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There is a need for parsimonious global health scales for use in large sample surveys.
Citizen scientists were encouraged to participate, resulting in large sample sets covering wide areas.
Complete randomization can be effective to reduce bias in the created groups especially in large sample size situations.
In large sample inventories the model errors in point estimates of biomass will often dominate sampling errors [12, 40].
These results allow us to investigate efficiencies of different least squares variogram-parameter estimators in large samples.
New low-temperature inserts compatible with an existing hyperpolarizer were developed to dynamically polarize nuclei in large samples.
The aim of this study was to investigate the association between lipid levels and depression with suicidality in large sample.
The sample versions of these matrices are nonsingular, but in large samples we assume these sample matrices converge to a singular matrix.
The normal approximation for these estimators in large samples can be easily handled either analytically or numerically.
The normal approximation for these estimators in large sample distribution theory is easily handled either analytically or numerically.
Therefore in large samples the standard errors and confidence intervals of parameters can be obtained using the asymptotic variance.
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