A Statistical Method to Determine Sample Size to Estimate Characteristic Value of Soil Parameters

Abstract The relationship between the two estimates of genetic variation at the DNA level, namely the number of segregating sites and the average number of nucleotide differences estimated from pairwise comparison, is investigated. It is found that the correlation between these two estimates is large when the sample size is small, and decreases slowly as the sample size increases. Using the relationship obtained, a statistical method for testing the neutral mutation hypothesis is developed. This method needs only the data of DNA polymorphism, namely the genetic variation within population at the DNA level. A simple method of computer simulation, that was used in order to obtain the distribution of a new statistic developed, is also presented. Applying this statistical method to the five regions of DNA sequences in Drosophila melanogaster, it is found that large insertion/deletion (greater than 100 bp) is deleterious. It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.

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Statistical or Non-Statistical Sampling: Which Approach Is Best?

Journal of Applied Business Research (JABR) ◽

10.19030/jabr.v7i2.6252 ◽

2011 ◽

Vol 7 (2) ◽

pp. 117 ◽

Cited By ~ 2

Author(s):

James L. Colbert

Keyword(s):

Sample Size ◽

Statistical Method ◽

Statistical Approach ◽

Objective Measure ◽

Statistical Sampling ◽

Statistical Sample ◽

Sampling Procedures

When planning sampling procedures, the auditor considers this question: should a non-statistical or a statistical approach be used? A statistical method provides an objective measure of risk, optimizes the sample size, and is best for a population of a large number of homogeneous transactions. If the population members are dissimilar or there are key items, a non-statistical approach is most suitable. Some practitioners believe a statistical sample is more defensible; others feel a non-statistical approach can be more readily justified.

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Confidence interval of risk difference by different statistical methods and its impact on the study conclusion in antibiotic non-inferiority trials

Trials ◽

10.1186/s13063-021-05686-8 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Anthony D. Bai ◽

Adam S. Komorowski ◽

Carson K. L. Lo ◽

Pranav Tandon ◽

Xena X. Li ◽

...

Keyword(s):

Confidence Interval ◽

Sample Size ◽

Success Rate ◽

Statistical Method ◽

Statistical Methods ◽

Primary Outcome ◽

Treatment Success ◽

Secondary Analysis ◽

Risk Difference ◽

Treatment Success Rate

Abstract Background Numerous statistical methods can be used to calculate the confidence interval (CI) of risk differences. There is consensus in previous literature that the Wald method should be discouraged. We compared five statistical methods for estimating the CI of risk difference in terms of CI width and study conclusion in antibiotic non-inferiority trials. Methods In a secondary analysis of a systematic review, we included non-inferiority trials that compared different antibiotic regimens, reported risk differences for the primary outcome, and described the number of successes and/or failures as well as patients in each arm. For each study, we re-calculated the risk difference CI using the Wald, Agresti-Caffo, Newcombe, Miettinen-Nurminen, and skewness-corrected asymptotic score (SCAS) methods. The CIs by different statistical methods were compared in terms of CI width and conclusion on non-inferiority. A wider CI was considered to be more conservative. Results The analysis included 224 comparisons from 213 studies. The statistical method used to calculate CI was not reported in 134 (59.8%) cases. The median (interquartile range IQR) for CI width by Wald, Agresti-Caffo, Newcombe, Miettinen-Nurminen, and SCAS methods was 13.0% (10.8%, 17.4%), 13.3% (10.9%, 18.5%), 13.6% (11.1%, 18.9%), 13.6% (11.1% and 19.0%), and 13.4% (11.1%, 18.9%), respectively. In 216 comparisons that reported a non-inferiority margin, the conclusion on non-inferiority was the same across the five statistical methods in 211 (97.7%) cases. The differences in CI width were more in trials with a sample size of 100 or less in each group and treatment success rate above 90%. Of the 18 trials in this subgroup with a specified non-inferiority margin, non-inferiority was shown in 17 (94.4%), 16 (88.9%), 14 (77.8%), 14 (77.8%), and 15 (83.3%) cases based on CI by Wald, Agresti-Caffo, Newcombe, Miettinen-Nurminen, and SCAS methods, respectively. Conclusions The statistical method used to calculate CI was not reported in the majority of antibiotic non-inferiority trials. Different statistical methods for CI resulted in different conclusions on non-inferiority in 2.3% cases. The differences in CI widths were highest in trials with a sample size of 100 or less in each group and a treatment success rate above 90%. Trial registration PROSPERO CRD42020165040. April 28, 2020.

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