Biomedical subjects

Mark van der Laan

Publications and source records attributed to Mark van der Laan.

7 recordsLinked to original sources

PubMed2006

A method to increase the power of multiple testing procedures through sample splitting.

Consider the standard multiple testing problem where many hypotheses are to be tested, each hypothesis is associated with a test statistic, and large test statistics provide evidence against the null hypotheses. One proposal to provide probabilistic control of Type-I errors is the use of procedures ensuring that the expected number of false positives does not exceed a user-supplied threshold. Among such multiple testing procedures, we derive the most powerful method, meaning the test statistic cutoffs that maximize the expected number of true positives. Unfortunately, these optimal cutoffs depend on the true unknown data generating distribution, so could never be used in a practical setting. We instead consider splitting the sample so that the optimal cutoffs are estimated from a portion of the data, and then testing on the remaining data using these estimated cutoffs. When the null distributions for all test statistics are the same, the obvious way to control the expected number of false positives would be to use a common cutoff for all tests. In this work, we consider the common cutoff method as a benchmark multiple testing procedure. We show that in certain circumstances the use of estimated optimal cutoffs via sample splitting can dramatically outperform this benchmark method, resulting in increased true discoveries, while retaining Type-I error control. This paper is an updated version of the work presented in Rubin et al. (2005), later expanded upon by Wasserman and Roeder (2006).

Algorithms↗

PubMed2005

Effects of body composition and leisure-time physical activity on transitions in physical functioning in the elderly.

Physical activity and body composition were examined with respect to variation in functional limitation over a 6-year period (four surveys conducted between 1994 and 2000) based on a cohort of 1,655 community-dwelling older women and men living in Sonoma, California. Measures of functional limitation and physical activity were based on standard self-report questions. Measures of body composition (lean mass, fat mass) were estimated from bioelectric impedance by using population-specific prediction equations derived from dual-energy x-ray absorptiometry. For women, a one-unit gain in lean mass:fat mass ratio reduced the report of limitation at all surveys 65.5% (95% confidence interval: 21.8, 87.4). A similar reduction was not observed for men; however, there was a 3% increase in the report of no limitation at any survey. The effect of high levels of physical activity reduced new functional limitation that occurred at the last survey by 36.8% (95% confidence interval: 0.0, 92.2) for men and 52.7% (95% confidence interval: 13.5, 91.9) for women. In summary, higher levels of physical activity appeared to reduce the risk of future functional limitation conditional on the level of functioning established early in the disablement process by lean mass:fat mass ratio.

Absorptiometry, Photon↗

PubMed2005

An application of model-fitting procedures for marginal structural models.

Marginal structural models (MSMs) are being used more frequently to obtain causal effect estimates in observational studies. Although the principal estimator of MSM coefficients has been the inverse probability of treatment weight (IPTW) estimator, there are few published examples that illustrate how to apply IPTW or discuss the impact of model selection on effect estimates. The authors applied IPTW estimation of an MSM to observational data from the Fresno Asthmatic Children's Environment Study (2000-2002) to evaluate the effect of asthma rescue medication use on pulmonary function and compared their results with those obtained through traditional regression methods. Akaike's Information Criterion and cross-validation methods were used to fit the MSM. In this paper, the influence of model selection and evaluation of key assumptions such as the experimental treatment assignment assumption are discussed in detail. Traditional analyses suggested that medication use was not associated with an improvement in pulmonary function--a finding that is counterintuitive and probably due to confounding by symptoms and asthma severity. The final MSM estimated that medication use was causally related to a 7% improvement in pulmonary function. The authors present examples that should encourage investigators who use IPTW estimation to undertake and discuss the impact of model-fitting procedures to justify the choice of the final weights.

Air Pollutants↗

PubMed2005

A randomized, controlled trial of in-home drinking water intervention to reduce gastrointestinal illness.

