Determining the Reference Sample Size Needed to Control the Accuracy of the Conditional in-control ARL of a Normal-theory CUSUM

2016 ◽  
Vol 32 (7) ◽  
pp. 2499-2504 ◽  
Author(s):  
Daniel R. Jeske
Keyword(s):  
Sample Size ◽  
Reference Sample ◽  
Normal Theory

scholarly journals Sample size for determination of the physiological potential of coriander (Coriandrum sativum L.) seeds

2019 ◽  
Vol 13 ((04) 2019) ◽  
pp. 552-557
Author(s):  
Érica Fernandes Leão Araújo ◽  
Anderson Rodrigo da Silva ◽  
Amanda Rithieli Pereira dos Santos ◽  
Kaique Ferreira Alves, Lara Bernardes da S. Ferreira ◽  
Hygor Amaral Santana ◽  
...  
Keyword(s):  
Sample Size ◽  
Reference Sample ◽  
Seed Vigor ◽  
Species Determination ◽  
Germination Time ◽  
Germination Speed ◽  
Minimum Number ◽  
Mean Germination Time ◽  
Number Of Seeds

The objective of this work was to determine the minimum number of replications and seeds per replication to perform the germination and seed vigor tests with coriander seeds. Two seed lots were compared in terms of water content, vigor and viability. Eight hundred seeds per lot were used. Values of germination first count, germination, germination speed index and mean germination time were analyzed. Sample size scenarios were developed using different combinations of number of replications (from 2 to 10) and the number of seeds per replication (from 20 to 80) by means of a resampling with replacement technique. The reference sample consisted of four replications of 50 seeds, as it is commonly used in researches with this species. Determination of the minimum number of replications and seeds was based on comparing the 95% bootstrapped confidence intervals for the index of variation (CV/n0.5) of each scenario with the confidence interval of the reference sample. It is reasonable to reduce the number of seeds per replication from 50 to 30 in order determine germination first count, germination and germination speed index. Forty seeds per replication are recommended to quantify the mean germination time. However, reductions in the number of replications can affect negatively the accuracy of germination and vigor tests.

Sample Size Formulas for Normal Theory T Tests

1981 ◽  
Vol 35 (4) ◽  
pp. 243 ◽  
Author(s):  
William C. Guenther
Keyword(s):  
Sample Size ◽  
Normal Theory

Use of small-sample-based reference limits on a group basis

1994 ◽  
Vol 40 (9) ◽  
pp. 1698-1702 ◽  
Author(s):  
E A van der Meulen ◽  
P J Boogaard ◽  
N J van Sittert
Keyword(s):  
Sample Size ◽  
Reference Sample ◽  
Nonparametric Test ◽  
Small Sample ◽  
Reference Limit ◽  
Health Assessments ◽  
Group Basis ◽  
Test Of Significance ◽  
Upper Reference Limit ◽  
Limit Estimate

Abstract The evaluation of a biochemical or hematological quantity measured in a study group of employees during occupational health assessments involves a comparison with a reference sample group. Part of this evaluation consists of checking whether the percentage of values larger than a predetermined upper reference limit is significantly larger than the percentage normally expected (2.5%, if the 97.5 percentile is used as the upper reference limit). The reference limit, however, is estimated from a random reference sample, the size of which, for many reasons, may be relatively small; as a consequence, the reference limit estimate will be imprecise. In situations in which the reference sample size is smaller than or not much larger than the study sample size, this imprecision results in the usual binomial test of significance being highly inappropriate. We provide an exact nonparametric test valid for all reference sample sizes.

scholarly journals Reference sample size for multiple regression in corn

2020 ◽  
Vol 55 ◽  
Author(s):  
Alberto Cargnelutti Filho ◽  
Marcos Toebe
Keyword(s):  
Grain Yield ◽  
Sample Size ◽  
Multiple Regression ◽  
Reference Sample ◽  
Multiple Regression Model ◽  
Coefficient Of Determination ◽  
Size Number ◽  
Corn Grain ◽  
Double Cross ◽  
Corn Grain Yield

Abstract: The objective of this work was to determine the number of plants required to model corn grain yield (Y) as a function of ear length (X1) and ear diameter (X2), using the multiple regression model Y = β0 + β1X1 + β2X2. The Y, X1, and X2 traits were measured in 361, 373, and 416 plants, respectively, of single-, three-way, and double-cross hybrids in the 2008/2009 crop year; and in 1,777, 1,693, and 1,720 plants, respectively, of single-, three-way, and double-cross hybrids in the 2009/2010 crop year, totaling 6,340 plants. Descriptive statistics were calculated, and frequency histograms and scatterplots were created. The sample size (number of plants) for the estimate of the β0, β1, and β2 parameters, of the residual standard error, the coefficient of determination, the variance inflation factor, and the condition number between the explanatory traits of the model (X1 and X2) were determined by resampling with replacement. Measuring 260 plants is sufficient to adjust precise multiple regression models of corn grain yield as a function of ear length and ear diameter. The Y = -229.76 + 0.54X1 + 6.16X2 model is a reference for estimating corn grain yield.

A Comparison of the Power of the Paired Samples Rank Transform Statistic to that of Wilcoxon’s Signed Ranks Statistic

1985 ◽  
Vol 10 (4) ◽  
pp. 368-383 ◽  
Author(s):  
R. Clifford Blair ◽  
James J. Higgins
Keyword(s):  
Sample Size ◽  
Treatment Effects ◽  
High Reliability ◽  
Small Sample Size ◽  
Small Sample ◽  
Relative Power ◽  
Normal Theory ◽  
Large Sample ◽  
Paired Samples ◽  
Rank Transform

This study was concerned with the effects of reliability of observations, sample size, magnitudes of treatment effects, and the shape of the sampled population on the relative power of the paired samples rank transform statistic and Wilcoxon’s signed ranks statistic. It was found that factors favoring the Wilcoxon statistic were high reliability of observations, moderate to large sample sizes, and small treatment effects. Factors favoring the rank transform statistic were low reliability of observations, small sample size, and moderate to large treatment effects. It was also noted that the Wilcoxon statistic appeared to maintain the power advantage under normal theory assumptions.

Sample size of the reference sample in a case-augmented study

2017 ◽  
Vol 26 (5) ◽  
pp. 528-534
Author(s):  
Palash Ghosh ◽  
Anup Dewanji
Keyword(s):  
Sample Size ◽  
Reference Sample
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