Search results
Results From The WOW.Com Content Network
In survey methodology, probability-proportional-to-size (pps) sampling is a sampling process where each element of the population (of size N) has some (independent) chance to be selected to the sample when performing one draw.
Probability sampling includes: simple random sampling, systematic sampling, stratified sampling, probability-proportional-to-size sampling, and cluster or multistage sampling. These various ways of probability sampling have two things in common: Every element has a known nonzero probability of being sampled and; involves random selection at ...
The optical and physical fractionators use a sampling method called systematic uniform random sampling, or SURS. Unlike these two methods the proportionator introduces sampling with probability proportional to size, or PPS. With SURS all sampling sites are equal. With PPS sites are not sampled with the same probability.
In this sampling plan, the probability of selecting a cluster is proportional to its size, so a large cluster has a greater probability of selection than a small cluster. The advantage here is that when clusters are selected with probability proportionate to size, the same number of interviews should be carried out in each sampled cluster so ...
For example, in cluster sampling we can use a two stage sampling in which we sample each cluster (which may be of different sizes) with equal probability, and then sample from each cluster at the second stage using SRS with a fixed proportion (e.g. sample half of the cluster, the whole cluster, etc.).
This is the smallest value for which we care about observing a difference. Now, for (1) to reject H 0 with a probability of at least 1 − β when H a is true (i.e. a power of 1 − β), and (2) reject H 0 with probability α when H 0 is true, the following is necessary: If z α is the upper α percentage point of the standard normal ...
Maps being used for fieldwork were outdated. Fast-growing neighborhoods led to bad measures of size used for probability proportional to size sampling based on the last census, which, in turn, led to intolerably expensive workloads if the original sampling plan was implemented. [13]
Inverse probability weighting is a statistical technique for estimating quantities related to a population other than the one from which the data was collected. Study designs with a disparate sampling population and population of target inference (target population) are common in application. [ 1 ]