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 ?
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.
Type I error rates for the scores test as a function of sample size (n), average rate Poisson ([theta]), nominal level of significance [alpha] = 5% and N = 10,000 simulations.
Table 4 divides the companies into two groups: Group 1 includes those companies whose sample size collectively is greater than their sample size under the individual approach.
In order to improve the quality of research findings, this article attempts to contribute to the derivation and evaluation of sample size methodology for two-sample t tests in two important and distinctive aspects.
a]), is a function of sample size n, type I error [alpha] and values of [mu] specified in the null [H.
Moreover, this fit statistic does not depend on the sample size or test length.
As the sample size increases the estimated relative bias (Table 5) of all the estimators' decreases.
2009) state that this effect is due to the sensitivity of the chi-squared statistic of the LRT to the sample size, especially when the sample size is greater than 200 observations; when n is less than or equal to 100, the chi-squared test will exhibit an acceptable fit (the differences are not significant between the estimated and observed covariance matrices), even when the model relationships are not significant.
But fudging the extent of testing with a "finger to the wind" approach is not the way to plan procedures: The AICPA Audit Sampling Guide's sample size table should not be used, because it does not provide reliable guidance.
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.