Finally, strategies will be presented to implement a Gibbs sampler for drawing inferences from the posterior distributions of the breeding values.
In both situations, the analytical expression for the full conditional posterior densities is recognizable and, as a consequence, it is possible to implement a Gibbs sampling algorithm as the inference method [ 37].
However, such surveys often need to implement a complex sampling methodology including prestratification and post-stratification, multiple stages, unequal selection probabilities, clusters, resampling, etc, and often a mix of these, to cite the most frequent situations 1 7; in turn, survey planning, implementation and analyses are time-consuming and expensive.
Given the differences among countries in school systems, the age of children entering the first class of primary school (reception year), and the number of children repeating a grade, it was difficult to implement a uniform sampling approach that was applicable in every country.
In contrast, it is extremely simple to implement a program to sample quasi-random saturated structures, thus permitting one to easily obtain an idea of various structural features in the ensemble of quasi-random structures.
The objective of this qualitative, retrospective case study was to explain how and why the Chaguo Letu project was able to successfully make informed strategic decisions on how to implement a Cervical Self Sampling Program (CSSP) in Kenya.
We also explain how this technique could be used to implement a blocking Gibbs sampler.
In order to select a representative sample of the Portuguese family physicians working in the Portuguese National Health Service without a database of family physicians, we had to implement a stratified cluster sampling design.
In addition, if preferred it would be trivial to implement an MCMC Gibbs sampler to sample from these densities.
However, this conclusion has been challenged [ 13, 44], because in practice, it is difficult to design and implement a sampling protocol free of methodological bias.
