bluuebunny/crossref_metadata_2025_split huggingface dataset:
A sequential phase II/III trial for binary outcomes
Authors: Storer Barry E. 
Published: April 2007

AbstractThis paper describes a simple two‐stage design for randomized clinical trials with a binary outcome. An early stopping criterion applies to results in the experimental arm only and seeks to evaluate that arm with respect to some external standard of efficacy. Stopping rules are similar to those commonly used in phase II designs. This design has no adverse impact on the overall type I error rate, though one must increase sample size to accommodate a modest loss in power.
The choice of a balanced allocation method for a clinical trial in otitis media with effusion
Authors: Zielhuis G. A. , Straatman H. , Van 'T Hof‐Grootenboer A. E. , Van Lier H. J. J. , Rach G. H. , Van Den Broek P. 
Published: April 2007

AbstractWe review the choice of treatment allocation procedures in a specific small clinical trial of the effect of tympanostomy tubes on language development in patients with otitis media with effusion. The options for balanced allocation available at the planning stage are discussed. A clearly favourable method could not be identified. A simulation study was performed, and its results demonstrated least imbalance with the variance method. In practice this method produced considerable imbalance on relevant prognostic factors.
Bias in the one‐step method for pooling study results
Authors: Greenland Sander , Salvan Alberto 
Published: April 2007

AbstractThe one‐step (Peto) method for obtaining pooled effect estimates can yield extremely biased results when applied to unbalanced data. Even for balanced studies, the one‐step estimate may incorporate an unacceptable degree of bias. In place of the one‐step estimate, we recommend use of ordinary Mantel‐Haenszel, weighted least squares, or maximum likelihood estimates whenever the total number of events is adequate for such methods. If the total number of events is small, we recommend exact methods.
Predicting response to treatment: Differentiating active‐factor and non‐specific effects
Authors: Young Michael A. , Fogg Louis F. 
Published: April 2007

AbstractAn important step in providing treatment is prediction of which treatments will be effective for which patients. Common methods for prediction of efficacy, however, are inconsistent with the assumptions of the standard placebo‐control paradigm for establishment of efficacy. This is because in prediction of the observed response, one ignores the distinction between response attributable to non‐specific factors and that attributable to active‐treatment factors. This paper presents a paradigm for the use of log‐linear analysis that allows for the development of predictive methods that take into account this distinction. An example with simulated data demonstrates how, if this distinction is ignored, one can reach misleading conclusions and make non‐optimal treatment decisions as a result of an inaccurate cost ‐ benefit analysis of the treatment.
Optimal choice of prognostic variables with an application to cardiac monitoring using M‐mode echocardiography
Authors: Puterman Martin L. , Schumacher Peter , Sandor George G. S. 
Published: April 2007

AbstractThis paper provides a methodology for the optimal choice of a subset from a large number of interrelated diagnostic variables. We use predetermined abnormal ranges for each measurement and code subjects as abnormal or normal on this basis. We present a procedure to determine the smallest subset of measurements that identifies any subject abnormal on at least one measurement. We formulate and solve the problem using integer programming. We then apply this methodology to study the use of M‐mode echocardiography to determine potentially cardiotoxic side effects of chemotherapy and compare its performance to several multivariate methods. Extensions and modifications are discussed.
The proportionate mortality ratio and its relationship with measures of mortality
Authors: Hansen Eva Stottrup 
Published: April 2007

