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Sample size multiplicity

Expanding the sample size to 2Xc admits the other shape families shown on Fig. 6 into the analysis and leads to additional codimension-two interactions between the shapes is the (1A<.)- family and shapes with other numbers of cells in the sample. The bifurcation diagram computed for this sample size with System I and k = 0.865 is shown as Fig. 11. The (lAc)- and (Ac/2)-families are exactly as computed in the smaller sample size, but the stability of the cell shapes is altered by perturbations that are admissible is the larger sample. The secondary bifurcation between the (lAc)- and (2Ae/3)-families is also a result of a codimension two interaction of these families at a slightly different wavelength. Two other secondary bifurcation points are located along the (lAc)-family and may be intersections with the (4Ac and (4A<./7) families, as is expected because of the nearly multiple eigenvalues for these families. [Pg.315]

Often there is a desire to compare responses to multiple treatments rather than simply evaluate active against a placebo control. For instance, it may be useful to evaluate several doses or to assess a product against another marketed product. Increasing the number of treatments will increase the sample size required overall, but will also increase the number of subjects required per treatment arm because the number of statistical comparisons is larger. If all between-group comparisons are to be made, the number of statistical tests increases dramatically as the number of treatment arms increases. With two groups, only one comparison is possible. With three groups, the number... [Pg.242]

Large tolerance to sample size (from subgram to multiple-gram)... [Pg.116]

Second, while we applaud the fact that more Hispanics are being included in clinical studies, the sample sizes continue to be small, limiting the interpretations that can be made from the data. In some cases, multiple studies have been pooled together to increase the Hispanic sample size. This is methodologically less rigorous as there may be variability in the methods employed between studies, for example inter-rater differences. [Pg.106]

HSQC-14-ADEQUATE spectra. When 1,1-ADEQUATE data are to be utilized in conjunction with UIC or GIC co-processing, acquisition times and/or sample sizes may be reduced. In the former case, with an 10 mg sample of strychnine (1), acquisition times could be reduced to approximately 4 h while still giving very usable HSQC-1,1-ADEQUATE spectra. Using the latter tact, the authors demonstrated that it was possible to reduce the sample size to <0.5 mg of 1 over a weekend when the data were acquired using a 600-MHz 1.7 mm Micro CryoProbe.50 Clearly, for applications such as this, there appears to be considerable potential for the utilization of UIC or GIC co-processing of multiplicity-edited GHSQC and 1,1-ADEQUATE spectra. [Pg.277]

Witte JS, Elston RC, Cardon LR. On the relative sample size required for multiple comparisons. Stat Med 2000 19 369-372. [Pg.234]

The Array Biosensor developed at the Naval Research Laboratory (NRL) is an automated, portable detection device for simultaneous analysis of up to six samples for multiple analytes with the size of a shoebox (Figure 10) 42-43. [Pg.447]

For samples with low values of K, < 500 ppm, the laser method, because of its small sample size, becomes more uncertain than a thermal release study with a larger sample size. It is not possible to compensate in the laser probe method by multiple pulses above MOO individual pulses which corresponds to evaporation of approximately 20 pg. It is conceivable that by completely redesigning a mass spectrometer with smaller volumes which is bakeable to higher temperatures to alleviate this problem. We have been able on occasion to work with samples as low as 100 ppm K but certainly not on a routine basis. [Pg.145]

Overall sampling quality — quantitative analysis. For dynamical trajectories, the "structural decorrelation time" analysis [10] can estimate the slowest timescale affecting significant configuration-space populations and hence yield the effective sample size. For non-dynamical simulations, a variance analysis based on multiple runs is called for [1]. Analyzing the variance in populations of approximate physical states appears to be promising as a benchmark metric. [Pg.45]


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