SEARCH · PubMed Health

Results for “likelihood”

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 469 records · Page 26Linked to original sources

PubMed2002

Hierarchical-likelihood approach for mixed linear models with censored data.

Mixed linear models describe the dependence via random effects in multivariate normal survival data. Recently they have received considerable attention in the biomedical literature. They model the conditional survival times, whereas the alternative frailty model uses the conditional hazard rate. We develop an inferential method for the mixed linear model via Lee and Nelder's (1996) hierarchical-likelihood (h-likelihood). Simulation and a practical example are presented to illustrate the new method.

Animals↗

PubMed2003

Maximum likelihood estimation of life-span based on censored and passively registered historical data.

We consider the estimation of life length of people who were born in the seventeenth or eighteenth century in England. The data consist of a sequence of times of life events that is either ended by a time of death or is right-censored by an unobserved time of migration. We propose a semi parametric model for the data and use a maximum likelihood method to estimate the unknown parameters in this model. We prove the consistency of the maximum likelihood estimators and describe an algorithm to obtain the estimates numerically. We have applied the algorithm to data and the estimates found are presented.

Algorithms↗

PubMed1997

The use of likelihood-based confidence intervals in genetic models.

This article describes the computation and relative merits of likelihood-based confidence intervals, compared to other measures of error in parameter estimates. Likelihood-based confidence intervals have the advantage of being asymmetric, which is often the case with structural equation models for genetically informative studies. We show how the package Mx provides confidence intervals for parameters and functions of parameters in the context of a simple additive genetic, common, and specific environment threshold model for binary data. Previously published contingency tables for major depression in adult female twins are used for illustration. The support for the model shows a marked skew as the additive genetic parameter is systematically varied from zero to one. The impact of allowing different prevalence rates in MZ vs. DZ twins is explored by fitting a model with separate threshold parameters and comparing the confidence intervals. Despite the improvement in fit of the different prevalence model, the confidence intervals on all parameters broaden, owing to their covariance.

Adult↗

PubMed1996

Reconciling simplicity and likelihood principles in perceptual organization.

Two principles of perceptual organization have been proposed. The likelihood principle, following H. L. F. von Helmholtz (1910/1962), proposes that perceptual organization is chosen to correspond to the most likely distal layout. The simplicity principle, following Gestalt psychology, suggests that perceptual organization is chosen to be as simple as possible. The debate between these two views has been a central topic in the study of perceptual organization. Drawing on mathematical results in A. N. Kolmogorov's (1965) complexity theory, the author argues that simplicity and likelihood are not in competition, but are identical. Various implications for the theory of perceptual organization and psychology more generally are outlined.

Attention↗

PubMed2000

Maximum likelihood analysis of quantitative trait loci under selective genotyping.

Selective genotyping is a cost-saving strategy in mapping quantitative trait loci (QTLs). When the proportion of individuals selected for genotyping is low, the majority of the individuals are not genotyped, but their phenotypic values, if available, are still included in the data analysis to correct the bias in parameter estimation. These ungenotyped individuals do not contribute much information about linkage analysis and their inclusion can substantially increase the computational burden. For multiple trait analysis, ungenotyped individuals may not have a full array of phenotypic measurements. In this case, unbiased estimation of QTL effects using current methods seems to be impossible. In this study, we develop a maximum likelihood method of QTL mapping under selective genotyping using only the phenotypic values of genotyped individuals. Compared with the full data analysis (using all phenotypic values), the proposed method performs well. We derive an expectation-maximization (EM) algorithm that appears to be a simple modification of the existing EM algorithm for standard interval mapping. The new method can be readily incorporated into a standard QTL mapping software, e.g. MAPMAKER. A general recommendation is that whenever full data analysis is possible, the full maximum likelihood analysis should be performed. If it is impossible to analyse the full data, e.g. sample sizes are too large, phenotypic values of ungenotyped individuals are missing or composite interval mapping is to be performed, the proposed method can be applied.

Algorithms↗

PubMed2002

Simplifying likelihood ratios.

Likelihood ratios are one of the best measures of diagnostic accuracy, although they are seldom used, because interpreting them requires a calculator to convert back and forth between "probability" and "odds" of disease. This article describes a simpler method of interpreting likelihood ratios, one that avoids calculators, nomograms, and conversions to "odds" of disease. Several examples illustrate how the clinician can use this method to refine diagnostic decisions at the bedside.