AbstractUnder certain circumstances a proportionate mortality ratio (PMR) equals the cause‐specific standardized mortality ratio (SMR) divided by the overall SMR. In this paper, the relationship between PMR and SMR is derived stepwise with focus on the conditions that must be fulfilled for each step of the derivation to be valid. It appears essential that the following conditions be fulfilled: (1) the compared populations are closed throughout the period of study; (2) all deaths (or a representative sample) in the compared populations are included in the analysis; (3) every dead person is assigned to exactly the same exposure category that he or she would have been assigned to in a follow‐up study; and (4) possible diagnostic misclassification is not exposure‐dependent. Furthermore, for dead people within the comparison group, the relative frequency of the cause of death of interest must be constant over age. In view of this it is recommended that PMR studies of occupational mortality are designed to cover only a short period; to use data from national or regional death certificate registries only; to be restricted to lifetime occupations; to make use of a hand‐picked comparison group that has had the same access to medical care and diagnosis as the index group; and to restrict the PMR analysis to age‐at‐death strata in which the relative frequency of the studied cause of death is constant in the comparison group of deceased persons.
An application of the LFP survival model to smoking cessation data
Authors: Koehler Kenneth J. , McGovern Paul G. 
Published: April 2007

AbstractWe use a limited failure population (LFP) model based on the Weibull distribution to model the times from initial abstinence to return to smoking for subjects enrolled in programmes to help them stop smoking. The model contains a third parameter that corresponds to the proportion of subjects who permanently abstain from smoking. The data are subject to both right and interval censoring. Furthermore, subjects receive treatment in groups, and individuals in the same group may provide correlated outcomes. Use of a maximum likelihood estimation procedure which assumes independent outcomes provides reasonable parameter estimates, but the corresponding standard errors tend to be too small, which results in tests with inflated type I error levels and confidence intervals that tend to be too narrow. We use a bootstrap procedure to obtain more reasonable values for the standard errors and to construct confidence intervals that more nearly achieve the stated coverage probabilities.
Estimation of risk ratios in case‐base studies with competing risks
Authors: Flanders W. Dana , Dersimonian Rebecca , Rhodes Philip 
Published: April 2007

AbstractThe case‐base study is a recently developed modification of the case‐control design that leads to risk ratio estimates. Currently available methods for the analysis of case‐base studies lead to estimates of the unconditional risk ratio which may be misleading if censoring occurs. In this manuscript, we describe an approach for the analysis of case‐base studies that yields conditional risk ratio estimates which remain valid in the presence of censoring. The approach we propose for estimating risk ratios and their standard errors involves a non‐iterative procedure.
Murphy's law of limiting dilution cloning
Authors: Staszewski Robert 
Published: April 2007

AbstractConventional practice and literature on limiting dilution cloning address the irrelevant problem of selection of a single progenitor from a uniform population, and provide optimistic estimates of monoclonality for interesting cultures and subcultures. Any cell line established via these estimates is suspect and may be polyclonally metastable. Cultures derived by limiting dilution of the progenitors of independently Poisson distributed populations obey a counterintuitive relation with the characteristics of a Murphy's law: the probability that an interesting culture is monotypic or monoclonal is less than that of a random non‐sterile culture, decreases for increasingly rare interesting cultures, and is bounded below by the probability of sterility. A priori and empiric a posteriori estimates of the probability that interesting subcultures are monotypic or monoclonal are derived consistent with this principle.
Biplots in biomedical research
Authors: Gabriel K. Ruben , Odoroff Charles L. 
Published: April 2007

AbstractThe biplot is a graphical display of multivariate data. A number of examples from biomedical research illustrate its use. Biplots allow for inspection of data preliminary to formal analysis, and can follow an analysis by the graphical inspection of residuals. The simplicity and intuitive appeal of these displays is stressed. An appendix indicates their method of construction and the software for producing them.
Must clinical trials be large? The interpretation of p‐values and the combination of test results
Authors: Barnard G. A. 
Published: April 2007

AbstractThe notion that small, well planned clinical trials may not be worth undertaking is shown to arise from an overemphasis on just one way of interpreting P‐values. Alternative forms of P and other interpretations are put forward. Attention is drawn to some aspects of the theory of hypothesis testing which seem less well known than they should be.
Some historical and methodological developments in early clinical trials at the national institutes of health
Authors: Greenhouse Samuel W. 
Published: April 2007

