Cluster sampling is much more complex to plan than other forms of sampling. Other interesting articles If you want to know more about statistics, methodology, or research bias, make sure to check out some of our
Generally, it shows that efficiency gains through the application of ACS, when compared to Simple Random Sampling (SRS), are large, particularly at higher levels of fieldwork effort. In particular, ACS efficiency gains over SRS remain sizable at higher values of initial starting samples, but ...
In this study, a stratified two-stage random cluster sampling methodology was employed to ensure the acquisition of a representative sample. The study encompassed all 22 provinces, 5 municipalities, and 4 autonomous regions within mainland China (all of them have the same administrative status, colle...
Cluster Dynamic refers to a methodology in which vehicles are grouped together based on factors such as speed, direction, connectivity degree, and mobility pattern, forming dynamic clusters that adapt to changing scenarios in real-time. AI generated definition based on: Intelligent Vehicular Networks ...
Clustering performance using Nyström method is directly dependent on the selection of sampling points, i.e., more number of samples lead to better approximations. But increasing the sampling rate is also not favorable in case of big data problems. So, multiple extensions in Nyström techniques...
Cluster randomization design is increasingly used for the evaluation of health-care, screening or educational interventions. The intraclass correlation coefficient (ICC) defines the clustering effect and be specified during planning. The aim of this work
As is standard practice for school-based CRCTs, schools were recruited through convenience and purposive sampling, with 519 schools approached across NSW, QLD and WA. An a priori power analysis was conducted for primary outcomes but not for secondary outcomes25. The methodology proposed by M. ...
Wooldridge, "Sampling- based versus design-based uncertainty in regression analysis,"Econometrica, 88(1), 265–296. Neyman, J. (1923, 1990), "On the Application of probability theory to Agricultural Experiments. Essay on Principles, Section 9,"Statistical Science, 5, 465-472. Startz, Richard...
To deal with huge datasets, a sampling-based method called Clustering LARge Applications (CLARA) [112] might be utilized. CLARA's concept is that instead of considering the entire collection of items, a tiny subset of the original objects is chosen as the dataset's representations. PAM [111]...
in data transmission. However, the proposed mechanism reduces energy consumption by sacrificing sampling accuracy.Dropping packetswhen channel is sensed to be busy may lead to information being lost. This approach is also application dependent. Clustering based on sensed data makes this scheme unsuitable...