scholarly journals Using digital twins to reduce sample sizes while maintaining power and statistical accuracy

2021 ◽  
Vol 17 (S9) ◽  
Author(s):  
David Walsh ◽  
Alejandro M Schuler ◽  
Diana Hall ◽  
Jonathan R. Walsh ◽  
Charles K. Fisher
Keyword(s):  
Sample Sizes ◽  
Statistical Accuracy ◽  
Digital Twins

Is Red Really Romantic?

2017 ◽  
Vol 48 (3) ◽  
pp. 174-183 ◽  
Author(s):  
Gabrielle K. Lehmann ◽  
Robert J. Calin-Jageman
Keyword(s):  
Opposite Direction ◽  
Positive Control ◽  
Weak Effect ◽  
Sample Sizes ◽  
Quality Controls

Abstract. Red has been reported to enhance attraction for women rating men ( Elliot et al., 2010 ) and men rating women ( Elliot & Niesta, 2008 ). We replicated one of these studies online and in-person. To ensure rigor, we obtained original materials, planned for informative sample sizes, pre-registered our study, used a positive control, and adopted quality controls. For men, we found a very weak effect in the predicted direction (d = 0.09, 95% CI [−0.17, 0.34], N = 242). For women, we found a very weak effect in the opposite direction (d = −0.09, 95% CI [−0.30, 0.12], N = 360). The original studies may have overestimated the red effect, our studies may be an underestimate, or there could be strong moderation of the effect of red on attraction.

Norm-Block Sample Sizes: A Review of 15 Multidimensional Intelligence Tests

2013 ◽  
Author(s):  
Randy G. Floyd ◽  
Ryan L. Farmer ◽  
Sarah Irby ◽  
Phil Norfolk ◽  
Haley Hawkins ◽  
...  
Keyword(s):  
Intelligence Tests ◽  
Sample Sizes ◽  
Block Sample

On the Mathematical Basis of Zelen’s Prerandomized Designs

1985 ◽  
Vol 24 (03) ◽  
pp. 120-130 ◽  
Author(s):  
E. Brunner ◽  
N. Neumann
Keyword(s):  
Clinical Trial ◽  
Normal Distribution ◽  
Random Variables ◽  
Small Samples ◽  
Selection Effects ◽  
Sample Sizes ◽  
Mathematical Basis ◽  
Additional Assumptions

SummaryThe mathematical basis of Zelen’s suggestion [4] of pre randomizing patients in a clinical trial and then asking them for their consent is investigated. The first problem is to estimate the therapy and selection effects. In the simple prerandomized design (PRD) this is possible without any problems. Similar observations have been made by Anbar [1] and McHugh [3]. However, for the double PRD additional assumptions are needed in order to render therapy and selection effects estimable. The second problem is to determine the distribution of the statistics. It has to be taken into consideration that the sample sizes are random variables in the PRDs. This is why the distribution of the statistics can only be determined asymptotically, even under the assumption of normal distribution. The behaviour of the statistics for small samples is investigated by means of simulations, where the statistics considered in the present paper are compared with the statistics suggested by Ihm [2]. It turns out that the statistics suggested in [2] may lead to anticonservative decisions, whereas the “canonical statistics” suggested by Zelen [4] and considered in the present paper keep the level quite well or may lead to slightly conservative decisions, if there are considerable selection effects.

Hybrid maize breeding with doubled haploids: Comparison between selection criteria

2006 ◽  
Vol 54 (3) ◽  
pp. 343-350 ◽  
Author(s):  
C. F. H. Longin ◽  
H. F. Utz ◽  
A. E. Melchinger ◽  
J.C. Reif
Keyword(s):  
Selection Criteria ◽  
Doubled Haploids ◽  
Optimum Allocation ◽  
Finite Sample ◽  
Sample Sizes ◽  
Maize Breeding ◽  
Selection Gain ◽  
Breeding Programmes ◽  
Hybrid Maize ◽  
Breeding Resources

The optimum allocation of breeding resources is crucial for the efficiency of breeding programmes. The objectives were to (i) compare selection gain ΔGk for finite and infinite sample sizes, (ii) compare ΔGk and the probability of identifying superior hybrids (Pk), and (iii) determine the optimum allocation of the number of hybrids and test locations in hybrid maize breeding using doubled haploids. Infinite compared to finite sample sizes led to almost identical optimum allocation of test resources, but to an inflation of ΔGk. This inflation decreased as the budget and the number of finally selected hybrids increased. A reasonable Pk was reached for hybrids belonging to the q = 1% best of the population. The optimum allocations for Pk(q) and ΔGkwere similar, indicating that Pk(q) is promising for optimizing breeding programmes.

No Evidence that Experiencing Physical Warmth Promotes Interpersonal Warmth: Two Failures to Replicate Williams and Bargh (2008)

2018 ◽  
Author(s):  
Christopher Chabris ◽  
Patrick Ryan Heck ◽  
Jaclyn Mandart ◽  
Daniel Jacob Benjamin ◽  
Daniel J. Simons
Keyword(s):  
Null Hypothesis ◽  
Small Sample ◽  
Sample Sizes ◽  
Double Blind ◽  
Bayesian Analyses ◽  
Physical Warmth ◽  
Small Sample Sizes ◽  
Interpersonal Warmth

Williams and Bargh (2008) reported that holding a hot cup of coffee caused participants to judge a person’s personality as warmer, and that holding a therapeutic heat pad caused participants to choose rewards for other people rather than for themselves. These experiments featured large effects (r = .28 and .31), small sample sizes (41 and 53 participants), and barely statistically significant results. We attempted to replicate both experiments in field settings with more than triple the sample sizes (128 and 177) and double-blind procedures, but found near-zero effects (r = –.03 and .02). In both cases, Bayesian analyses suggest there is substantially more evidence for the null hypothesis of no effect than for the original physical warmth priming hypothesis.

Signature Analysis: Statistical Models and Their Application to FA

1996 ◽  
Author(s):  
C.K. Lakshminarayan ◽  
S. Pabbisetty ◽  
O. Adams ◽  
F. Pires ◽  
M. Thomas ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Failure Analysis ◽  
Statistical Models ◽  
Essential Elements ◽  
Assessment Model ◽  
Signature Analysis ◽  
Risk Assessment Model ◽  
Sample Sizes ◽  
Reliability Engineering ◽  
Semiconductor Chips

Abstract This paper deals with the basic concepts of Signature Analysis and the application of statistical models for its implementation. It develops a scheme for computing sample sizes when the failures are random. It also introduces statistical models that comprehend correlations among failures that fail due to the same failure mechanism. The idea of correlation is important because semiconductor chips are processed in batches. Also any risk assessment model should comprehend correlations over time. The statistical models developed will provide the required sample sizes for the Failure Analysis lab to state "We are A% confident that B% of future parts will fail due to the same signature." The paper provides tables and graphs for the evaluation of such a risk assessment. The implementation of Signature Analysis will achieve the dual objective of improved customer satisfaction and reduced cycle time. This paper will also highlight it's applicability as well as the essential elements that need to be in place for it to be effective. Different examples have been illustrated of how the concept is being used by Failure Analysis Operations (FA) and Customer Quality and Reliability Engineering groups.

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