SEARCH · PubMed Health

Results for “Bayesian analysis”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11Linked to original sources

PubMed2006

Bayesian analysis using continuous likelihood ratios for identifying pleural exudates.

STUDY OBJECTIVES: To ascertain if equations that calculate continuous likelihood ratios (CLRs) for pleural exudates improve pleural fluid categorization, especially when false positive or false negative test results are obtained by using Light's criteria. DESIGN AND SETTING: Retrospective review of the clinical and pleural fluid data from a consecutive series of patients with pleural effusion who underwent thoracentesis at the University Hospital Arnau de Vilanova (Lleida, Spain) over an 11-year period. PATIENTS AND METHODS: A total of 1490 patients with pleural effusion (298 transudates and 1192 exudates) were recruited into the study. The presence of a transudate or exudate was established by clinical judgment. We examined the comparative diagnostic accuracy of 4 tests (i.e. pleural fluid protein and lactate dehydrogenase (LDH), and pleural fluid to serum protein and LDH ratios) for discriminating between transudates and exudates. Decision thresholds were determined by receiver operating characteristics (ROC) analysis. Equations for calculating CLRs derived from a logistic regression analysis based on a previously described method. RESULTS: Individual pleural fluid tests did not differ in their diagnostic accuracies according to ROC analysis. We calculated CLRs for the elements of Light's criteria and pleural fluid protein, and also illustrated the sequential use of CLRs for determining posttest probabilities. Overall, CLR formulas had marginal performance for the correct categorization of pleural fluid. CONCLUSIONS: CLRs provide a probabilistic statement as to the likelihood an effusion is a transudate or exudate. However, clinical judgment is little changed by the application of CLRs, and in doubtful cases a great amount of uncertainty remains. This Bayesian approach is likely to have no major impact on the clinical practice.

Bayes Theorem↗

PubMed2002

A Bayesian analysis of colonic crypt structure and coordinated response to carcinogen exposure incorporating missing crypts.

This paper is concerned with modeling the architecture of colonic crypts and the implications of this modeling for understanding possible coordinated response of carcinogen-induced DNA damage between various regions of the colon. The methods we develop to address these two issues are applied to a particular important example in colon carcinogenesis. We cast the problem as an unusual and not previously studied hierarchical mixed-effects model characterized by completely missing covariates in units at a structurally base level, except for some randomly selected units. Information concerning the missing covariates is available through certain known ordering constraints and surrogate measures. Our methods use Bayesian machinery. We exploit the biological structure of this problem to generate the missing covariates simultaneously and efficiently at the base levels, as opposed to the naive practice of generating units at the base levels one-at-a-time with Metropolis-Hastings steps. We apply our methods to show that different regions of the colon have different architectures, and to estimate an important but non-standard function that measures the interrelationship of DNA damage mechanisms in different regions of the colon.

Journal Article↗

PubMed2006

Bayesian analysis of the differences of count data.

Paired count data usually arise in medicine when before and after treatment measurements are considered. In the present paper we assume that the correlated paired count data follow a bivariate Poisson distribution in order to derive the distribution of their difference. The derived distribution is shown to be the same as the one derived for the difference of the independent Poisson variables, thus recasting interest on the distribution introduced by Skellam. Using this distribution we remove correlation, which naturally exists in paired data, and we improve the quality of our inference by using exact distributions instead of normal approximations. The zero-inflated version is considered to account for an excess of zero counts. Bayesian estimation and hypothesis testing for the models considered are discussed. An example from dental epidemiology is used to illustrate the proposed methodology.

Algorithms↗

PubMed2002

Phylogeny of the tree swallow genus, Tachycineta (Aves: Hirundinidae), by Bayesian analysis of mitochondrial DNA sequences.

To set the stage for historical analyses of the ecology and behavior of tree swallows and their allies (genus Tachycineta), we reconstructed the phylogeny of the nine Tachycineta species by comparing DNA sequences of six mitochondrial genes: Cytochrome b (990 base pairs), the second subunit of nicotinamide adenine dinucleotide dehydrogenase (839 base pairs), cytochrome oxidase II (85 base pairs), ATPase 8 (158 base pairs), tRNA-lysine (73 base pairs), and tRNA-methionine (25 base pairs). The phylogeny consisted of two main clades: South and Central American species ((T. stolzmanni, T. albilinea, T. albiventris), (T. leucorrhoa, T. meyeni)), and North American and Caribbean species (T. bicolor, (T. thalassina, T. euchrysea, T. cyaneoviridis)). The genetic distances among the species suggested that Tachycineta is a relatively old group compared to other New World swallow genera. One interesting biogeographic discovery was the close relationship between Caribbean and western North American taxa. This historical connection occurs in other groups of swallows and swifts as well. To reconstruct the phylogeny, we employed Bayesian as well as traditional maximum-likelihood methods. The Bayesian approach provided probability values for trees produced from the different genes and gene combinations, as well as probabilities of branches within those trees. We compared Bayesian and maximum-likelihood bootstrap branch support and found that all branches with Bayesian probabilities > or = 95% received bootstrap support >70%.

