 project leaders and co-ordinators in close relation to the EC.
	www.wabcluster.org (1091 words)

	Cluster Sampling - Educational Research - Del Siegle (Site not responding. Last check: 2007-10-09)
		If we wished to know the attitude of fifth graders in Connecticut about reading, it might be difficult and costly to visit each fifth grade in the state to collect our data.
		Each school in the state would have an equal chance of being selected, but only the students at the selected schools would be surveyed.
		In this situation, the clusters (classes in our example) are randomly selected and then students within those clusters are randomly selected.
	www.gifted.uconn.edu /siegle/research/Samples/cluster.htm (126 words)

	CDC Mass Casualties \| Community Study: Rapid community needs assessment using modified cluster sampling methods (Site not responding. Last check: 2007-10-09)
		To rapidly obtain population-based estimates of needs in the early aftermath of a mass trauma event, with severe property damage affecting at least one neighborhood.
		Use of a modified cluster sampling method to perform rapid needs assessment after Hurricane Andrew.
		Sampling plan: A minimum of 30 clusters would be systematically sampled from the area of interest and from households within each cluster identified using the methods described in Hlady et al., 1994.
	www.bt.cdc.gov /masstrauma/research/community.asp (532 words)

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