Trials have provided conflicting estimates of the risk of gastrointestinal illness attributable to tap water. To estimate this risk in an Iowa community with a well-run water utility with microbiologically challenged source water, the authors of this 2000-2002 study randomly assigned blinded volunteers to use externally identical devices (active device: 227 households with 646 persons; sham device: 229 households with 650 persons) for 6 months (cycle A). Each group then switched to the opposite device for 6 months (cycle B). The active device contained a 1-microm absolute ceramic filter and used ultraviolet light. Episodes of "highly credible gastrointestinal illness," a published measure of diarrhea, nausea, vomiting, and abdominal cramps, were recorded. Water usage was recorded with personal diaries and an electronic totalizer. The numbers of episodes in cycle A among the active and sham device groups were 707 and 672, respectively; in cycle B, the numbers of episodes were 516 and 476, respectively. In a log-linear generalized estimating equations model using intention-to-treat analysis, the relative rate of highly credible gastrointestinal illness (sham vs. active) for the entire trial was 0.98 (95% confidence interval: 0.86, 1.10). No reduction in gastrointestinal illness was detected after in-home use of a device designed to be highly effective in removing microorganisms from water.

Adolescent↗

PubMed2003

Exploratory and confirmatory gene expression profiling of mac1Delta.

Exploratory outlier identification methods and confirmatory gene expression studies showed induction of the iron regulon in Saccharomyces cerevisiae lacking Mac1p, a copper-responsive transcription factor. The Aft1p/Aft2p binding motif was the most discriminating motif between up- and down-regulated genes, and we identified new genes potentially regulated by Aft1p/Aft2p. In addition, multiple genes encoding proteins containing Fe-S clusters were down-regulated suggesting metabolic reorganization to conserve iron in mac1Delta. Null mutants of each of the differentially expressed genes were characterized for copper- or iron-related phenotypes. New or additional support for a role in copper and iron homeostasis is provided in this study for the gene products of AKR1, MRS4, PCA1, SSU1, TIS11, YBR047W, YHL035C, YHR045W, YLR047C, YLR126C, and YTP1.

Base Sequence↗

PubMed2002

Modeling treatment effects on binary outcomes with grouped-treatment variables and individual covariates.

During evaluation of treatment effects in observational studies, confounding is a constant threat because it is always possible that patients with a better prognosis, not adequately characterized by measured covariates, are chosen for a specific therapy. Ecologic analyses may avoid confounding that would be present in analysis at the individual level because variations in regional or hospital practice may be unrelated to prognosis. The authors used simulated data with an excluded confounder to evaluate the reliability and limitations of the grouped-treatment approach, a method of incorporating an ecologic measure of treatment assignment into an individual-level multivariable model, similar to the instrumental variable approach. Estimates based on the grouped-treatment approach were closer to the true value than those of standard individual-level multivariable analysis in every simulation. Furthermore, confidence intervals based on the grouped-treatment approach achieved approximately their nominal coverage, whereas those based on individual-level analyses did not. The grouped-treatment approach appears to be more reliable than standard individual-level analysis in situations where the grouped-treatment variable is unassociated with the outcome except via the actual treatment assignment and measured covariates.

Confounding Factors, Epidemiologic↗

PubMed2002

Identification of regulatory elements using a feature selection method.

MOTIVATION: Many methods have been described to identify regulatory motifs in the transcription control regions of genes that exhibit similar patterns of gene expression across a variety of experimental conditions. Here we focus on a single experimental condition, and utilize gene expression data to identify sequence motifs associated with genes that are activated under this experimental condition. We use a linear model with two-way interactions to model gene expression as a function of sequence features (words) present in presumptive transcription control regions. The most relevant features are selected by a feature selection method called stepwise selection with monte carlo cross validation. We apply this method to a publicly available dataset of the yeast Saccharomyces cerevisiae, focussing on the 800 basepairs immediately upstream of each gene's translation start site (the upstream control region (UCR)). RESULTS: We successfully identify regulatory motifs that are known to be active under the experimental conditions analyzed, and find additional significant sequences that may represent novel regulatory motifs. We also discuss a complementary method that utilizes gene expression data from a single microarray experiment and allows averaging over variety of experimental conditions as an alternative to motif finding methods that act on clusters of co-expressed genes. AVAILABILITY: The software is available upon request from the first author or may be downloaded from http://www.stat.berkeley.edu/~sunduz. CONTACT: keles@stat.berkeley.edu

Amino Acid Motifs↗