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PubMed2003

Bacon, Boole, the EPA, and scientific standards.

The scientific standards of the Environmental Protection Agency (EPA) include the use of retrospective meta-analysis. This analysis entails a use of the theory of probability that is only a simulation and cannot accurately measure the confidence that should be placed in the results. The uncertainty necessary for probability is, in a retrospective study, simulated rather than real. There are three logical forms for establishing a proposition. In the logic of the syllogism, a proposition is established by deduction from assumed propositions. In the logic of the physical sciences, a proposition is established by its ability to predict the outcomes of future experiments. In the logic of the courtroom, a proposition is established by its ability to explain past events. The logic of the courtroom operates under the handicap of working with nonrepeatable events. It is more subject to the preferences of the judge than the logic of the physical sciences or that of the syllogism. Because the logic of the courtroom is less reliable than either the logic of the physical sciences or that of the syllogism, it is the logic of last resort, i.e., it is used only when the other two are not applicable. Under the EPA scientific standards, the logic of the courtroom is accepted for establishing propositions about the physical world. As the logic of the courtroom is less reliable than that of the physical sciences, this practice increases the likelihood of errors.

Journal Article↗
PubMed2003

Sequential conditional probability ratio tests for normalized test statistic on information time.

Sequential conditional probability ratio tests (SCPRTs) provide monitoring procedures with a unique property that a decision reached at early stopping is unlikely to be reversed should the trial continue to the planned end (Xiong, X., 1995, Journal of the American Statistical Association 90, 1463-1473; Tan, M., Xiong, X., and Kutner, M. H., 1998, Biometrics 54, 682-95). It actually provides a probability statement of a conclusion reversal, should the proposed interim analysis plan be used. To broaden its scope of applications, in this article we develop the SCPRT in terms of Brownian motion, which is applicable to most clinical trials with various endpoints. In addition, we utilize the unique structure of the SCPRT to derive a class of adaptive sequential tests that retain the significance level and power in the presence of a nuisance parameter. We illustrate the proposed methods with examples in clinical trials.

Biometry↗
PubMed2002

Robust inference for event probabilities with non-Markov event data.

Multistate event data, in which a single subject is at risk for multiple events, is common in biomedical applications. This article considers nonparametric estimation of the vector of probabilities of state membership at time t. Estimators, derived under the Markov assumption, have been shown (Datta and Satten, 2001, Statistics and Probability Letters 55, 403-411) to be consistent for data that is non-Markov. Inference, however, must take into account possibly non-Markov transitions when constructing confidence bands for event curves. We develop robust confidence bands for these curves, evaluate them via simulation, and illustrate the method on two datasets.

AIDS-Related Opportunistic Infections↗
PubMed2002

Sample-size redetermination for repeated measures studies.

Clinical trialists recently have shown interest in two-stage procedures for updating the sample-size calculation at an interim point in a trial. Because many clinical trials involve repeated measures designs, it is desirable to have available practical two-stage procedures for such designs. Shih and Gould (1995, Statistics in Medicine 14, 2239-2248) discuss sample-size redetermination for repeated measures studies but under a highly simplified setup. We develop two-stage procedures under the general mixed linear model, allowing for dropouts and missed visits. We present a range of procedures and compare their Type I error and power by simulation. We find that, in general, the achieved power is brought considerably closer to the required level without inflating the Type I error rate. We also derive an inflation factor that ensures the power requirement is more closely met.

Analysis of Variance↗
PubMed2002

Adaptive decision making in a lymphocyte infusion trial.

We describe an adaptive Bayesian design for a clinical trial of an experimental treatment for patients with hematologic malignancies who initially received an allogeneic bone marrow transplant but subsequently suffered a disease recurrence. Treatment consists of up to two courses of targeted immunotherapy followed by allogeneic donor lymphocyte infusion. The immunotherapy is a necessary precursor to the lymphocyte infusion, but it may cause severe liver toxicity and is certain to cause a low white blood cell count and low platelets. The primary scientific goal is to determine the infusion time that has the highest probability of treatment success, defined as the event that the patient does not suffer severe toxicity and is alive with recovered white blood cell count 50 days from the start of therapy. The method is based on a parametric model accounting for toxicity, time to white blood cell recovery, and survival time. The design includes an algorithm for between-patient immunotherapy dose de-escalation based on the toxicity data and an adaptive randomization among five possible infusion times according to their most recent posterior success probabilities. A simulation study shows that the design reliably selects the best infusion time while randomizing greater proportions of patients to superior infusion times.

