Results 221 to 230 of about 1,662,855 (280)
Serological and viral prevalence of Oropouche virus (OROV): A systematic review and meta-analysis from 2000-2024 including human, animal, and vector surveillance studies. [PDF]
Toews E +9 more
europepmc +1 more source
Systematic Approach to Reducing Errors in Deoxynivalenol Quantification: Insights from Bulk Wheat Sampling and Sample Preparation. [PDF]
Li L +10 more
europepmc +1 more source
Determinants of exclusive breastfeeding in Tanzania: a systematic review and meta-analysis. [PDF]
Noorani M +4 more
europepmc +1 more source
Agreement and systematic bias between QuantiFERON chemiluminescent immunoassay and QuantiFERON enzyme-linked immunosorbent assay in the detection of latent tuberculosis infection: A systematic review and meta-analysis. [PDF]
Bongomin F +5 more
europepmc +1 more source
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Biometrical Journal, 1998
Summary: A new systematic sampling scheme with Markovian behaviour which yields positive first order inclusion probabilities for all units and positive second order inclusion probabilities for all pairs of units is introduced. The suggested method has been compared with simple random sampling, stratified random sampling, linear systematic sampling and ...
Sampath, S., Uthayakumaran, N.
openaire +2 more sources
Summary: A new systematic sampling scheme with Markovian behaviour which yields positive first order inclusion probabilities for all units and positive second order inclusion probabilities for all pairs of units is introduced. The suggested method has been compared with simple random sampling, stratified random sampling, linear systematic sampling and ...
Sampath, S., Uthayakumaran, N.
openaire +2 more sources
2019
AbstractIn many contexts it is difficult or impossible to select a simple random sample. For example, the number of units in the finite population, N, may not be known in advance, or it may not be feasible to assign labels to all units in the population and to select an SRS from these labels (e.g., crabs within boxes on a fishing vessel).
David G. Hankin +2 more
openaire +1 more source
AbstractIn many contexts it is difficult or impossible to select a simple random sample. For example, the number of units in the finite population, N, may not be known in advance, or it may not be feasible to assign labels to all units in the population and to select an SRS from these labels (e.g., crabs within boxes on a fishing vessel).
David G. Hankin +2 more
openaire +1 more source

