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This paper considers the problem of choosing the sample size for testing hypotheses on the parameters of a model using Bayes factors.
On the negative side, it is widely assumed that the sample size for testing indirect association scales inversely with the linkage disequilibrium r2 between the typed marker and the untyped causal variant.
Since the needed sample size for testing the specificities was smaller (37 cases and 75 controls) we decided to achieve the calculated sample size for testing the sensitivities.
The sample size for testing psychometric properties is recommended to be at least 10 times the number of the items in an instrument [ 19].
Understanding the natural history of diabetic retinopathy is also important for estimating sample size for testing new interventions in clinical trials.
According to the COSMIN rating scale [ 46], a sample size for testing measurement properties of n ≥ 100, is considered excellent; from n = 50-99 is good; from n = 30-49 is fais; and n < 30 is poor.
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The program executes computations over different block sizes for testing the stability of the resulting optimal depth.
The choice of these municipalities was made arbitrary, considering the difference of sizes, for testing the algorithm.
In our study, the sample sizes for testing measurement properties of the DHI-N, seem mostly adequate, according to quality criteria proposed by Terwee et al. [ 27].
Hobart et al. suggested that the minimum sample size required for testing the validity and reliability of an instrument is 80 and 20 subjects, respectively [ 23].
The minimum sample size required for testing the validity and reliability of an instrument is 80 and 20 subjects, respectively [ 10].
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