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PubMed1999

Statistical methods for the Ames Salmonella assay: a review.

The Ames Salmonella assay remains the most widely used in vitro genotoxicity assay. Several statistical methods have been proposed for its analysis [B.H. Margolin, N. Kaplan, E. Zeiger, Statistical analysis of the Ames Salmonella/microsome test, Proc. Natl. Acad. Sci., 78 (1981) 3779-3783; L.E. Myers, N.H. Saxton, L.I. Southerland, T.J. Wolff, Regression analysis of Ames test data, Environ. Mol. Mutagen., 3 (1981) 575-586; A.G. Stead, V. Hasselblad, J.P. Creason, L. Claxton, Modelling the Ames test, Mutation Res., 85 (1981) 13-27; L. Bernstein, J. Kaldor, J. McCaan, M.C. Pike, An empirical approach to the statistical analysis of mutagenesis data from the Salmonella test, Mutation Res., 97 (1982) 267-281; N.E. Breslow, Extra-Poisson variation in log-linear models, Appl. Stat., 33 (1984) 38-44; J. Wahrendorf, G.A.T. Mahon, M. Schumacher, A nonparametric approach to the statistical analysis of mutagenicity data, Mutation Res., 147 (1985) 5-13; D.G. Simpson, B.H. Margolin, Recursive nonparametric testing for dose-response relationships subject to downturns at high doses, Biometrika, 73 (1986) 589-596; D.G. Simpson, B.H. Margolin, Nonparametric testing for dose-response curves subject to downturns: Asymptotic power considerations, Annals Stat., 18 (1990) 373-390.]. In this paper we review recent literature to see what statistical methods are in fact employed for the analysis of the Ames assay. We then note that these methods can be classified into a common category in the framework of Haynes and Eckardt's mutation induction kinetics model [R.H. Haynes, F. Eckardt, Mathematical analysis of mutation induction kinetics, in: F.J. de Serres, A. Hollaender (Eds. ), Chemical Mutagens, Principles and Methods for Their Detection, Vol. 6, Plenum, New York, 1980, pp. 271-307]. The value in knowing this is that most methods of analysis considered here will likely exhibit common statistical behavior. These analyses are computationally intensive, e.g., [B.H. Margolin, N. Kaplan, E. Zeiger, Statistical analysis of the Ames Salmonella/microsome test, Proc. Nat. Acad. Sci., 78 (1981) 3779-3783], hence the ready availability of computer programs is essential if biologists are to use these methods. We briefly review two statistical software programs that are available in the public domain, and describe in detail a third program, Salm, [B.H. Margolin, N. Kaplan, E. Zeiger, Statistical analysis of the Ames Salmonella/microsome test, Proc. Nat. Acad. Sci., 78 (1981) 3779-3783; B.H. Margolin, B.S. Kim, K. Risko, The Ames Salmonella/microsome assay: Issues of inference and validation, J. Amer. Stat. Assoc., 84 (1989) 651-661]. The Salm program is obtainable through the file transfer protocol (ftp) or using a WWW browser. Finally, we discuss two statistical consequences of naively applying the two-fold rule, a method of analysis employed by a number of researchers.

Dose-Response Relationship, Drug↗
PubMed2004

Tests for multivariate recurrent events in the presence of a terminal event.

In studies involving diseases associated with high rates of mortality, trials are frequently conducted to evaluate the effects of therapeutic interventions on recurrent event processes terminated by death. In this setting, cumulative mean functions form a natural basis for inference for questions of a health economic nature, and Ghosh and Lin (2000) recently proposed a relevant class of test statistics. Trials of patients with cancer metastatic to bone, however, involve multiple types of skeletal complications, each of which may be repeatedly experienced by patients over their lifetime. Traditionally the distinction between the various types of events is ignored and univariate analyses are conducted based on a composite recurrent event. However, when the events have different impacts on patients' quality of life, or when they incur different costs, it can be important to gain insight into the relative frequency of the specific types of events and treatment effects thereon. This may be achieved by conducting separate marginal analyses with each analysis focusing on one type of recurrent event. Global inferences regarding treatment benefit can then be achieved by carrying out multiplicity adjusted marginal tests, more formal multiple testing procedures, or by constructing global test statistics. We describe methods for testing for differences in mean functions between treatment groups which accommodate the fact that each particular event process is ultimately terminated by death. The methods are illustrated by application to a motivating study designed to examine the effect of bisphosphonate therapy on the incidence of skeletal complications among patients with breast cancer metastatic to bone. We find that there is a consistent trend towards a reduction in the cumulative mean for all four types of skeletal complications with bisphosphonate therapy; there is a significant reduction in the need for radiation therapy for the treatment of bone. The global test suggests that bisphosphonate therapy significantly reduces the overall number of skeletal complications.

