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PubMed1996

Low birth weight reduces the likelihood of breast-feeding among Filipino infants.

We studied the relationship of low birth weight (LBW) to concordance of mother's feeding intentions during pregnancy with actual feeding practices; initiation of breast-feeding; and patterns of feeding in the first 6 mo. Data came from the Cebu Longitudinal Health and Nutrition Survey, which followed 3080 mother-infant pairs from urban and rural communities of Metro Cebu, Philippines. We used logistic regression to estimate the effects of LBW on feeding practices, controlling for place of delivery (home, public or private health facility), receipt of free infant formula samples; infant sex, urban residence; primiparity, education level and age of the mother; and family income and assets. Birth of a LBW infant significantly decreased the likelihood that women would initiate breast-feeding. Of particular note is the finding of this decreased likelihood among women who during pregnancy had stated an intention to breast-feed. In a comparison of 6-mo feeding patterns, we also found that LBW increased the likelihood of not breast-feeding or of weaning before 6 mo. Among breast-feeding mothers, LBW increased the likelihood of full breast-feeding for 6 mo compared with patterns characterized by earlier supplementation with other foods and liquids. The negative relationship of LBW to breast-feeding was strongest when births took place in private or public health facilities. Given the known health risks of LBW and the proven benefits of breast-feeding, these results emphasize the need for special efforts to promote breast-feeding of LBW infants born in clinical settings.

Adult↗

PubMed1978

A multivariate analysis of the likelihood and volume of preventive visit demand in a prepaid group practice.

An economic framework for the investigation of the demand for preventive medical care services is suggested and empirical models for the likelihood and volume of preventive physician visits are specified. These are tested using data on 3,892 individuals enrolled in the Kaiser Foundation Prepaid Health Plan of Portland, Oregon. Preventive visits, delineated by the Kaiser Clinical Behavioral Classification System, included general medical examinations, eye examinations, well-child care and immunization services. Multiple regression is used to estimate the likelihood of preventive visits for all persons and the volume of preventive visits for users. Income and coinsurance were the most significant economic variables in the likelihood equation, possessing the expected positive and negative signs, respectively. The usual findings of a positive education effect and negative family size effect were supported by the results. The economic variables were less significant in the volume equations than in the likelihood equations, suggesting that system and physician effects may neutralize these factors. Females were more likely to make a preventive visit than were males and the relatively young and old were the heaviest age-group users of preventive care. Perceived helath status did not appear to significantly affect preventive care demand.

Adult↗

PubMed1994

Monte Carlo likelihood in the genetic mapping of complex traits.

Many of the likelihoods arising in the analysis of complex genetic traits, particularly in linkage analysis, are computationally infeasible. Where exact likelihoods cannot be computed, Monte Carlo estimates of likelihoods may provide a satisfactory alternative. Although simulation on pedigrees is straightforward, simulation conditional upon observed phenotypic data is not. However, recent advances in Markov chain Monte Carlo methods have provided a method well suited to this problem. From realizations of underlying genes, simulated under a genetic model, conditional upon observed data, a Monte Carlo estimate of this likelihood surface can be formed. Various sampler and model modifications are needed to enhance the statistical efficiency of the Monte Carlo estimator; as these methods become increasingly developed, this approach becomes a useful tool in resolving the genes contributing to the phenotypes associated with genetically complex diseases.

Algorithms↗

PubMed2002

Likelihood-based refinement. I. Irremovable model errors.

In conventional structure refinement, the discrepancy between the calculated magnitudes and those observed in X-ray experiments is attributed to errors inherent in preliminary assigned values of the model parameters. However, the chosen set of model parameters may not be adequate to describe the structure factors precisely. For example, if some atoms are not included in the current model, then the structure factors calculated from such a partial model contain 'irremovable errors'. These errors cannot be eliminated by any choice of the parameters of the partial structure. Probabilistic modelling suggests a way to take irremovable errors into account. Every trial set of values of the model parameters is now associated with the joint probability distribution of the calculated magnitudes, rather than with a particular set of magnitudes. The new goal of the refinement is formulated as the search for the distribution that is the most consistent with the observed data. The statistical likelihood is a possible measure of the consistency. The suggested quadratic approximation of the likelihood function allows the likelihood-based refinement to be considered as a kind of least-squares refinement that uses appropriate weights and modified targets for the calculated magnitudes. This in turn enables the analysis of tendencies of the likelihood-based refinement in comparison with the classical least-squares refinement.