Diagnosis↗

PubMed2002

Improving homeopathic prescribing by applying epidemiological techniques: the role of likelihood ratio.

A committee of the Dutch Association of Homeopathic Physicians is trying to validate materia medica by evaluating successful cases. These cases are presented and assessed by a group of experienced homeopathic physicians to provide indications about the prevalence of symptoms related to particular homeopathic medicines. The next logical question is whether epidemiological techniques can be applied to them. We have some ideas concerning the information these data can provide, based on epidemiological theory and limited experimental data. Theoretical investigation suggests that the epidemiological concept of likelihood ratio is well adapted to homeopathy. Researching and applying likelihood ratio will lead to more accurate materia medica and repertory. These considerations already indicate some shortcomings in the representation of rare remedies and the use of grading in the current repertories.

Drug Prescriptions↗

PubMed2003

Evidence-based emergency medicine/skills for evidence-based emergency care. Interval likelihood ratios: another advantage for the evidence-based diagnostician.

Emergency physicians are often confronted with making diagnostic decisions on the basis of a test result represented on a continuous scale. When the results of continuous data are expressed as binary outcomes using a single cutoff, loss of information and distortion may occur. In this setting, interval likelihood ratios provide a distinct advantage in interpretation over those based on a dichotomized sensitivity and specificity. Dividing the data into intervals uses more of the information contained in the data and allows the clinician to more appropriately interpret the test results and to make valid clinical decisions. This article illustrates the advantages of interval likelihood ratios with examples and demonstrates how to calculate them on the basis of different data formats. Authors and journals need to be encouraged to report the results of studies of performance of diagnostic tests using interval ranges rather than simple dichotomization when the tests involve continuous variables.

Confidence Intervals↗

PubMed2002

Factors affecting the likelihood of successful induction after intravaginal misoprostol application for cervical ripening and labor induction.

OBJECTIVE: Our purpose was to determine whether maternal age, height and weight, parity, duration of pregnancy, cervical dilatation or Bishop score, and birth weight could be used to predict the likelihood of successful induction in women given intravaginal misoprostol. STUDY DESIGN: A computerized database was compiled of 1373 pregnancies in which intravaginal misoprostol was given for cervical ripening and labor induction. Most of these women were placed on investigational protocols in which the dose of misoprostol administered was 25 to 50 microg and the dosing intervals ranged from 3 to 6 hours. No more than 24 hours of administration was permitted. Induction was undertaken in women with unfavorable cervical examinations (Bishop scores of 4 or less) and without spontaneous labor or ruptured membranes. Univariate and stepwise multiple regression analyses were performed to identify those factors associated with successful induction, defined as vaginal delivery within 24 hours of induction. RESULTS: Six hundred fifty-seven (48%) had successful induction. Parity (odds ratio [OR] 2.5, 95% CI 2.0-2.9, P <.0001), initial cervical dilatation (OR 1.9, 95% CI 1.6-2.3, P <.0001), Bishop score (OR 1.6, 95% CI 1.3, 1.8, P <.0001), and gestational age at entry (OR 1.3, 95% CI 1.1-1.5, P =.002) were significant at the.05 level for predicting successful induction. A multivariate stepwise logistic regression was then performed to evaluate each of these as independent predictors. Parity (OR 2.4, 95% CI 2.0-3.0, P <.0001), initial cervical dilatation (OR 1.7, 95% CI 1.4-2.1, P <.0001), and estimated gestational age (OR 1.3, 95% CI 1.1-1.6, P =.003) are significant independent predictors for successful induction, but initial Bishop score is not significant (P =.19) after adjustment for other significant predicting factors. CONCLUSIONS: The clinical characteristics of parity, initial cervical dilatation, and gestational age at entry are predictors of the likelihood of success of cervical ripening and labor induction with intravaginal misoprostol administration.

Administration, Intravaginal↗

PubMed2004

GERBIL: Genotype resolution and block identification using likelihood.

