Biomedical subjects

Jason C Hsu

Publications and source records attributed to Jason C Hsu.

4 recordsLinked to original sources

PubMed2006

Statistically designing microarrays and microarray experiments to enhance sensitivity and specificity.

Gene expression signatures from microarray experiments promise to provide important prognostic tools for predicting disease outcome or response to treatment. A number of microarray studies in various cancers have reported such gene signatures. However, the overlap of gene signatures in the same disease has been limited so far, and some reported signatures have not been reproduced in other populations. Clearly, the methods used for verifying novel gene signatures need improvement. In this article, we describe an experiment in which microarrays and sample hybridization are designed according to the statistical principles of randomization, replication and blocking. Our results show that such designs provide unbiased estimation of differential expression levels as well as powerful tests for them.

Breast Neoplasms↗

PubMed2006

To permute or not to permute.

UNLABELLED: Permutation test is a popular technique for testing a hypothesis of no effect, when the distribution of the test statistic is unknown. To test the equality of two means, a permutation test might use a test statistic which is the difference of the two sample means in the univariate case. In the multivariate case, it might use a test statistic which is the maximum of the univariate test statistics. A permutation test then estimates the null distribution of the test statistic by permuting the observations between the two samples. We will show that, for such tests, if the two distributions are not identical (as for example when they have unequal variances, correlations or skewness), then a permutation test for equality of means based on difference of sample means can have an inflated Type I error rate even when the means are equal. Our results illustrate permutation testing should be confined to testing for non-identical distributions. CONTACT: calian@raunvis.hi.is.

Computer Simulation↗

PubMed2006

Statistical selection of maintenance genes for normalization of gene expressions.

Maintenance genes can be used for normalization in the comparison of gene expressions. Even though the absolute expression levels of maintenance genes may vary considerably among different tissues or cells, a set of maintenance genes may provide suitable normalization if their expression levels are relatively constant in the specific tissues or cells of interest. A statistical procedure is proposed to select maintenance genes for normalization of gene expression data from tissues or cells of interest. This procedure is based on simultaneous confidence intervals for practical equivalence of relative gene expressions in these tissues or cells. As an illustration, the procedure is applied to the maintenance gene expression data from Vandesompele et al. (2002).

Data Interpretation, Statistical↗

PubMed2003

Identifying effective and/or safe doses by stepwise confidence intervals for ratios.

Typical randomized clinical dose-finding studies consist of the comparison of several doses of a drug versus a placebo. Interest lies in estimating relevant doses among those under investigation for efficacy and safety variables, such as the minimum effective dose or the maximum safe dose (or estimating both doses simultaneously). Step-down procedures have been proposed for comparing the standardized differences of the dose groups against placebo. In this paper we consider the ratio of population means and propose stepwise confidence intervals for these ratios. These confidence intervals do not require multiplicity adjustments and yield the same decisions as the associated test procedures. In addition, several power concepts are investigated within the present framework. The results allow sample size determination in the design phase of a study for the probability of estimating correctly the dose of interest. Auxiliary results of a numerical study show the range of application of these methods.

Allylamine↗