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PubMed1999

The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies.

The literature which considers the statistical properties of cost-effectiveness analysis has focused on estimating the sampling distribution of either an incremental cost-effectiveness ratio or incremental net benefit for classical inference. However, it is argued here that rules of inference are arbitrary and entirely irrelevant to the decisions which clinical and economic evaluations claim to inform. Decisions should be based only on the mean net benefits irrespective of whether differences are statistically significant or fall outside a Bayesian range of equivalence. Failure to make decisions in this way by accepting the arbitrary rules of inference will impose costs which can be measured in terms of resources or health benefits forgone. The distribution of net benefit is only relevant to deciding whether more information is required. A framework for decision making and establishing the value of additional information is presented which is consistent with the decision rules in CEA. This framework can distinguish the simultaneous but conceptually separate steps of deciding which alternatives should be chosen, given existing information, from the question of whether more information should be acquired. It also ensures that the type of information acquired is driven by the objectives of the health care system, is consistent with the budget constraint on service provision and that research is designed efficiently.

Bayes Theorem↗

PubMed2006

Variational Bayes inference of spatial mixture models for segmentation.

Mixture models are commonly used in the statistical segmentation of images. For example, they can be used for the segmentation of structural medical images into different matter types, or of statistical parametric maps into activating and nonactivating brain regions in functional imaging. Spatial mixture models have been developed to augment histogram information with spatial regularization using Markov random fields (MRFs). In previous work, an approximate model was developed to allow adaptive determination of the parameter controlling the strength of spatial regularization. Inference was performed using Markov Chain Monte Carlo (MCMC) sampling. However, this approach is prohibitively slow for large datasets. In this work, a more efficient inference approach is presented. This combines a variational Bayes approximation with a second-order Taylor expansion of the components of the posterior distribution, which would otherwise be intractable to Variational Bayes. This provides inference on fully adaptive spatial mixture models an order of magnitude faster than MCMC. We examine the behavior of this approach when applied to artificial data with different spatial characteristics, and to functional magnetic resonance imaging statistical parametric maps.

Algorithms↗

PubMed2003

Monte carlo conditional inference for log-linear and logistic models: a survey of current methodology.

Nuisance parameters are parameters that are not of immediate interest to the experimenter. For log-linear and logistic models the null distribution of (most) statistics of interest depends on such parameters. Traditionally, nuisance parameters were eliminated by performing inference with respect to the chi-squared limiting distribution of common test statistics. An alternative solution is to eliminate the nuisance parameters by conditioning on their minimal sufficient statistics. The support of the resulting conditional distribution is often intractable, making null probability calculations challenging. An often feasible way to avoid complete enumeration of this support is to approximate conditional probabilities using Monte Carlo methods. In this article we survey recent developments in Monte Carlo conditional analysis for log-linear and logistic models focusing on the algorithms proposed by Booth and Butler, Diaconis and Sturmfels, Smith et al., and Mehta et al. We illustrate these algorithms with simple motivating examples.

Algorithms↗

PubMed2005

Causal inference based on counterfactuals.

BACKGROUND: The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies. DISCUSSION: This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures. SUMMARY: Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept.

Causality↗

PubMed1993

Statistical tests of models of DNA substitution.

Penny et al. have written that "The most fundamental criterion for a scientific method is that the data must, in principle, be able to reject the model. Hardly any [phylogenetic] tree-reconstruction methods meet this simple requirement." The ability to reject models is of such great importance because the results of all phylogenetic analyses depend on their underlying models--to have confidence in the inferences, it is necessary to have confidence in the models. In this paper, a test statistic suggested by Cox is employed to test the adequacy of some statistical models of DNA sequence evolution used in the phylogenetic inference method introduced by Felsenstein. Monte Carlo simulations are used to assess significance levels. The resulting statistical tests provide an objective and very general assessment of all the components of a DNA substitution model; more specific versions of the test are devised to test individual components of a model. In all cases, the new analyses have the additional advantage that values of phylogenetic parameters do not have to be assumed in order to perform the tests.

Animals↗

PubMed2000

Chromosome abnormalities in ovarian adenocarcinoma: III. Using breakpoint data to infer and test mathematical models for oncogenesis.