Journal Article↗

PubMed2006

The validity of self-reported likelihood of HIV infection among the general population in rural Malawi.

BACKGROUND: Understanding HIV risk perception is important for designing appropriate strategies for HIV/AIDS prevention, because these interventions often rely on behaviour modification. A key component of HIV risk perception is the individual's own assessment of HIV status, and the extent to which this assessment is correct. However, this issue has received limited attention. OBJECTIVES: To examine the validity of self-reported likelihood of current HIV infection among the general population in rural Malawi. METHODS: As part of a panel household survey, data on behaviour and biomarkers were collected for a population-based sample of approximately 3000 respondents in rural Malawi aged > or = 15 years. Information on self-assessed likelihood of currently having HIV was collected by survey interview. Saliva was obtained from all consenting respondents to assess actual HIV status. RESULTS: Of 2299 survey respondents who assessed their likelihood of being infected with HIV at the time of the survey, 71% were accurate. Most incorrect assessments (88%) were due to respondents overestimating (rather than underestimating) their likelihood of being infected with HIV. Women were less likely than men to correctly assess their HIV status. The two most important predictors of false-positive responses were marital status and self-reported health. CONCLUSIONS: Self-reports of HIV infection were generally valid. Most invalid self-reports were due to overestimating the risk of having HIV. The implications of this finding are highlighted, as they pertain to the design of HIV prevention interventions and the expansion of HIV counselling, testing and treatment programmes in developing countries.

Adolescent↗

PubMed1989

Likelihood estimation of quantitative genetic parameters when selection occurs: models and problems.

Conceptual aspects of estimation of genetic components of variance and covariance under selection are discussed, with special attention to likelihood methods. Certain selection processes are described and alternative likelihoods that can be used for analysis are specified. There is a mathematical relationship between the likelihoods that permits comparing the relative amount of information contained in them. Theoretical arguments and evidence indicate that point inferences made from likelihood functions are not affected by some forms of selection.

Animals↗

PubMed2003

Likelihood of change: a study assessing surgeon use of multisource feedback data.

BACKGROUND: Multisource feedback, using questionnaire-based data from patients, coworkers, and medical colleagues, is designed to provide broad-based information about clinical performance to facilitate change. PURPOSE: To determine and explain the likelihood that surgeons would implement change following receipt of performance data. METHODS: Surgeons were surveyed to determine the likelihood they would make changes based on specific feedback about their clinical practices. RESULTS: One hundred fifty-three surgeons (76.5%) responded to the follow-up survey. There was little correlation between performance ratings provided by self or medical colleagues and the likelihood of change. A linear regression analysis indicated that 19.2% of the variance in likelihood to change could be explained by age, time spent reviewing feedback, the gap between self- and other ratings, and surgical specialty. CONCLUSION: Surgeons made few changes in practice in response to feedback data. Attention needs to be paid to methods that might increase surgeon use of performance data

Alberta↗

PubMed2004

Cerebral infarctions and the likelihood of dementia from Alzheimer disease pathology.

