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PubMed2003

Estimation of false discovery rates in multiple testing: application to gene microarray data.

Testing for significance with gene expression data from DNA microarray experiments involves simultaneous comparisons of hundreds or thousands of genes. If R denotes the number of rejections (declared significant genes) and V denotes the number of false rejections, then V/R, if R > 0, is the proportion of false rejected hypotheses. This paper proposes a model for the distribution of the number of rejections and the conditional distribution of V given R, V / R. Under the independence assumption, the distribution of R is a convolution of two binomials and the distribution of V / R has a noncentral hypergeometric distribution. Under an equicorrelated model, the distributions are more complex and are also derived. Five false discovery rate probability error measures are considered: FDR = E(V/R), pFDR = E(V/R / R > 0) (positive FDR), cFDR = E(V/R / R = r) (conditional FDR), mFDR = E(V)/E(R) (marginal FDR), and eFDR = E(V)/r (empirical FDR). The pFDR, cFDR, and mFDR are shown to be equivalent under the Bayesian framework, in which the number of true null hypotheses is modeled as a random variable. We present a parametric and a bootstrap procedure to estimate the FDRs. Monte Carlo simulations were conducted to evaluate the performance of these two methods. The bootstrap procedure appears to perform reasonably well, even when the alternative hypotheses are correlated (rho = .25). An example from a toxicogenomic microarray experiment is presented for illustration.

Bayes Theorem↗
PubMed2004

Multiple-testing strategy for analyzing cDNA array data on gene expression.

An objective of many functional genomics studies is to estimate treatment-induced changes in gene expression. cDNA arrays interrogate each tissue sample for the levels of mRNA for hundreds to tens of thousands of genes, and the use of this technology leads to a multitude of treatment contrasts. By-gene hypotheses tests evaluate the evidence supporting no effect, but selecting a significance level requires dealing with the multitude of comparisons. The p-values from these tests order the genes such that a p-value cutoff divides the genes into two sets. Ideally one set would contain the affected genes and the other would contain the unaffected genes. However, the set of genes selected as affected will have false positives, i.e., genes that are not affected by treatment. Likewise, the other set of genes, selected as unaffected, will contain false negatives, i.e., genes that are affected. A plot of the observed p-values (1 - p) versus their expectation under a uniform [0, 1] distribution allows one to estimate the number of true null hypotheses. With this estimate, the false positive rates and false negative rates associated with any p-value cutoff can be estimated. When computed for a range of cutoffs, these rates summarize the ability of the study to resolve effects. In our work, we are more interested in selecting most of the affected genes rather than protecting against a few false positives. An optimum cutoff, i.e., the best set given the data, depends upon the relative cost of falsely classifying a gene as affected versus the cost of falsely classifying a gene as unaffected. We select the cutoff by a decision-theoretic method analogous to methods developed for receiver operating characteristic curves. In addition, we estimate the false discovery rate and the false nondiscovery rate associated with any cutoff value. Two functional genomics studies that were designed to assess a treatment effect are used to illustrate how the methods allowed the investigators to determine a cutoff to suit their research goals.

Amphetamine↗
PubMed1989

Relationship between skin-prick tests, the multiple allergosorbent test and symptoms of allergic disease.

In 47 atopic subjects, skin-prick testing to 10 common allergens was performed, and specific IgE to the same allergens was assessed by the multi-allergosorbent chemiluminescent assay (MAST-CLA). Overall agreement between the tests was 66.4% for conventionally positive skin tests (weal diameter greater than or equal to 3 mm), rising to 78.5% when a positive skin test was defined as having a weal diameter greater than or equal to 5 mm. Agreement between the tests was statistically significant for all allergens except Alternaria. A history was obtained from each subject of the presence or absence of allergic symptoms on exposure to cats, and whether there was a history of grass pollen allergy. MAST-CLA testing for specific IgE to cat dander predicted a history of cat allergy with an efficiency of 74.5%, while a positive MAST-CLA test for Cocksfoot grass predicted a history of grass pollen allergy with an efficiency of 85.1%. Similar results were obtained on skin testing for these allergens. We conclude that MAST-CLA gave results comparable to those obtained by skin-prick testing, and correlated equally well with the history of allergic symptoms.

Adult↗
PubMedDate not supplied

Multiple test analyzer (MTA): a microcomputer program for determining preferred strategies with two diagnostic tests.

There are ten distinct management strategies in clinical situations that involve two diagnostic tests with dichotomous outcomes. The authors describe a microcomputer program, based on a previously described model, that can be used to identify test and test-treatment thresholds and to compute preferred strategies. The program provides tables and graphs of the results, which can be viewed or printed, and there is an optimization routine that facilitates comprehensive analysis. It can be used by decision-analytic researchers and policy analysts, medical educators who teach decision analysis, and clinicians who use decision analysis in their practices.

Computers↗
PubMed2006

Segregation accuracy in item-method directed forgetting across multiple tests.

Two experiments examined recall across tests following item-method directed-forgetting instructions and the varying of presentation duration of items at study. For both immediate testing (Experiment 1) and delayed testing (Experiment 2), accurate recall of remember instruction items (R-items) exceeded the accurate recall of forget instruction items (F-items). However, some F-items from study were inaccurately recalled as R-items and R-items from study as F-items. Inaccurate recall persisted across tests for both immediate and delayed recall and increased across tests for immediate recall. We view the R-item advantage in accurate recall as consistent with the account they receive more rehearsal at study than do F-items. We view inaccurate recall as reflecting the bias to report items retrieved on an immediate test lacking instructional tags as F-items. On delayed tests, items retrieved lacking instructional tags are first assessed against a criterion point on a memory-strength continuum and those with strength above the criterion reported as R-items and those below the criterion as F-items.

Humans↗