Algorithms↗
PubMed2005

Variance estimators for three "probabilities of causation".

This article introduces the definitions of three "probabilities of causation" suggested by Pearl (1999), which are used to evaluate the causal effect of an exposure on a disease in epidemiological studies. Pearl (1999) and Tian and Pearl (2000a, 2000b) provided identification formulas for three "probabilities of causation" from statistical data under some assumptions. In order to examine the estimation accuracy problem, this article derives variance estimators for three "probabilities of causation" correspondent to each case in Pearl (1999) and at the same time clarify their properties. In addition, we conduct simulation experiments and show that the proposed method can approximate sufficiently to the variance of "probabilities of causation." The results of this article provide a complete framework for using "probabilities of causation" effectively in order to analyze responsibility and susceptibility in epidemiological studies.

Analysis of Variance↗
PubMedDate not supplied

The use of statistical methodology for the analysis of QA data.

Modern statistical methods offer the quality assurance professional a powerful set of tools for the analysis of health care data. By using well-established procedures the quality assurance professional can isolate and quantify the relative degree of problems, determine statistical significance, and allocate resources towards problem resolution. This article briefly covers the concepts of hypothesis testing and statistical significance and their role in assisting the health care professional to assign priorities for use in problem resolution. Several statistical tests are described in the context of health care data analysis. The distinction between parametric, and non-parametric tests is made and a set of guidelines included on when and where the respective tests should be applied. An outline for the application of these statistical tests to several example situations is presented. Some details of population identification, sampling, and data organization are covered. Interpretation of results in the context of different problem situations is also covered.

Data Collection↗
PubMed2002

[A risk analysis by a measles exportation model concerning the FIFA World Cup 2002].

Risk of measles exportation from Japan is of concern regarding the FIFA World Cup 2002 (WC 2002), which will be held in Korea and Japan in June, 2002. During January 1999 through June 2001. the number of reported exportation cases from Japan was 7 to Australia and 22 to the United States. During the same time, a total of 2.13 million and 14.69 million people traveled between Japan-Australia and Japan-US, respectively. Based on an estimated number for travelers during the WC 2002 (420,000-432,000) announced by the Japanese Ministry of Transportation, we estimated the number of travelers for Japan-Australia and Japan-US would be 16,000 and 109,000 respectively. We analyzed the risk of measles exportation to Australia (PAU) and the United States (PUS) regarding travel for the WC2002 by assumption that measles exposure and transmission would be similar with the usual setting: P = 1 - [1 - (reported exported measles/number of travelers)]estimated number of travelers. The risk was estimated as PAU = 0.051 and PUS = 0.15, however, the results could be higher, because the peak of measles usually lies during May through June and exposure of the virus among young population during the soccer watch would be denser. Through immunization to one-year-old Japanese children is highly needed, as well as strengthening of international measles surveillance especially after the WC2002.

Humans↗
PubMed2002

Robustness of the Chen-Dougherty-Bittner procedure against non-normality and heterogeneity in the coefficient of variation.

Chen, Dougherty, and Bittner [Y. Chen, E. R. Dougherty, and M. L. Bittner, J. Biomed. Opt. 2(4), 364-374 (1997)] provided the derivation of a probability density function (PDF) for a signal ratio from a DNA microarray. This PDF is potentially useful for testing whether a pair of signals from the same gene has a common mean. The derivation of the PDF assumes the normality of all signal distributions and a common coefficient of variation (CV) for all signals within a microarray. The testing procedure requires the calculation of a common confidence interval for a microarray, based on a maximum likelihood estimator of the "common" CV, and the determination of whether or not a ratio for a particular gene falls within this interval. This study used Monte Carlo techniques and demonstrated that the procedure is robust to violations of normality and also to constancy in the coefficients of variation. A closer examination of the dynamics of the procedure found that the robustness was the result of offsetting effects. The size of the confidence interval was increased as a result of higher estimates of the common CV, as the actual CV pattern became heterogeneous. This effect mitigated the inflation in the size of the ratio as a result of increasing CV heterogeneity. These findings suggest that the Chen-Dougherty-Bittner procedure may be used even if underlying assumptions do not hold.

