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In the first stage, four schools (SRM University, Vellammal Engineering College, Crescent University, and Loyola Institution of Business Applications) were randomly selected using a probability proportion to size method from a pool of thirteen ranked business schools.
Five out of the 23 districts were selected for the evaluation using a probability proportion to size sampling strategy.
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A probability proportion to size design was used to select clusters.
At the second stage, all the villages in each of the designated affected and control sub-counties were listed and households assigned into 25 villages using the probability proportion to size technique, hence a total of 50 villages per district, i.e. 100 villages in both districts combined.
Using a three-stage probability proportion to size sampling method, the NHSS randomly selected 30 counties in Sichuan Province in the first stage, one town from each sampled counties in the second stage, and one THC from each sampled town in the third stage for the Prescription Survey.
Two-stage sampling protocol was used: in the first stage, primary sampling units (PSU) were selected using probability proportion to size (PPS) from the sampling frame; this was followed by the second stage, where a random selection of respondents was done based on listing at selected clusters.
Villages were selected using probability proportion to sample size (PPS).
The study subjects were selected through cluster sampling using probability proportion to size criteria.
This was a cross-sectional survey in which sampling was carried out using multi-stage and probability proportion to size sampling methods.
At the first stage of sampling, 289 Primary Sampling Units (PSUs) (95 sub-wards in urban areas and 194 groups of wards in rural areas) were selected using systematic sampling with probability proportion to size.
Multi-stage sampling using probability in proportion to size was used to select a nationally representative sample.
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CEO of Professional Science Editing for Scientists @ prosciediting.com