Antineoplastic Agents↗
PubMed2006

Inferring evolutionary signals from ecological data in a plant-pathogen metapopulation.

We followed the dynamics of local epidemics in three populations of a natural plant-pathogen system for four sequential years. We characterize the overwintering process with spatial statistics and use a stochastic, spatially explicit, modeling approach with Bayesian parameter estimation to study the spread of the infection during the growing season. Our modeling approach allows us to infer coevolutionary signals from spatiotemporal data on pathogen prevalence. Most importantly, we are able to assess the distribution of resistant hosts within the distribution of all host plants. We show that resistant hosts occur in areas with high pathogen encounter rates, and that the occurrence of resistance correlates with overwintering probability of the pathogen. The estimates for essentially all model parameters are characterized by a large amount of variation over the years and the populations. While the variation in the fraction of resistant hosts and in the force of infection is to a large extent explained by the population, the other model parameters (two parameters describing the shape of the dispersal kernel) vary essentially in an unpredictable manner, suggesting that much of the variation may occur at very fine spatial and temporal scales.

Bayes Theorem↗
PubMed2001

Integrating psychopathological dimensions in functional psychoses: a hierarchical approach.

Previous factor analysis studies of psychotic symptomatology have demonstrated three psychopathological dimensions: positive, negative and disorganization. However, few studies have analyzed non-schizophrenic samples and most use a syndrome-level of analysis or only schizophrenic symptom scales. This study examined how many dimensions underlie psychosis, and whether within psychosis there is a hierarchical organization of dimensions.A total of 660 inpatients with an acute psychotic episode were studied. Psychopathology was measured through a wide psychopathological assessment using the Manual for the Assessment and Documentation of Psychopathology (AMDP-system). Principal component factor analysis was carried out on 64 psychopathological symptoms scoring 1 or higher in at least 10% of the sample. A 15-factor solution was obtained which failed to depict a psychosis model on clinical and methodological grounds. Further predetermined factor analyses ranging from 1 to 15 factors were carried out to examine alternative factor solutions. A 10-dimensional model was the best model on clinical, statistical and conceptual grounds. Moreover, the examination of the 1 to 10 dimensional models allowed us to infer a hierarchical model of psychopathological dimensions, which can be represented in the frame of a tree-structure. The model permitted transitions between psychiatric categories and psychopathological dimensions, and it was able to integrate previous factor solutions with different numbers of resulting dimensions.The findings have implications for the design of future studies and for the hierarchical conceptualization of psychopathological dimensions.

Adult↗
PubMed2003

Multiple outputation: inference for complex clustered data by averaging analyses from independent data.

This article applies a simple method for settings where one has clustered data, but statistical methods are only available for independent data. We assume the statistical method provides us with a normally distributed estimate, theta, and an estimate of its variance sigma. We randomly select a data point from each cluster and apply our statistical method to this independent data. We repeat this multiple times, and use the average of the associated theta's as our estimate. An estimate of the variance is given by the average of the sigma2's minus the sample variance of the theta's. We call this procedure multiple outputation, as all "excess" data within each cluster is thrown out multiple times. Hoffman, Sen, and Weinberg (2001, Biometrika 88, 1121-1134) introduced this approach for generalized linear models when the cluster size is related to outcome. In this article, we demonstrate the broad applicability of the approach. Applications to angular data, p-values, vector parameters, Bayesian inference, genetics data, and random cluster sizes are discussed. In addition, asymptotic normality of estimates based on all possible outputations, as well as a finite number of outputations, is proven given weak conditions. Multiple outputation provides a simple and broadly applicable method for analyzing clustered data. It is especially suited to settings where methods for clustered data are impractical, but can also be applied generally as a quick and simple tool.

Acute Disease↗
PubMed2004

Discovery of meaningful associations in genomic data using partial correlation coefficients.

MOTIVATION: A major challenge of systems biology is to infer biochemical interactions from large-scale observations, such as transcriptomics, proteomics and metabolomics. We propose to use a partial correlation analysis to construct approximate Undirected Dependency Graphs from such large-scale biochemical data. This approach enables a distinction between direct and indirect interactions of biochemical compounds, thereby inferring the underlying network topology. RESULTS: The method is first thoroughly evaluated with a large set of simulated data. Results indicate that the approach has good statistical power and a low False Discovery Rate even in the presence of noise in the data. We then applied the method to an existing data set of yeast gene expression. Several small gene networks were inferred and found to contain genes known to be collectively involved in particular biochemical processes. In some of these networks there are also uncharacterized ORFs present, which lead to hypotheses about their functions. AVAILABILITY: Programs running in MS-Windows and Linux for applying zeroth, first, second and third order partial correlation analysis can be downloaded at: http://mendes.vbi.vt.edu/tiki-index.php?page=Software. SUPPLEMENTARY INFORMATION: Supplementary information can be found at: URL to be decided.

