sample size


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Related to sample size: sampling techniques

sample size

(1) A subset of a larger population, selected for investigation to draw conclusions or make estimates about the larger population.
(2) The number of subjects in a clinical trial.
(3) Number of subjects required for primary analysis.
References in periodicals archive ?
However, as increasing sample size implies higher cost for studies, power is generally set at some reasonable level such as 0.
In sum, the results suggest that RMSD, SRMSD, and NRMSD are not suitable as fit statistics because they are highly dependent on sample size in the absence of DIF.
Values of the type I error rates of the LRT for the independence between two groups of variables under multivariate normal distribution in small sample sizes, n=25, (Figure 1A) increased significantly with the increase in the number of variables.
In addition, there was an interaction between test length and the amount of DIF (higher Type I error rate with a greater amount of DIF in the test and shorter tests) and between sample size and the amount of DIF (higher Type I error rate with larger sample sizes and a greater amount of DIF).
Thus, we claim that our self-adaptive approach concerning the test sample size solves the problems that are mentioned above.
In synthesis the interpretation of results is given in the specification of the suitable sample size to verify the adequacy of the Poisson and ZIP models through score test proposed by Van den Broek.
To calculate sample size when EPER is not set to zero requires visual basic programming in Excel as presented in Appendix A.
The distinct advantage of the prescribed methods is that it circumvents the uncertainty of sample variance by taking account of the underlying chi-square distribution of sample variance and permits a corrected sample size determination according to the desired assurance probability and expected power considerations.
With differences in magnitude between groups and level of significance held constant, changes in sample size will affect statistical power.
The purpose of the current study is determination of sample size in regression analysis of hydrologic variables by means of power analysis where power analysis is considered for generally fitting the model.
We then built multivariable linear regression models for both outcome variables using a hybrid selection approach to minimize overfitting given the modest sample size.
He explains how to determine the appropriate sample size for clinical trials and pharmaceutical and public medicine.