Cancer geneticists seek to identify genetic changes in tumor cells and to relate the genetic changes to tumor development. Because single changes can disrupt the cell cycle and promote other genetic changes, it is extremely hard to distinguish cause from effect. In this article we illustrate how 7 techniques from statistics, theoretical computer science, and phylogenetics can be used to infer and test possible models of tumor progression from single genome-wide descriptions of aberrations in a large sample of tumors. Specifically, we propose 4 tree models for tumor progression inferred from the large ovarian cancer data set described in the first 2 articles in this series. The models are derived from 2 different methods to select the non-random genetic aberrations and 2 different methods to infer the trees, given a set of events. Various aspects of the tree models are tested and extended by 5 methods: overall tests of independence, likelihood ratio tests, principal components analysis, directed acyclic graph modeling, and Bayesian survival analysis. All our methods lead to strikingly consistent conclusions about chromosomal breakpoints in ovarian adenocarcinoma, including (1) the non-random breakpoints in ovarian adenocarcinoma do not occur independently; (2) breakpoints in regions 1p3 and 11p1 are important early events and distinguish a class of tumors associated with poor prognosis; and (3) breakpoints in 1p1, 3p1, and 1q2 distinguish a class of ovarian tumors, and the breaks at 1p1 and 3p1 are associated with poor prognosis.

Adenocarcinoma↗

PubMed1989

Striatal dysfunction in attention deficit and hyperkinetic disorder.

We have previously reported that periventricular structures are hypoperfused in attention deficit and hyperactivity disorder (ADHD). This study has expanded the number of patients, who were divided into two groups: six patients with pure ADHD, and 13 patients with ADHD in combination with other neurologic symptoms. By using xenon 133 inhalation and emission tomography, the regional cerebral blood flow distribution was determined and compared with a control group. Striatal regions were found to be hypoperfused and, by inference, hypofunctional in both groups. This hypoperfusion was statistically significant in the right striatum in ADHD, and in both striatal regions in ADHD with other neuropsychologic and neurologic symptoms. The primary sensory and sensorimotor cortical regions were highly perfused. Methylphenidate increased flow to striatal and posterior periventricular regions, and tended to decrease flow to primary sensory regions. Low striatal activity, partially reversible with methylphenidate, appears to be a cardinal feature in ADHD.

Attention Deficit Disorder with Hyperactivity↗

PubMed1988

Longitudinal versus cross-sectional estimation of lung function decline--further insights.

This paper explores the extent to which differences in longitudinal versus cross-sectional inference may be influenced by the choice of statistical models. Using lung function data on 524 working men, we first compare the goodness-of-fit and implication for longitudinal decline of a variety of cross-sectional models. We then compare the predicted longitudinal patterns from these models with those observed over a period of four years. In general, both approaches provide qualitatively, if not quantitatively, similar messages concerning the relative effects of smoking and age on lung function decline. Nonetheless, we acknowledge the existence of real selection and cohort effects. Although we recognize the utility of cross-sectional designs, we discourage quantitative comparisons between studies, especially longitudinal versus cross-sectional.

Adult↗

PubMed2001

"Voxel-based morphometry" should not be used with imperfectly registered images.

John Ashburner and Karl Friston (2000) introduced a standardized method of "voxel-based morphometry" (VBM) for comparisons of local concentrations of gray matter between two groups of subjects. Segmented images of gray matter from grossly normalized high-resolution images are smoothed and their group differences analyzed by the now-conventional voxelwise Worsley approach to Gaussian random fields of differences. This comment concerns an unfortunate interaction between the algorithm's spatial normalization and voxelwise comparison steps, whereby several obvious quantitative confounds are injected at the core of the inference engine the authors put forward. Specifically, the statistics of the resulting voxelwise comparisons are uninformative about group differences wherever the spatial normalization algorithm has failed to register on any robustly appearing image gradient. The method of Ashburner and Friston is defensible only far from all image gradients.

Artifacts↗

PubMed1997

A gene tree for beta-globin sequences from Melanesia.

We have analyzed allelic sequence variation in sixty-one 3-kb beta-globin sequences from the Melanesian population of Vanuatu to demonstrate the value of (1) turning to the autosomal nuclear genome for studies on the evolution of modern humans and (2) using new analytical methods based on a coalescent model. After excluding recombination events, beta-globin sequence variants were connected in a unique gene tree. A gene tree provides more information for inferences on the population genealogy than simple summary statistics such as the average pairwise sequence difference. Estimates of the time to the most recent common ancestor (MRCA) and of the ages of each mutation, conditional on the gene tree, were made using new maximum likelihood methods assuming a coalescent model. We found that allelic beta-globin variation coalesces to a single shared ancestral haplotype over a time scale of approximately 900,000 years. Three major haplotypes (A1, B1, C3) that are older than 200,000 years identify ancestral diversity contemporaneous with the single MRCA for mitochondrial variation.