Adenosine Triphosphatases↗

PubMed2001

Bayesian analysis of geographical variation in the incidence of Type I diabetes in Finland.

AIMS/HYPOTHESIS: In Finland, the incidence of Type I (insulin-dependent) diabetes mellitus among children aged 14 years or under is the highest in the world. The increase in incidence is approximately 3% per year. A marked geographical variation in incidence was reported in Finland during the late 1980s. Our aim was to explore the most recent regional pattern in incidence of Type I diabetes in Finland. METHODS: Data on the nationwide incidence of childhood diabetes in Finland was obtained from the Prospective Childhood Diabetes Registry for the periods 1987-1991 and 1992-1996. Population data was obtained from the National Population Registry. The geographical pattern of incidence was studied applying a Bayesian hierarchical approach and Geographical Information Systems. The inferences from the data was based on the estimated geographical intensity of diabetes. RESULTS: There was a clear evidence of geographic variation for the risk of childhood diabetes during the entire 10-year period. The high-risk areas were found in the wide belt crossing the central part of Finland. Comparison of the estimated intensity of diabetes between the two 5-year periods showed that the geographical pattern of diabetes risk has changed over time. Our analyses also confirmed the existence of a few persistent high-risk and low-risk areas in Finland. CONCLUSION/INTERPRETATION: The finding of high-risk areas of childhood Type I diabetes suggests that specific genetic or environmental risk factors have become greater in certain geographic locations in Finland.

Adolescent↗

PubMed2006

Bayesian analysis of polyphonic western tonal music.

This paper deals with the computational analysis of musical audio from recorded audio waveforms. This general problem includes, as subtasks, music transcription, extraction of musical pitch, dynamics, timbre, instrument identity, and source separation. Analysis of real musical signals is a highly ill-posed task which is made complicated by the presence of transient sounds, background interference, or the complex structure of musical pitches in the time-frequency domain. This paper focuses on models and algorithms for computer transcription of multiple musical pitches in audio, elaborated from previous work by two of the authors. The audio data are supposedly presegmented into fixed pitch regimes such as individual chords. The models presented apply to pitched (tonal) music and are formulated via a Gabor representation of nonstationary signals. A Bayesian probabilistic structure is employed for representation of prior information about the parameters of the notes. This paper introduces a numerical Bayesian inference strategy for estimation of the pitches and other parameters of the waveform. The improved algorithm is much quicker and makes the approach feasible in realistic situations. Results are presented for estimation of a known number of notes present in randomly generated note clusters from a real musical instrument database.

Journal Article↗

PubMed2006

Bayesian analysis of the linear reaction norm model with unknown covariates.

The reaction norm model is becoming a popular approach for the analysis of genotype x environment interactions. In a classical reaction norm model, the expression of a genotype in different environments is described as a linear function (a reaction norm) of an environmental gradient or value. An environmental value is typically defined as the mean performance of all genotypes in the environment, which is usually unknown. One approximation is to estimate the mean phenotypic performance in each environment and then treat these estimates as known covariates in the model. However, a more satisfactory alternative is to infer environmental values simultaneously with the other parameters of the model. This study describes a method and its Bayesian Markov Chain Monte Carlo implementation that makes this possible. Frequentist properties of the proposed method are tested in a simulation study. Estimates of parameters of interest agree well with the true values. Further, inferences about genetic parameters from the proposed method are similar to those derived from a reaction norm model using true environmental values. On the other hand, using phenotypic means as proxies for environmental values results in poor inferences.

Bayes Theorem↗

PubMed2004

A bayesian analysis of metazoan mitochondrial genome arrangements.

Genome arrangements are a potentially powerful source of information to infer evolutionary relationships among distantly related taxa. Mitochondrial genome arrangements may be especially informative about metazoan evolutionary relationships because (1) nearly all animals have the same set of definitively homologous mitochondrial genes, (2) mitochondrial genome rearrangement events are rare relative to changes in sequences, and (3) the number of possible mitochondrial genome arrangements is huge, making convergent evolution of genome arrangements appear highly unlikely. In previous studies, phylogenetic evidence in genome arrangement data is nearly always used in a qualitative fashion-the support in favor of clades with similar or identical genome arrangements is considered to be quite strong, but is not quantified. The purpose of this article is to quantify the uncertainty among the relationships of metazoan phyla on the basis of mitochondrial genome arrangements while incorporating prior knowledge of the monophyly of various groups from other sources. The work we present here differs from our previous work in the statistics literature in that (1) we incorporate prior information on classifications of metazoans at the phylum level, (2) we describe several advances in our computational approach, and (3) we analyze a much larger data set (87 taxa) that consists of each unique, complete mitochondrial genome arrangement with a full complement of 37 genes that were present in the NCBI (National Center for Biotechnology Information) database at a recent date. In addition, we analyze a subset of 28 of these 87 taxa for which the non-tRNA mitochondrial genomes are unique where the assumption of our inversion-only model of rearrangement is more plausible. We present summaries of Bayesian posterior distributions of tree topology on the basis of these two data sets.