Algorithms↗
PubMedDate not supplied

The causal role for genital ulcer disease as a risk factor for transmission of human immunodeficiency virus. An application of the Bradford Hill criteria.

BACKGROUND AND OBJECTIVES: Genital ulcer disease (GUD) has been reported to increase the risk for the acquisition of human immunodeficiency virus (HIV). Although many investigators have reported an increased risk for HIV infection in persons with concurrent or previous GUD, not all studies have been designed to determine whether GUD causes an increased risk for HIV infection or acts only as a risk marker for infection. The evidence from the literature is discussed, and the criteria for causal inference proposed by Sir Austin Bradford Hill are applied. GOAL: To evaluate the strength of the association between GUD and infection by HIV. STUDY DESIGN: Case-control, cross-sectional, and cohort studies that examined the association between HIV seroconversion and GUD were chosen from the literature. Twenty-seven epidemiologic studies were selected for analysis, many of which reported separate analyses of the association between HIV infection and herpes simplex virus infection, syphilis, or nonspecified GUD. The studies were analyzed to investigate the magnitude of association between GUD and HIV, and the evidence evaluated using Hill's criteria. RESULTS: Approximately two thirds of the analyses reported a statistically significant association between GUD and HIV infection. Fourteen studies reported 29 separate analyses using a case-control design, 18 of which reported a statistically significant association between GUD (GUD, herpes, and syphilis) and HIV infection, four analyses were of varying significance depending on the analytical technique used, and seven were nonsignificant. Thirteen studies reported 23 separate longitudinal analyses that used a nested case-control or cohort design: 11 reported a significant association, 11 had nonsignificant findings, and results of one study varied. No study reported a statistically significant negative association. When applying the literature to Hill's criteria, all nine criteria for causal inference were met, providing additional evidence that genital ulcers are associated with an increased risk for the development of HIV infection. CONCLUSIONS: The published evidence suggests that GUD increases the risk for HIV acquisition. Few studies, however, have examined carefully the temporal association between preexisting GUD and subsequent HIV acquisition. The analyses that simultaneously controlled for additional risks for HIV infection, such as lifetime sex partners or history of injection drug use, report a generally lower risk for HIV associated with GUD. It is likely that studies that adequately control for risk factors will find a lower risk associated with GUD than was reported in the literature earlier in the HIV epidemic. Future research needs and the problems associated with conducting these types of studies are discussed.

Case-Control Studies↗
PubMed1988

Exact inference for matched case-control studies.

In an epidemiological study with a small sample size or a sparse data structure, the use of an asymptotic method of analysis may not be appropriate. In this paper we present an alternative method of analyzing data for case-control studies with a matched design that does not rely on large-sample assumptions. A recursive algorithm to compute the exact distribution of the conditional sufficient statistics of the parameters of the logistic model for such a design is given. This distribution can be used to perform exact inference on model parameters, the methodology of which is outlined. To illustrate the exact method, and compare it with the conventional asymptotic method, analyses of data from two case-control studies are also presented.

Algorithms↗
PubMed2000

[Proof of equivalence as a new issue in confirmatory statistics].

A correct confirmatory analysis of studies aiming at demonstration of equivalence requires the use of a class of testing procedures that is still widely unknown among non-specialists and not even mentioned in traditional textbooks on Applied Statistics. The naive approach to equivalence testing, i.e. performing an ordinary two-sided test and inferring equivalence from the absence of a significant difference, is unacceptable since it entails an uncontrolled increase of the risk of false positive conclusions. A technically simple approach to avoiding such fallacies is based on the principle of confidence interval inclusion. However, the latter suffers from the disadvantage of yielding testing procedures that tend to exhibit comparatively poor power properties. For the sake of keeping the numbers of patients or subjects to be recruited for the respective trials as low as possible, application of optimum testing procedures, also for equivalence assessment, has much to recommend it. The rationale of such an optimum test for equivalence is described in some detail for four standard settings frequently encountered in clinical research.

Binomial Distribution↗
PubMed2000

Assessment of the population structure of five Finnish dog breeds with microsatellites.