The abundance of genotype data generated by individual and international efforts carries the promise of revolutionizing disease studies and the association of phenotypes with individual polymorphisms. A key challenge is providing an accurate resolution (phasing) of the genotypes into haplotypes. We present here results on a method for genotype phasing in the presence of recombination. Our analysis is based on a stochastic model for recombination-poor regions ("blocks"), in which haplotypes are generated from a small number of core haplotypes, allowing for mutations, rare recombinations, and errors. We formulate genotype resolution and block partitioning as a maximum-likelihood problem and solve it by an expectation-maximization algorithm. The algorithm was implemented in a software package called GERBIL (genotype resolution and block identification using likelihood), which is efficient and simple to use. We tested GERBIL on four large-scale sets of genotypes. It outperformed two state-of-the-art phasing algorithms. The phase algorithm was slightly more accurate than GERBIL when allowed to run with default parameters, but required two orders of magnitude more time. When using comparable running times, GERBIL was consistently more accurate. For data sets with hundreds of genotypes, the time required by phase becomes prohibitive. We conclude that GERBIL has a clear advantage for studies that include many hundreds of genotypes and, in particular, for large-scale disease studies.

Chromosome Mapping↗

PubMed2006

A likelihood approach to analysis of network data.

Biological, sociological, and technological network data are often analyzed by using simple summary statistics, such as the observed degree distribution, and nonparametric bootstrap procedures to provide an adequate null distribution for testing hypotheses about the network. In this article we present a full-likelihood approach that allows us to estimate parameters for general models of network growth that can be expressed in terms of recursion relations. To handle larger networks we have developed an importance sampling scheme that allows us to approximate the likelihood and draw inference about the network and how it has been generated, estimate the parameters in the model, and perform parametric bootstrap analysis of network data. We illustrate the power of this approach by estimating growth parameters for the Caenorhabditis elegans protein interaction network.

Animals↗

PubMed2001

Maximum likelihood estimation of a migration matrix and effective population sizes in n subpopulations by using a coalescent approach.

A maximum likelihood estimator based on the coalescent for unequal migration rates and different subpopulation sizes is developed. The method uses a Markov chain Monte Carlo approach to investigate possible genealogies with branch lengths and with migration events. Properties of the new method are shown by using simulated data from a four-population n-island model and a source-sink population model. Our estimation method as coded in migrate is tested against genetree; both programs deliver a very similar likelihood surface. The algorithm converges to the estimates fairly quickly, even when the Markov chain is started from unfavorable parameters. The method was used to estimate gene flow in the Nile valley by using mtDNA data from three human populations.

Genetics, Population↗

PubMed2001

A likelihood ratio test for evolutionary rate shifts and functional divergence among proteins.

Changes in protein function can lead to changes in the selection acting on specific residues. This can often be detected as evolutionary rate changes at the sites in question. A maximum-likelihood method for detecting evolutionary rate shifts at specific protein positions is presented. The method determines significance values of the rate differences to give a sound statistical foundation for the conclusions drawn from the analyses. A statistical test for detecting slowly evolving sites is also described. The methods are applied to a set of Myc proteins for the identification of both conserved sites and those with changing evolutionary rates. Those positions with conserved and changing rates are related to the structures and functions of their proteins. The results are compared with an earlier Bayesian method, thereby highlighting the advantages of the new likelihood ratio tests.

Amino Acid Sequence↗

PubMed1995

A maximum likelihood algorithm for genome mapping of cytogenetic loci from meiotic configuration data.

Frequencies of meiotic configurations in cytogenetic stocks are dependent on chiasma frequencies in segments defined by centromeres, breakpoints, and telomeres. The expectation maximization algorithm is proposed as a general method to perform maximum likelihood estimations of the chiasma frequencies in the intervals between such locations. The estimates can be translated via mapping functions into genetic maps of cytogenetic landmarks. One set of observational data was analyzed to exemplify application of these methods, results of which were largely concordant with other comparable data. The method was also tested by Monte Carlo simulation of frequencies of meiotic configurations from a monotelodisomic translocation heterozygote, assuming six different sample sizes. The estimate averages were always close to the values given initially to the parameters. The maximum likelihood estimation procedures can be extended readily to other kinds of cytogenetic stocks and allow the pooling of diverse cytogenetic data to collectively estimate lengths of segments, arms, and chromosomes.

