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The objective of the paper was to design a computer algorithm to calculate sample sizes for estimating proportions incorporating clustered sampling units using a beta-binomial model when information concerning the intraclass correlation is not available.
The ICC values reported here may be useful in designing future studies that use clustered sampling from primary care practices.
Besides, stratified clustered sampling method and a relatively high response rate with the help of local government minimize sampling bias.
Analyses were conducted in Mplus version 7 [ 32], using maximum likelihood estimation with robust standard errors to account for non-normality of data and clustered sampling.
One could, for example, perform clustered sampling in which a random sample of clinics is chosen and then a random sample of patients within each clinic is identified.
Clustered sampling is an alternative sampling approach commonly used to reduce the recruitment effort and gather data from subjects, without reducing the whole population representativeness.
DHS sampling design uses clustered sampling, which includes both over-sampling and under-sampling.
The TIMSS assessments use a two-stage, clustered sampling design.
Thus, these observations suggest that clustered sampling is unfeasible for this sampling frame.
Robust standard errors corrected for heteroskedasticity and for the clustered sampling scheme are in parenthesis.
Robust standard errors corrected for heteroskedasticity and for the clustered sampling scheme in parenthesis.
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