BACKGROUND: Alzheimer disease (AD) is the most common cause of dementia. The effect of cerebral infarctions on the likelihood of dementia from AD pathology is not well understood. METHODS: The study included 153 deceased Catholic clergy who participated in the Religious Orders Study. Annual evaluations, including 19 tests of cognitive function, were performed to determine a diagnosis of dementia and level of cognitive abilities proximate to death. At autopsy, neuritic and diffuse plaques and neurofibrillary tangles were counted and combined into a standardized summary measure of AD pathology. Number, volume, side, and distribution of old macroscopic infarctions were recorded. Analyses included logistic and linear regression, adjusting for age, sex, and education. RESULTS: The AD pathology score ranged from 0 to 2.93 units, and 54 persons had infarctions. There was no relationship between AD pathology and infarctions (r = 0.04, p = 0.56). Each unit of AD pathology increased the odds of dementia by 4.40-fold (95% CI = 2.33 to 8.32), and this was essentially unchanged after accounting for infarctions. The presence of one or more infarctions independently increased the odds of dementia by 2.80-fold (95% CI = 1.26 to 6.21). There was no interaction between AD pathology and infarctions to further increase the likelihood of dementia (p = 0.39). The number, size, and distribution of infarctions added to the odds of dementia but also did not show an interaction with AD pathology. Similar results were found in analyses with global cognitive function and five different cognitive systems. CONCLUSION: Cerebral infarctions independently contribute to the likelihood of dementia but do not interact with AD pathology to increase the likelihood of dementia beyond their additive effect.

Aged↗

PubMed2003

Likelihood approaches to sensory coding in auditory cortex.

Likelihood methods began their evolution in the early 1920s with R A Fisher, and have developed into a rich framework for inferential statistics. This framework offers tools for the analysis of the differential geometry of the full likelihood function based on observed data. We examine likelihood functions derived from inverse Gaussian (IG) probability density models of cortical ensemble responses of single units. Specifically, we investigate the problem of sound localization from the observation of an ensemble of neural responses recorded from the primary (Al) field of the auditory cortex. The problem is framed as a probabilistic inverse problem with multiple sources of ambiguity. Observed and expected Fisher information are defined for the IG cortical ensemble likelihood functions. Receptive field functions of multiple acoustic parameters are constructed and linked to the IG density. The impact of estimating multiple acoustic parameters related to the direction of a sound is discussed, and the implications of eliminating nuisance parameters are considered. We examine the degree of acuity afforded by a small ensemble of cortical neurons for locating sounds in space, and show the predicted patterns of estimation errors, which tend to follow psychophysical performance.

Acoustic Stimulation↗

PubMedDate not supplied

How useful are physical examination procedures? Understanding and applying likelihood ratios.

OBJECTIVE: To describe the calculation and interpretation of likelihood ratios for examination procedures performed by certified athletic trainers. BACKGROUND: Physical examination procedures or "special tests" are commonly taught to athletic training students and performed by certified athletic trainers. Likelihood ratios offer an approach to assessing test performance that incorporates estimates of sensitivity and specificity into a clinically useful value. We describe the calculation of likelihood ratios and the application of likelihood ratios to clinical decision making. RECOMMENDATIONS: The performance characteristics of physical examination procedures taught and practiced in athletic training should be considered in the planning of course materials as well as test interpretation after a physical examination. Research is needed to better understand how well physical examination procedures, when performed by certified athletic trainers, identify those athletes with and without specific musculoskeletal injuries.

Journal Article↗

PubMed1987

A likelihood analysis of experiments to test altitude decompression protocols for shuttle operations.

The principle of maximum likelihood and the method of linear regression both are used to fit mathematical models to experimental data, but likelihood can be applied to binary data such as the outcome of a decompression, whereas linear regression cannot. Maximum likelihood was applied to 548 individual altitude exposures from 30 experimental pressure profiles tested by NASA and the Air Force. Twelve decompression models were studied including modified Haldane models and models which assume that stationary bubbles cause Type I decompression sickness. The data was best represented by a model in which a bubble in tissue is surrounded by a diffusion barrier, but this representation was statistically indistinguishable from a single tissue Haldane model with a halftime of 508 min. By providing a quantitative measure of the agreement between theory and data, the principle of maximum likelihood offers an opportunity for improving the understanding of decompression mechanisms and for developing safer and faster decompression procedures.

Altitude↗

PubMed1983

Estimating morbidity risks with variable age of onset: review of methods and a maximum likelihood approach.