Analysis of Variance↗
PubMed2000

An analysis of the relationship between radiosensitivity and volume effects in tumor control probability modeling.

The dependence of local tumor control probability (tcp) on tumor volume is analyzed and discussed with the help of radiobiological modeling; in particular the impact of possible correlations between mean tumor radiosensitivity and tumor dimensions on the tcp volume dependence is explored. The linear-quadratic Poissonian tumor control probability (tcp) model was modified to account for the possible dependence of clonogenic cell density and radiosensitivity parameters on tumor volume; then the original and modified versions of the model were fitted to published clinical and laboratory tumor control data. These different versions of the tcp model often fitted tumor control data equally well, because of the high degree of correlation between the parameters. Nevertheless the results were very different from a physical point of view and we suggest that sometimes it is possible to choose between equally good fits on the basis of physical considerations. Possible links between the volume dependence of the mean radiosensitivity and the degree of tumor hypoxia were also analyzed through a comparison of the results of the tcp fit to published measurements of oxygen tension in tumors.

Animals↗
PubMed1999

Detection of Verrucomicrobia in a pasture soil by PCR-mediated amplification of 16S rRNA genes.

Oligonucleotide primers were designed and used to amplify, by PCR, partial 16S rRNA genes of members of the bacterial division Verrucomicrobia in DNA extracted from a pasture soil. By applying most-probable-number theory to the assay, verrucomicrobia appeared to contribute some 0.2% of the soil DNA. Amplified ribosomal DNA restriction analysis of 53 cloned PCR-amplified partial 16S rRNA gene fragments and comparative sequence analysis of 21 nonchimeric partial 16S rRNA genes showed that these primers amplified only 16S rRNA genes of members of the Verrucomicrobia in DNA extracted from the soil.

DNA, Bacterial↗
PubMed1981

Rapid identification of Enterobacteriaceae with microbial enzyme activity profiles.

A total of 539 clinical isolates belonging to 10 species of the Enterobacteriaceae family were identified by enzyme activity profiles within 30 min of test inoculation. Each isolate was grown at 37 degrees C for 18 h on Mueller-Hinton agar and suspended to an optical density of 200 Klett units on 0.85% saline. Enzyme activity profiles were obtained by inoculating 18 fluorogenic substrates with the standardized bacterial suspension and monitoring initial rates of hydrolysis over the first 30 min of analysis. Individual enzyme activity profiles were entered into a coded data bank, and identifications were based on the Bayesian theory of probabilities. At a confidence level of 95%, five species were identified with a greater than 90% efficiency, three species were identified between 83 and 88% efficiency, and two species demonstrated a 72 and 75% efficiency of identification. The enzyme activity profile method of bacterial identification is rapid, easily automated, and reproducible.

Aminopeptidases↗
PubMed1998

Application of probability techniques to the objective interpretation of veterinary clinical biochemistry data.

Methods for the interpretation of veterinary clinical biochemistry have not developed as rapidly as biochemical technology. However, the results of clinical biochemistry tests are only of value when they are interpreted appropriately. A retrospective study was undertaken to investigate the equine biochemistry data which had been stored in a veterinary hospital database. By applying percentile analysis and Bayesian probability methods to the clinical biochemistry and corresponding diagnosis data, a novel method for the interpretation of clinical biochemistry data has been developed. The method allows clinicians to determine whether a biochemistry value is abnormal, its degree of abnormality, and the most likely associated diagnoses. The method could be used to investigate a practice-based population and may have significant implications for the interpretation of clinical biochemistry data in veterinary medicine in the future.

Animals↗
PubMed1993

The calibration of a sit-ups task using the Rasch Poisson Counts model.

The purpose of this study was to calibrate a nationally used sit-ups test using the Rasch Poisson Counts model and evaluate the model-data fit. The total number of subjects was 8,723, consisting of 4,486 girls and 4,237 boys, ages 10 to 18. The estimated difficulty of the sit-ups task was -2.80, which was appropriate for a majority of examinees whose ability levels ranged from .09 to 1.39. After the calibration, boys and girls as well as different age groups were compared under the same metric. Graphs of the model-data fit demonstrated that the model-data fit at a low ability level was not as good as the fit at a high ability, which could be caused by violation of assumptions of the model that examinees have the same performance speed throughout the test and that the speed at a given time is independent of the number of sit-ups completed so far.

Adolescent↗