Animals↗

PubMed2005

Functional form and risk adjustment of hospital costs: Bayesian analysis of a Box-Cox random coefficients model.

While risk-adjusted outcomes are often used to compare the performance of hospitals and physicians, the most appropriate functional form for the risk adjustment process is not always obvious for continuous outcomes such as costs. Semi-log models are used most often to correct skewness in cost data, but there has been limited research to determine whether the log transformation is sufficient or whether another transformation is more appropriate. This study explores the most appropriate functional form for risk-adjusting the cost of coronary artery bypass graft (CABG) surgery. Data included patients undergoing CABG surgery at four hospitals in the midwest and were fit to a Box-Cox model with random coefficients (BCRC) using Markov chain Monte Carlo methods. Marginal likelihoods and Bayes factors were computed to perform model comparison of alternative model specifications. Rankings of hospital performance were created from the simulation output and the rankings produced by Bayesian estimates were compared to rankings produced by standard models fit using classical methods. Results suggest that, for these data, the most appropriate functional form is not logarithmic, but corresponds to a Box-Cox transformation of -1. Furthermore, Bayes factors overwhelmingly rejected the natural log transformation. However, the hospital ranking induced by the BCRC model was not different from the ranking produced by maximum likelihood estimates of either the linear or semi-log model.

Bayes Theorem↗

PubMed1981

[Dynamic ECG, exercise stress testing and coronary arteriography for the diagnosis of ischaemic heart disease. A Bayesian analysis of probability (author's transl)].

In spite of great technological improvement in Ambulatory ECG Monitoring (AEM), there is still debate about its reliability in detecting ECG signs of myocardial ischemia and about the utility of AEM and Exercise Stress Testing (ET)--apart and/or in association--to predict Coronary Artery Disease (CAD). 50 consecutive male patients (pts) (mean age 51 +/- 69 years, 37 to 64 years) were studied for precordial chest pain. 17 had evidence of previous myocardial infarction. Resting ECG was normal in 21 pts and abnormal in 29; no pt received therapy during the examination period. ECG recordings were considered positive for ischemic ECG changes if there was greater than or equal to 1 mm of horizontal or down sloping ST-segment depression or ST-segment elevation of the same degree for greater than or equal to 0.08 sec in at least 15 consecutive beats; coronary arteriography was considered positive for significant CAD if any major vessel had greater than or equal to 75% luminal diameter narrowing. The percentage of false negative results was similar in AEM and ET (22.7% vs 22.2%); the false positives were few with both tests: 2 pts and 1 pt respectively; Bayesian probability (post-test likelihood for disease) calculated using the prevalence of CAD estimated from 2124 male pts who underwent coronary angiography in our Laboratory, for a given test result was very high: 97.1% +/- 1.3% (AEM), 98.6% +/- 1.1% (ET) and 98.1% +/- 1.1% (AEM & ET if concordant); post-test likelihood for CAD in a patient who did not show the given test result decreased to 67.8% +/- 1.3% (AEM), 60.9% +/- 1.1% (ET) and 52.1% +/- 1.1% (AEM & ET if concordant). The application of Bayes' theorem to these two non invasive tests improves the evaluation of patients with suspected CAD; the association of AEM and ET enhances the diagnostic accuracy.

Adult↗

PubMed2003

Bayesian analysis of a multivariate null intercept errors-in-variables regression model.

Longitudinal data are of great interest in analysis of clinical trials. In many practical situations the covariate can not be measured precisely and a natural alternative model is the errors-in-variables regression models. In this paper we study a null intercept errors-in-variables regression model with a structure of dependency between the response variables within the same group. We apply the model to real data presented in Hadgu and Koch (Hadgu, A., Koch, G. (1999). Application of generalized estimating equations to a dental randomized clinical trial. J. Biopharmaceutical Statistics 9(1):161-178). In that study volunteers with preexisting dental plaque were randomized to two experimental mouth rinses (A and B) or a control mouth rinse with double blinding. The dental plaque index was measured for each subject in the beginning of the study and at two follow-up times, which leads to the presence of an interclass correlation. We propose the use of a Bayesian approach to model a multivariate null intercept errors-in-variables regression model to the longitudinal data. The proposed Bayesian approach accommodates the correlated measurements and incorporates the restriction that the slopes must lie in the (0, 1) interval. A Gibbs sampler is used to perform the computations.