Algorithms↗

PubMed2006

Profile likelihood-based confidence intervals using Monte Carlo integration for population pharmacokinetic parameters.

Population pharmacokinetic (PPK) analysis usually employs nonlinear mixed effects models using first-order linearization methods. It is well known that linearization methods do not always perform well in actual situations. To avoid linearization, the Monte Carlo integration method has been proposed. Moreover, we generally utilize asymptotic confidence intervals for PPK parameters based on Fisher information. It is known that likelihood-based confidence intervals are more accurate than those from the usual asymptotic confidence intervals. We propose profile likelihood-based confidence intervals using Monte Carlo integration. We have evaluated the performance of the proposed method through a simulation study, and analyzed the erythropoietin concentration data set by the method.

Computer Simulation↗

PubMed1993

The likelihood ratio for comparing means when a portion of the subjects fail to respond.

Results of clinical studies are often obscured by the fact that some of the subjects improve with treatment while others do not. As a consequence, for example, we may obtain a contaminated distribution in a treatment group, having one component similar to the entire distribution for a control group and the other shifted by the treatment effect. Maximum-likelihood estimation and the likelihood ratio test for investigating the proportion of responders together with the treatment effect are based on asymptotic theory and use iterative maximization techniques. We investigate the sampling distribution of the estimates and the test and demonstrate their use in statistical inference. Our results suggest that the chi-square distribution with 1.4 degrees of freedom provides a useful test criterion even when the sample sizes are as small as 10. Only in obvious testing situations is the t-test adequate.

Clinical Trials as Topic↗

PubMed2000

Likelihood-based tests of topologies in phylogenetics.

Likelihood-based statistical tests of competing evolutionary hypotheses (tree topologies) have been available for approximately a decade. By far the most commonly used is the Kishino-Hasegawa test. However, the assumptions that have to be made to ensure the validity of the Kishino-Hasegawa test place important restrictions on its applicability. In particular, it is only valid when the topologies being compared are specified a priori. Unfortunately, this means that the Kishino-Hasegawa test may be severely biased in many cases in which it is now commonly used: for example, in any case in which one of the competing topologies has been selected for testing because it is the maximum likelihood topology for the data set at hand. We review the theory of the Kishino-Hasegawa test and contend that for the majority of popular applications this test should not be used. Previously published results from invalid applications of the Kishino-Hasegawa test should be treated extremely cautiously, and future applications should use appropriate alternative tests instead. We review such alternative tests, both nonparametric and parametric, and give two examples which illustrate the importance of our contentions.

Classification↗

PubMed2004

Molecular clock fork phylogenies: closed form analytic maximum likelihood solutions.

Maximum likelihood (ML) is increasingly used as an optimality criterion for selecting evolutionary trees, but finding the global optimum is a hard computational task. Because no general analytic solution is known, numeric techniques such as hill climbing or expectation maximization (EM) are used in order to find optimal parameters for a given tree. So far, analytic solutions were derived only for the simplest model-three-taxa, two-state characters, under a molecular clock. Quoting Ziheng Yang, who initiated the analytic approach,"this seems to be the simplest case, but has many of the conceptual and statistical complexities involved in phylogenetic estimation."In this work, we give general analytic solutions for a family of trees with four-taxa, two-state characters, under a molecular clock. The change from three to four taxa incurs a major increase in the complexity of the underlying algebraic system, and requires novel techniques and approaches. We start by presenting the general maximum likelihood problem on phylogenetic trees as a constrained optimization problem, and the resulting system of polynomial equations. In full generality, it is infeasible to solve this system, therefore specialized tools for the molecular clock case are developed. Four-taxa rooted trees have two topologies-the fork (two subtrees with two leaves each) and the comb (one subtree with three leaves, the other with a single leaf). We combine the ultrametric properties of molecular clock fork trees with the Hadamard conjugation to derive a number of topology dependent identities. Employing these identities, we substantially simplify the system of polynomial equations for the fork. We finally employ symbolic algebra software to obtain closed formanalytic solutions (expressed parametrically in the input data). In general, four-taxa trees can have multiple ML points. In contrast, we can now prove that each fork topology has a unique(local and global) ML point.

Animals↗