Statistical Principles for the Design of Experiments

Mead, R.; Gilmour, Steven G.; Mead, Andrew

doi:10.1017/cbo9781139020879

Cited by 119 publications

(105 citation statements)

References 54 publications

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“…An alternative to the power analysis approach for determining the sample size in animal study is the 'resource equation' approach (4,6,9,10). Based on this approach, the acceptable range of degrees of freedom (DF) for the error term in an analysis of variance (ANOVA) is between 10 to 20 (4, 9, 10).…”

Section: Introductionmentioning

confidence: 99%

Sample Size Calculation in Animal Studies Using Resource Equation Approach

Arifin

Zahiruddin

2017

MJMS

436

160

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Animal research plays an important role in the pre-clinical phase of clinical trials. In animal studies, the power analysis approach to sample size calculation is recommended. Whenever it is not possible to assume the standard deviation and the effect size, an alternative to the power analysis approach is the 'resource equation' approach, which sets the acceptable range of the error degrees of freedom (DF) in an analysis of variance (ANOVA). The aim of this article is to guide researchers in calculating the minimum and maximum numbers of animals required in animal research by reformulating the error DF formulas.

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Section: Introductionmentioning

confidence: 99%

Sample Size Calculation in Animal Studies Using Resource Equation Approach

Arifin

Zahiruddin

2017

MJMS

436

160

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“…This analysis is similar to methods which have previously been used to compare the performance of different species in pure and mixed plots (e.g. Connolly 2013, 2016) and meets the general conditions, as outlined by Mead et al (2012). The following model (2) was used:…”

Section: Discussionmentioning

confidence: 99%

Effect of deployment-type on stem growth, biomass partitioning and crown characteristics of juvenile Sitka spruce clones

Donnelly¹,

Grant²,

O'Reilly³

2017

Silva Fenn.

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Highlights• Deployment × clone interactions reduced tree height and diameter growth in mixed plots for one clone • Height and diameter heterogeneity was significantly greater in mixed plots • Deployment-type significantly altered relationships between crown variables and competition was more asymmetric in mixed plots compared to monoclonal. AbstractCompetitive interactions in clonal forestry are not well understood and this needs to be addressed to develop better deployment strategies. Eight juvenile Sitka spruce (Picea sitchensis (Bong.) Carriére) clones were grown in monoclonal and clonal mixtures in a field experiment for three years to assess the effects of genetic diversity on shoot growth, above-and below-ground biomass partitioning and crown characteristics. Shoot elongation was measured throughout the growing season, while diameter was measured twice annually in May and December. After the third year, crown silhouette area was estimated from digitised images for one ramet per plot and ramets were then destructively harvested. Deployment × clone interactions were observed for tree height and diameter with reductions observed in mixed plots. Mixed plots had significantly greater height and diameter heterogeneity and more asymmetrical competition than monoclonal plots.Results from this study demonstrate that stem growth can be significantly altered when clones are planted in multi-clonal mixtures but for most clones, deployment-type will not significantly reduce their productivity.

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“…The measurements were made in compliance with a rotable central composite design with the star point distance α set to 1.6818, prepared using Statistica 12 [1,8,12]. According to the recommendations given in the literature [1], the measurements were repeated six times in the central point, leading to a total set of 20 runs that are listed in Table 1.…”

Section: Methodsmentioning

confidence: 99%

The Effect of Selected Conditions in a Thermoforming Process on Wall Thickness Variations

Sasimowski¹

2017

Adv. Sci. Technol. Res. J.

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The paper reports the results of a study on the effect of selected conditions in a thermoforming process for thin polystyrene sheet by vacuum assisted drape forming on the wall thickness non-uniformity of finished parts. The investigation was performed using Statistica's DOE module for three variables: temperatures in the external and internal zones of the heater as well as heating time of the plastic sheet. The results demonstrate that the wall thickness in the finished parts at the measuring points is primarily affected by the heating time and the temperature in the internal zone of the heater, while the temperature in the external zone only affects some regions of the finished part. The results demonstrate that a short heating time, and hence, a lower temperature of the plastic sheet lead to a more uniform deformation of both the bottom and the side walls of the finished part, and as a consequence, to smaller variations in the wall thickness. Shortening the heating time is, however, limited by the necessity of accurate reproduction of the shape of the finished part.

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Statistical Principles for the Design of Experiments

Cited by 119 publications

References 54 publications

Sample Size Calculation in Animal Studies Using Resource Equation Approach

Sample Size Calculation in Animal Studies Using Resource Equation Approach

Effect of deployment-type on stem growth, biomass partitioning and crown characteristics of juvenile Sitka spruce clones

The Effect of Selected Conditions in a Thermoforming Process on Wall Thickness Variations

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