Bayes Theorem↗

PubMed2002

A Bayesian analysis of a proportion under non-ignorable non-response.

The National Health Interview Survey (NHIS) is one of the surveys used to assess one aspect of the health status of the U.S. population. One indicator of the nation's health is the total number of doctor visits made by the household members in the past year. We study the binary variable of at least one doctor visit versus no doctor visit by all household members to each of the 50 states and the District of Columbia. The proportion of households with at least one doctor visit is an indicator of the status of health of the U.S. population. There is a substantial number of non-respondents among the sampled households. The main issue we address here is that the non-response mechanism should not be ignored because respondents and non-respondents differ. The purpose of this work is to estimate the proportion of households with at least one doctor visit, and to investigate what adjustment needs to be made for non-ignorable non-response. We consider a non-ignorable non-response model that expresses uncertainty about ignorability through the ratio of odds of a household doctor visit among respondents to the odds of doctor visit among all households, and this ratio varies from state to state. We use a hierarchical Bayesian selection model to accommodate this non-response mechanism. Because of the weak identifiability of the parameters, it is necessary to 'borrow strength' across states as in small area estimation. We also perform a simulation study to compare the expansion model with an alternative expansion model, an ignorable model and a non-ignorable model. Inference for the probability of a doctor visit is generally similar across the models. Our main result is that for some of the states the non-response mechanism can be considered non-ignorable, and that 95 per cent credible intervals of the probability for a household doctor visit and the probability that a household responds shed important light on the NHIS data.

Bayes Theorem↗

PubMed2006

Impact of reliance on CT pulmonary angiography on diagnosis of pulmonary embolism: a Bayesian analysis.

BACKGROUND: Spiral computed tomographic pulmonary angiography (CTPA) has become the primary test used to investigate suspected pulmonary embolism (PE) at many institutions, despite uncertainty regarding its sensitivity and specificity. Although CTPA-based diagnostic algorithms focus on minimizing the false-negative rate, we hypothesized that increasing use of CTPA also might lead to false-positive diagnoses. OBJECTIVE: Determine the frequency of possible false-positive diagnoses of PE when CTPA is the primary diagnostic test. DESIGN: Retrospective cohort study. SETTING: Two academic teaching hospitals. PARTICIPANTS: 322 patients with suspected PE evaluated with CTPA. MEASUREMENTS: We used a validated prediction rule to determine the pretest probability of PE in each patient. We combined these pretest probabilities with published estimates of CTPA test characteristics to generate expected posttest probabilities of PE. We compared these posttest probabilities to actual treatment decisions to determine the rate of false-positive diagnoses of PE. RESULTS: Among 322 patients investigated for PE, 37 (12%) had high pretest probability, 101 (32%) moderate, and 184 (57%) low. CT scans were interpreted as positive for PE in 57 patients (17.8%). Regardless of the pretest probability of PE, 96.5% of patients with a positive CTPA were treated with anticoagulants. Even under an optimistic assumption of CTPA test characteristics, as many as 25.4% of these patients may have been treated unnecessarily as a result of a false-positive diagnosis. Most of these patients had a low pretest probability of PE. CONCLUSIONS: Failure to utilize Bayesian reasoning when interpreting CTPA may lead to false-positive diagnoses of pulmonary embolism in a substantial proportion of patients.

Bayes Theorem↗

PubMed1990

The utility of routine screening of patients with uveitis for systemic lupus erythematosus or tuberculosis. A Bayesian analysis.

The indications for many laboratory tests in patients with uveitis are controversial. Bayes' theorem allows a mathematical approach to the assessment of the utility of a laboratory test based on the sensitivity of the test, the specificity of the test, and the pretest likelihood that the disease the test is intended to identify is present. We have utilized Bayes' theorem to assess the utility of routine antinuclear antibody and purified protein derivative testing in patients with uveitis. Based on published data about the sensitivity and specificity of each of these tests, as well as the prevalence of systemic lupus erythematosus and tuberculosis among patients with uveitis, we calculated that a patient with uveitis and a positive antinuclear antibody test result has less than a 1% chance of having systemic lupus erythematosus and that a patient with uveitis and a positive purified protein derivative test result has a 1% likelihood of having tuberculosis. These low probabilities mean that neither test is useful in the routine evaluation of patients with uveitis, and indiscriminate use may lead to improper diagnosis, increased costs, and, occasionally, inappropriate therapy.

Adult↗

PubMed1995