Various methods for the estimation of morbidity risk in a disease with late variable onset are described, along with a maximum likelihood approach. It is shown that the Strömgren estimator is nearly as efficient as the maximum likelihood estimator when the true risk is low, but may be significantly less efficient for high morbidity risks. The maximum likelihood estimator offers greater protection against risk estimates greater than or equal to 1, and for small samples, may also be less biased than the Strömgren estimator, especially when risk is high. For reasonable sample sizes both estimates are nearly unbiased. The modified Strömgren estimator is too biased, in general, to be practical. Methods for comparing morbidity risks are also described. If an age-of-onset distribution is estimated from the same sample as morbidity risk, a single maximum likelihood procedure is advocated. The methods are applied to a data set on major affective disorder. The sensitivity of morbidity-risk estimates and tests of hypotheses to the form of onset function assumed is examined.

Age Factors↗

PubMed1996

Computer program to predict likelihood of finding and HLA-matched donor: methodology, validation, and application.

Approximately 65% of the patients requiring bone marrow transplantation do not have an HLA-A, -B, -DR identical sibling and therefore need to find a phenotypically matched unrelated donor. As of June 30, 1996, the National Marrow Donor Program maintains a registry of 2.31 million volunteer donors, 35% of whom are fully typed for HLA-A, -B, -DR loci. Because a majority of the donors has not been DR typed, a patient who does not find a complete match at the time of the preliminary search may elect to prospectively DR type A, B matched and A, B one-antigen mismatched donors. An efficient strategy is therefore needed for determining the likelihood that an appropriate donor exists and for deciding which of the donors that have not yet been DR typed should be tested for DR matching with the candidate. We developed a mathematical algorithm and computer program to facilitate the search for a suitable donor by donor race and phenotype. The program provides information on the likelihood of 1) finding at least one HLA-A, -B, -DR phenotypically matched donor, 2) the likelihood of finding at least one DR match among m A, B matched donors who have not yet been DR typed, and 3) the likelihood of an A, B one antigen mismatched donor of a specific phenotype being a DR match with the patient. The mathematical models underlying the program are based on basic population genetics theory and utilize HLA-A, -B, DR haplotype frequencies derived from the NMDP registry. The results of the validation study show that the prediction is highly accurate at the level of broad antigens. The algorithm and program have the potential to assist patients and physicians in optimizing their decisions regarding clinical management and resource allocation on the process of searching for a suitable unrelated bone marrow donor.

Blood Donors↗

PubMed1996

Analysis of mortality rates via marginal extended quasi-likelihood.

We use a mixed Poisson regression model with extra variation to analyse mortality data cross-classified by age and geographic region. We use estimates of dispersion parameter and fixed effects parameters, obtained by maximizing a marginal quasi-likelihood function, to estimate mortality rates in an empirical Bayes manner. This is a modification of an earlier method by Tsutakawa that used the likelihood function and is computationally impractical for routine use. In order to apply the extended quasi-likelihood function, a linear variance function (of the mean) is used in place of a quadratic one used previously. We illustrate the method with male lung cancer deaths in the state of Missouri.

Age Distribution↗

PubMed1997

Second-stage least squares versus penalized quasi-likelihood for fitting hierarchical models in epidemiologic analyses.

Hierarchical regression analysis holds much promise for epidemiologic analysis, but has as yet seen limited application because of lack of easily used software and the relatively lengthy run times of preferred fitting methods (such as true maximum likelihood and Bayesian approaches). This paper compares three relatively simple choices for estimation of the regression coefficients: maximum-likelihood first stage combined with a weighted-least-squares second stage (MLLS); joint iteratively reweighted least squares fitting of first and second stage (JILS); and empirically penalized quasi-likelihood (EPQL). These choices can be combined with various methods for estimating the second-stage variance; the two contrasted here are based on first and second-stage residuals. JILS and EPQL yielded indistinguishable results, and had small sample performance superior to MLLS. In larger samples there was little practical difference among the methods. Use of first-stage residuals to estimate the prior variance required considerably more computation than use of second-stage residuals, but produced no discernible improvement in regression coefficient estimates. All three methods performed well for estimation of first-stage parameters but were less satisfactory for estimation of second-stage parameters.