Genetic variabilities within and between Finnish populations of Golden Retrievers, German Shepherds, Wirehaired Dachshunds, Pembroke Welsh Corgis and Bedlington Terriers were quantified with microsatellite allele numbers, observed heterozygosities, expected heterozygosities, FIS estimates, FST estimates and DS distances. In a sample of 50 individuals from each, breed and ten polymorphic loci, the highest genetic diversity was exhibited in the Wirehaired Dachshunds and lowest in the Bedlington Terriers. Although statistically significant deviations from the Hardy-Weinberg (H-W) equilibrium were observed, they occurred at an unexpectedly low frequency. Most strikingly, the extremely small Bedlington Terrier population displayed genotypes in H-W proportions in all investigated loci. The H-W deviations always occurred with positive FIS estimates, which, on average, were not larger than values reported for free-living canids. Genetic differentiation between the breeds was very large. As a comparison, present estimates were, on average, over two times higher than previously observed between breeds of sheep, and over two times higher than the highest estimates reported between human populations. Moreover, the highest DS distances were only slightly lower than the lowest values inferred between humans and chimpanzees. Severe bottlenecks in the recent past of the examined breeds were not statistically supported. The presented data imply genetic isolation and intense artificial selection in the history of these breeds of dogs.

Alleles↗
PubMed2003

Analysis of metabolic syndrome phenotypes in Framingham Heart Study families from Genetic Analysis Workshop 13.

Twelve teams of investigators constituted a group which analyzed phenotypes related to metabolic syndrome, making use of the available longitudinal measurements from the family component of the Framingham Heart Study or the simulated data, as distributed by Genetic Analysis Workshop 13 (GAW13). Body mass index, obesity, lipid abnormalities, glucose, or combinations of these traits were analyzed by this group. A wide variety of approaches were taken to construct phenotypes from the longitudinal measurements, including considering single or multiple cross-sectional time points, single ages, minimum values, maximum values, means, other lifetime values, ever/never dichotomy, or age at onset of some threshold value. Approaches also differed in the family structures utilized (sib pairs to full extended pedigrees), the genetic data considered (two-point or multipoint), and the statistics calculated (model-free and parametric), and led to a diverse set of analyses being performed. Inferences were made about heritability, and attempts were made to map underlying genes. Over 40 genome-wide linkage analyses were conducted. Despite the broad range of approaches, several regions of the genome were repeatedly identified across multiple analyses.

Cardiovascular Diseases↗
PubMed1983

A statistical method for the estimation of neuronal response latency and its functional interpretation.

The functional role of many central nervous structures has been inferred from the temporal relationship of a neuronal response with the different sensory and motor events in an experimental design such as when an animal performs a trained movement in response to a conditioned stimulus. However, this kind of data analysis leads to problems in estimating the occurrence and latency of any neuronal response. We examine these problems and propose a novel technique of data analysis to estimate the point of change in a sequence of neuronal discharge. Furthermore, data can be tested to see whether the neuronal response is related to the conditioned stimulus or the motor act. The method can also be used in the simple situation of determining the latency of a neuronal response after a stimulus.

Animals↗
PubMed2002

Estimating the distribution of worm burden and egg excretion of Schistosoma japonicum by risk group in Sichuan Province, China.

During autumn 2000 an extensive cross-sectional survey of the prevalence of Schistosomiasis japonicum was conducted among about 4000 villagers within 20 villages in the Anning River Valley located in the southwestern Sichuan Province. Two procedures were used to assess infection status, the Kato-Katz thick smear procedure and a miracidia hatch test. Whereas the Kato-Katz procedure provides information on both prevalence and intensity, the hatch test provides only prevalence data, albeit on a much larger volume of stool. In addition, we performed Kato-Katz smears for 15 consecutive samples on a subset of 15 individuals. The proportion of both hatch-test and Kato-Katz positive individuals in the larger cross-sectional survey was 25%. The goal of the study was to estimate both the egg and worm distributions among risk groups using both the hatch and Kato-Katz tests from the cross-sectional data and the repeated Kato-Katz smears from the longitudinal data sets. As a prelude to parameter estimation, individuals were classified into risk groups by natural village and occupation; the proportion of Kato-Katz positive subjects among the risk groups varied from 10% to 60%. We used the statistical model of de Vlas et al. (1992) and Bayesian techniques to derive both estimates of and inference about the worm and egg distribution parameters. The parameter estimates imply (1) similar eggs per gram stool (e.p.g.) per worm pair compared with earlier estimates, (2) a range of worm burdens among the risk groups and (3) estimates of risk heterogeneity within groups is sensitive to prior information on the within-person variability in egg excretion.

