Effects of simulated sample sizes on mortality estimates—Protocol for a study in 3 randomised ICU trials

2019 ◽  
Vol 63 (8) ◽  
pp. 1098-1101 ◽  
Author(s):  
A. Kofoed ◽  
A. Perner ◽  
S. Marker ◽  
N. Haase ◽  
L. B. Holst ◽  
...  
Keyword(s):  
Sample Sizes ◽  
Simulated Sample ◽  
Mortality Estimates

scholarly journals Error and bias in under-5 mortality estimates derived from birth histories with small sample sizes

2013 ◽  
Vol 11 (1) ◽  
Author(s):  
Laura Dwyer-Lindgren ◽  
Emmanuela Gakidou ◽  
Abraham Flaxman ◽  
Haidong Wang
Keyword(s):  
Small Sample ◽  
Sample Sizes ◽  
Small Sample Sizes ◽  
Mortality Estimates

Effects of simulated sample sizes on the mortality effect estimates in three randomized intensive care unit trials

2020 ◽  
Vol 64 (7) ◽  
pp. 976-981
Author(s):  
Andreas Kofoed ◽  
Anders Perner ◽  
Søren Marker ◽  
Nicolai Haase ◽  
Lars B. Holst ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Sample Sizes ◽  
Simulated Sample ◽  
Mortality Effect

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.

Problems with small sample sizes in psychophysiological research

1996 ◽  
Author(s):  
Todd C. Riniolo ◽  
Stephen W. Porges
Keyword(s):  
Small Sample ◽  
Sample Sizes ◽  
Psychophysiological Research ◽  
Small Sample Sizes

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.

219. Sample Sizes for Hypothesis Testing with Leftcensored Lognormal Distributions

1999 ◽  
Author(s):  
J. Coble ◽  
P. Lees
Keyword(s):  
Hypothesis Testing ◽  
Sample Sizes ◽  
Lognormal Distributions

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.

COMPARISON OF DIFFERENT EXPERIMENTAL DESIGNS, SAMPLE SIZES AND TECHNIQUES APPLIED TO METAMODELING THE INDUCED DRAG COEFFICIENT OF A BOX-WING AIRCRAFT

2018 ◽  
Author(s):  
Luiz Fernando Tibério Fernandez ◽  
Guilherme Barufaldi ◽  
Adson De Paula ◽  
Luiz Carlos Sandoval
Keyword(s):  
Drag Coefficient ◽  
Experimental Designs ◽  
Sample Sizes ◽  
Induced Drag
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