Bayes Theorem↗

PubMed1999

Maximum-Likelihood-Binomial method for genetic model-free linkage analysis of quantitative traits in sibships.

Sib-pair linkage studies are widely used to investigate the genetic factors implicated in complex quantitative traits. To analyze these data, we propose a Maximum-Likelihood-Binomial (MLB) approach, which considers the sibship as a whole and relies on the idea of binomial distributions of parental alleles among offsprings. The method is based on the introduction of a latent binary variable capturing the linkage information between the observed quantitative trait and the marker, and the final likelihood can be expressed assuming a parametric distribution for the studied trait but also without any assumption on this distribution. The test for linkage is a simple likelihood ratio test involving a single parameter. The performances of the MLB method are assessed by a simulation study in different kinds of family samples. In the case of families with various sibship sizes, both MLB approaches (assuming or not a parametric distribution for the quantitative trait) provide very consistent results in terms of type I errors and yield power levels generally higher than those of the classical Haseman-Elston method. In the case of extremely discordant sib pairs, we analytically show that, for a common asymptotic type I error, the distribution-free MLB statistic is expected to be more powerful than the test proposed by Risch and Zhang [(1995) Science 268:1584-1589]. In samples including both extremely concordant and discordant sib-pairs, simulation studies show that the MLB approach is at least as powerful as the EDAC method [Gu et al. (1996) Genet Epidemiol 13:513-533]. This MLB method, which can be easily extended to perform multipoint analysis and to account for genetic heterogeneity, appears to be quite an interesting alternative for mapping quantitative trait loci in humans.

Alleles↗

PubMedDate not supplied

Parametric bootstrap and penalized quasi-likelihood inference in conditional autoregressive models.

This paper discusses a variety of conditional autoregressive (CAR) models for mapping disease rates, beyond the usual first-order intrinsic CAR model. We illustrate the utility and scope of such models for handling different types of data structures. To encourage their routine use for map production at statistical and health agencies, a simple algorithm for fitting such models is presented. This is derived from penalized quasi-likelihood (PQL) inference which uses an analogue of best-linear unbiased estimation for the regional risk ratios and restricted maximum likelihood for the variance components. We offer the practitioner here the use of the parametric bootstrap for inference. It is more reliable than standard maximum likelihood asymptotics for inference purposes since relevant hypotheses for the mapping of rates lie on the boundary of the parameter space. We illustrate the parametric bootstrap test of the practically relevant and important simplifying hypothesis that there is no spatial autocorrelation. Although the parametric bootstrap requires computational effort, it is straightforward to implement and offers a wealth of information relating to the estimators and their properties. The proposed methodology is illustrated by analysing infant mortality in the province of British Columbia in Canada.

Algorithms↗

PubMed2001

Maximum likelihood inference for left-censored HIV RNA data.

Left-censored data are characteristic of many bioassays due to inherent limit of detection and limit of quantitation (LOQ) in the assays. This paper examines how the left-censoring of plasma HIV RNA measurements, collected for the Hemophilia Growth and Development Study, affects the quantification of viral load and the assessment of its association with a continuous or dichotomous outcome. Data analyses using maximum likelihood estimation are compared to analyses where the LOQ or LOQ/2 value is substituted for the left-censored observations, and also to other methods like multiple imputation. A Gaussian distribution is assumed for the log-transformed plasma HIV RNA data, and simulations are used to explore the sensitivity of the results to changes in the model parameters. The robustness of the estimators is also investigated when the data are generated from a mixture of two Gaussian distributions. Maximum likelihood is in general the least biased method. However, multiple imputation assuming a censored Gaussian imputation model and substituting the censored values with the expectation of its conditional predictive distribution are also competitive to maximum likelihood, and may be appealing because of their simpler computational algorithms.

Adolescent↗