Age Factors↗
PubMed1991

Relationship between fetal weight and malformation in developmental toxicity studies.

Exposure to developmental toxicants may cause fetal malformations, increase prenatal death rates and reduce fetal weight at term. However, there has been little formal study of the relationship among these effects. Certainly, no statistical methods are currently available to jointly analyze these effects of exposure. As a preliminary step in developing such methods, simple exploratory analyses were conducted using a series of ten studies conducted for the National Toxicology Program. Because fetal weight and malformation status were both reported for all live fetuses, the data permitted an exploration of the correlation between these two outcomes. The data show a clear pattern wherein malformed fetuses tended to be lighter at term than nonmalformed fetuses. While these patterns cannot be used to draw inferences regarding the biological relationship between fetal weight and malformation, they do suggest the potential value in developing statistical models for the joint effect of exposure on fetal weight and malformations.

Animals↗
PubMed2000

Variability in fMRI: an examination of intersession differences.

The results from a single functional magnetic resonance imaging session are typically reported as indicative of the subject's functional neuroanatomy. Underlying this interpretation is the implicit assumption that there are no responses specific to that particular session, i.e., that the potential variability of response between sessions is negligible. The present study sought to examine this assumption empirically. A total of 99 sessions, comprising 33 repeats of simple motor, visual, and cognitive paradigms, were collected over a period of 2 months on a single male subject. For each paradigm, the inclusion of session-by-condition interactions explained a significant amount of error variance (P < 0.05 corrected for multiple comparisons) over a model assuming a common activation magnitude across all sessions. However, many of those voxels displaying significant session-by-condition interactions were not seen in a multisession fixed-effects analysis of the same data set; i.e., they were not activated on average across all sessions. Most voxels that were both significantly variable and activated on average across all sessions did not survive a random-effects analysis (modeling between-session variance). We interpret our results as demonstrating that correct inference about subject responses to activation tasks can be derived through the use of a statistical model which accounts for both within- and between-session variance, combined with an appropriately large session sample size. If researchers have access to only a single session from a single subject, erroneous conclusions are a possibility, in that responses specific to this single session may be claimed to be typical responses for this subject.

Adult↗
PubMed1980

HLA antigen frequencies in patients with Huntington's chorea and their relatives.

Twenty patients with Hungtington's chorea and 30 family members were typed for 30 antigens of the HLA-A, B, and C series. There was an increased frequency of HLA-BW 16, significant at the 1%-level. After correcting for multiple inferences, the association of HLA-BW 16 with Huntington's chorea was no longer statistically significant. There was also no reliable indication of coupling between HLA antigens and Huntington's chorea in the family studies.

Adult↗
PubMed1982

Problems in the assessment of relative risk of chronic disease among biological relatives of affected individuals.

A question often asked in regard to a chronic disease is whether the risk to a biological relative of a case is evaluated, and if so by how much the risk is altered. To answer this question, data may be collected directly with genetic objectives in mind by ascertaining population of pedigrees. More often, the initial assessment of the question comes from family history data collected in an incidental manner in the course of a case-control or similar type of study. This paper discusses some limitations to the inferences which can be derived from such casual family history data. These include (i) poor statistical properties of standard relative risk measures, (ii) interpretational problems of observed relative risks when affected cases arise from genetic as well as nongenetic causes and when genes may not always be expressed in individuals in whom they are present, and (iii) confounding effects which may occur when a high risk allele alters the age of onset pattern of the disease. These problems result largely from a loss of design control over the degree of exposure of individuals ascertained and can lead to a small observed relative risk value even when genetic factors are important. Suggestions for handling such casual family history data are offered.

Age Factors↗
PubMed1996

Migration of persons with AIDS--a search for support from elderly parents?

In this paper we investigate the interstate migration of people with AIDS to Florida under the hypothesis that a significant proportion of these moves are made to access care and support from elderly parents. We present a variety of aggregate data to support this hypothesis. Data recording interstate moves to Florida show that over 19% of interstate migrants with AIDS chose small cities and largely rural counties as their destinations, places without well-developed medical and social service facilities beneficial to people with AIDS. Moreover, the highest in-migration rates are in counties with the greatest proportion of elderly people, who are mostly retirees from other states. A Poisson regression model of destination choice indicates that the attraction of places with a high proportion of the population over 65 is statistically significant, after controlling for other factors that may also draw migrants with AIDS. We infer from analysis of trends in migration flows, that some people with AIDS may be relocating to seek support from elderly parents.

Acquired Immunodeficiency Syndrome↗