Animals↗

PubMed2005

The significance of cognitive modeling in building healthcare interfaces.

BACKGROUND: Although there are many reasons that widespread adoption of healthcare information systems has not transpired, one reason is a failure to take into account the cognitive needs of the users. AIM: To understand the cognitive needs of nurses and physicians and determine how these needs should influence the design of healthcare interfaces. DESIGN OF STUDY: A qualitative and quantitative study that compares how nurses and physicians comprehend patient information. SETTING: Twenty-four registered nurses and twenty-four physicians working in the specialties of gastrointestinal or internal medicine. METHODS: Each clinician reviewed two mock electronic medical records and summarized the cases using a think-aloud protocol. All verbalizations were coded for medical and conceptual information. RESULTS: The nurses included a larger mean proportion (p<0.001) of recalls than did the physicians. As compared to the nurses, the physicians included a statistically significant (p<0.001) larger mean proportion of inferences, conditional statements, and interventions. The nurses concentrated on functional problems, whereas the physicians focused on diagnosis, treatment, and management. CONCLUSION: The main cognitive differences between the physicians and the nurses are explained through the differences in their practice models. Therefore, healthcare IT must develop separate interfaces for each discipline to address their unique needs.

Adult↗

PubMed1994

Ovarian cancer and pregnancy: comment on a paper by Whittemore et al.

We must concede that we were not able, with the published aggregate figures, to correct for the nuisance variables mentioned in the report, nor were we able to examine the individual "Study" results to derive estimates of "Between Study" variation, and so assess the regularity and statistical importance of the patterns observed. The tentative inferences outlined in this note are made therefore on the assumption that the analysis of these aggregate figures provides a fair reflection of the complete data base. Certainly, our analyses are numerically consistent with those in the report by Whittemore et al. (1). Because of the inconsistencies discovered between portions of the data presented by Whittemore et al. (1), we believe that the nature of the association between ovarian cancer and certain features such as nulliparity and age at first pregnancy remains unclear and demands further investigation, possibly with the very data base used by Whittemore and her colleagues.

Age Factors↗

PubMed2003

Recent results in cophylogeny mapping.

Virtually every problem in biology benefits from consideration within an evolutionary frame work. Parasitism has been part of life ever since one organism was able to provide an environment for another: questions of parasitology naturally lend themselves to consideration of the shared ancient history of parasites and hosts. The derivation of that shared history is therefore an area of great interest to theoreticians and practitioners alike. The most intuitive approach to this is by cophylogeny mapping. Mathematically the problem is that of optimally mapping the dependent tree into the independent one, e.g., parasite into host or gene tree into organismal phylogeny. This article describes some of the recent advances in cophylogenetic simulation, significance testing, and theoretical properties of maps. In simulation the author shows that the number of ways of mapping the parasite phylogeny into that of the hosts does indeed grow exponentially quickly in most cases and shows no close correlation with the similarity between the phylogenies, and that under a simple coevolutionary model, the range of behaviours of simulated parasite phylogenies is extremely broad and would appear to confound efforts to infer model parameters from observed cases. In the area of significance testing the author demonstrates that the maximal number of inferred codivergence events is not necessarily the best statistic for measuring cophylogenetic agreement, and that significance testing by randomisation which does not alter the parasite tree substantially biases results, and provides a new test to determine whether phylogenetic similarity is consistent with preferential host switching.

Animals↗

PubMedDate not supplied

[The problem of repeated measurements. Longitudinal analysis in epidemiology].

In longitudinal analyses subjects are repeatedly measured along time. They are mixed designs, characterised for their simultaneous consideration of two or more dimensions of analysis, in which time is one of the dimensions.Longitudinal analyses have important advantages with respect other designs. The most important is that they are more efficient, since they allow to distinguish between-individual and within-individual variation.Longitudinal analyses can be approached marginal and conditionally. Whereas the former allows to draw poblational, or average, inferences, the latter permits to draw individual inferences.The statistical models to use depend on the type of response variable. If the dependent variable is normally distributed one will use linear mixed models. When the response is a count one will use mixed Poisson regressions. Mixed binomial or multinomial logistic regressions should be used when the response would be categorical.

Epidemiologic Studies↗

PubMed1993

Interrupted time-series analysis with brief single-subject data.

