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If the game value is less than the amount bid, it must, before being doubled, be raised to the nearest appropriate multiple of the relevant base value that equals or exceeds the amount bid.
If the lower and upper limits are reported as such, the difference between the ln-transformed limits may be equated to an appropriate multiple of the standard deviation sX.
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The Lipschitz regularizations we will consider are the infimal convolutions of the functions with appropriate multiples of the norm.
Hence N = 1,732 for the SF = 1 scenario and appropriate multiples of this for the other SFs.
Authors believe that appropriate multiple injections of SC vectors could bring more striking results in terms of growth arrest as well as an earlier beginning of the therapy.
To investigate how smoking status is recorded in UK primary care; to evaluate whether appropriate multiple imputation (MI) of smoking status yields results consistent with health surveys.
To place the adenoviral E1 and E4 genes under the transcriptional control of the COX-2 and Ki-67 promoter we inserted these promoters in the appropriate multiple cloning site of our transfer vector generating pShuttle#4 COXKi and pShuttle#4 KiCOX.
In this study, we attacked the very important problem of application of appropriate multiple testing methods in identifying differential gene expression, and in addition, we have provided a framework for future experimental research in brachial plexus injuries and pain pathways.
Genetic analyses of such data typically present challenges, because of the choice of underlying hypotheses on genetic architecture of the studied disorders and phenotypes, large numbers of phenotypes, the appropriate multiple testing corrections, limited numbers of subjects, imputations required on missing phenotypes and genotypes, and the cross-disciplinary nature of the phenotype measures.
In addition, we illustrated the use of appropriate multiple testing methods for microarrays in monitoring differential gene expression between different biological states.
3 Improving the understanding of missingness structure in a data set allows for consideration of other appropriate multiple imputation methods, or other methods to incorporate partially observed variables, such as random effect models, Bayesian methods, down-weighting analyses, or pattern mixture models.
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