Assessing change with short time-series data is difficult because visual inference is unreliable with such data, and current statistical procedures cannot control Type I error because they underestimate positive autocorrelation. This article describes these problems and shows how they can be solved with a new interrupted time-series analysis procedure (ITSACORR) that uses a more accurate estimate of autocorrelation. Monte Carlo analyses show that, with short series, ITSACORR provides better control of Type I error than all previous procedures and has acceptable power. Clinical examples also show that ITSACORR is easy to use and functions well with real data.

Adolescent↗

PubMed1984

Ultraviolet carcinogenesis in the hairless mouse skin. Influence of the sunscreen 2-ethylhexyl-p-methoxycinnamate.

The mutagenicity of some samples of a commonly used sunscreen, 2-ethylhexyl-p-methoxycinnamate (2-EHMC), led to these studies of its potential carcinogenicity in the HRA/Skh hairless mouse. In a daily treatment regime, repeated for 9 weeks, groups of mice were painted on the dorsum with 2-EHMC, and were then exposed to low doses of one of two artificial ultraviolet (UV) light sources. Mice were also treated with UV alone and with 2-EHMC alone. The accumulated UV exposure alone produced tumours in 40-100% of mice. However, 2-EHMC-treated mice were protected. Subsequent treatment of the 2-EHMC-protected mice, and mice previously treated with 2-EHMC alone, with the tumour promoter, croton oil, produced tumours on a significant number of animals. We conclude that 2-EHMC protects from UV tumorigenesis in the absence of a tumour promoter. However, although tumours appeared on only 4 out of 160 2-EHMC-treated mice exposed to UV, the carcinogenic process had been initiated in others, as application of the tumour promoter, croton oil, produced tumours. Statistical analysis of the incidence of promoted tumours inferred that prior irradiation with UV may not have been implicated. Therefore, 2-EHMC itself may initiate tumours in this strain of hairless mouse.

Animals↗

PubMed2003

Control of confounding of genetic associations in stratified populations.

To control for hidden population stratification in genetic-association studies, statistical methods that use marker genotype data to infer population structure have been proposed as a possible alternative to family-based designs. In principle, it is possible to infer population structure from associations between marker loci and from associations of markers with the trait, even when no information about the demographic background of the population is available. In a model in which the total population is formed by admixture between two or more subpopulations, confounding can be estimated and controlled. Current implementations of this approach have limitations, the most serious of which is that they do not allow for uncertainty in estimations of individual admixture proportions or for lack of identifiability of subpopulations in the model. We describe methods that overcome these limitations by a combination of Bayesian and classical approaches, and we demonstrate the methods by using data from three admixed populations--African American, African Caribbean, and Hispanic American--in which there is extreme confounding of trait-genotype associations because the trait under study (skin pigmentation) varies with admixture proportions. In these data sets, as many as one-third of marker loci show crude associations with the trait. Control for confounding by population stratification eliminates these associations, except at loci that are linked to candidate genes for the trait. With only 32 markers informative for ancestry, the efficiency of the analysis is 70%. These methods can deal with both confounding and selection bias in genetic-association studies, making family-based designs unnecessary.

Bayes Theorem↗

PubMed1993

Recovering phylogenetic signal from DNA sequences: relationships within the corvine assemblage (class aves) as inferred from complete sequences of the mitochondrial DNA cytochrome-b gene.

Phylogenetic analysis of cytochrome-b sequences and cranial osteological characters for nine genera of corvine passerine birds supports the hypothesis that the two major groups of birds of paradise, the manucodines and paradisaeinines, constitute a monophyletic group and that their postulated sister group is the Corvidae (crows, jays, and allies). The data are also consistent with the hypothesis that the bowerbirds are not closely related to the birds of paradise but instead lie near the base of the corvine assemblage. The corvine radiation exemplifies a case of multiple star phylogenies embedded within a major clade, with the branching pattern characterized by very short internodal divergence times. Such histories are difficult to resolve no matter what type of data is employed, because little change accumulates between branching events. With respect to sequence data, reconstructed tree topologies are sensitive to the choice of outgroup and to the method of analysis (e.g., transversion vs. global parsimony). In such cases, assessing the "reliability" of a best-fit or most-parsimonious tree inferred from any particular data set becomes problematic. Statistical tests of tree topologies that depend on random sampling of characters will generally be inconclusive in that all cladistic components will tend to be poorly supported because relatively few character-state changes will be recorded between branching events. It is suggested, on the other hand, that congruence in cladistic signal across different data sets may be a potentially more useful method for evaluating the reliability of the signal of any one data set. Resolution of star phylogenies will probably be possible only if DNA sequence and morphological characters are combined in a single analysis.

Animals↗