AbstractThis paper reviews five randomized clinical trials with unusual design or analysis features from institutes other than the National Cancer Institute or the National Heart, Lung and Blood Institute. These are: a Cooperative Study of Retrolental Fibroplasia sponsored by the National Institute of Neurological Diseases and Blindness; the Diabetic Retinopathy Study sponsored by the National Eye Institute; the University Group Diabetes Program sponsored by the National Institute of Arthritis and Metabolic Diseases; a Clinical Trial of the Extracranial to Intracranial Arterial Anastomosis (EC/IC bypass) by the National Institute of Neurological and Communicative Disorders and Stroke; and the Clinical Trial of Hereditary Angioedema by the National Institute of Allergy and Infectious Diseases.
Estimating correlation between alternative measures of disease progression in a longitudinal study
Authors: Schluchter Mark D. 
Published: April 2007

AbstractA primary outcome variable in longitudinal studies is often the rate of change of a continuous measurement over time. Examples include the one‐second forced expiratory volume (FEV1) in pulmonary studies or glomerular filtration rate (GFR) in renal studies. An individual patient's least‐squares estimate of slope obtained from a linear regression is an imprecise measure of the true slope for that patient, and correlations involving the estimated slopes will be biased due to this measurement error. This paper presents methods for estimating the true correlation between these imprecise slope estimates, or between slope estimates and other variables measured with error. In addition to providing a simple consistent estimator of the correlation, we show how the maximum likelihood estimate of the correlation coefficient and a 100(1 — α) per cent confidence interval can be obtained. An example estimating the correlation between GFR and inverse serum creatinine slopes in patients with chronic renal disease is given.
Prognostic scores for detecting a high risk group: Estimating the sensitivity when applied to new data
Authors: Phillips Andrew N. , Thompson Simon G. , Pocock Stuart J. 
Published: April 2007

AbstractThe sensitivity of a prognostic scoring system will tend to be exaggerated if the scoring system is both derived and validated on the same data. This paper provides, by analogy to regression with error in an explanatory variable, an intuitive basis for the methodological results of Copas which seek to estimate the degree of such exaggeration. There was good agreement between Copas' results and those achieved in a series of cross‐validation exercises where logistic regression models predicting the risk of ischaemic heart disease were derived using data from the prospective British Regional Heart Study. When truly important variables were included, the exaggeration of the sensitivity increased as the number of cases of disease available decreased. It is concluded that Copas' method, which is easy to implement in practice, may be helpful in realistically anticipating the extent of such exaggeration, and that it can be usefully employed before pursuing a scoring system on newly collected data.
Variation in heart disease mortality across census tracts as a function of overdispersion and social class mixture
Authors: Jarjoura David , Logue Everett 
Published: April 2007

AbstractVariation in heart disease (HD) mortality rates across census tracts is greater than expected given binomial error and available explanatory variables. We extended an extra‐binomial variation model for rates standardized by the direct method. The overdispersion parameter accounted for 36 per cent of the observed variation in standardized rates. Ignoring overdispersion resulted in a change in an estimate of the effect of social class on HD mortality and substantial underestimation of the error of the estimates of such effects. Ecologic regression on the proportional mixture of social classes within tracts provided an appealing approach to the problem of estimating fixed effects with aggregated data.
The graphical representation of clinical trials with particular reference to measurements over time
Authors: Senn S. J. , Auclair P. , Johnson Samuel 
Published: April 2007

AbstractClinical trials are frequently analysed as if they were surveys when they are in fact experiments. In particular the experimental basis of clinical trials is rarely reflected in the graphs which are used to illustrate them. Proposals are made, and illustrated by example, as to how appropriate figures may be devised, both for parallel‐group designs and for crossover trials, to illustrate the experimental nature of clinical trials with measurements over time.It is incident to physicians, I am afraid, beyond all men, to mistake subsequence for consequence.
Quantifying misclassification bias in cohort studies of vaccine efficacy
Authors: Farrington Conor Patrick 
Published: April 2007

AbstractA simple mathematical model is presented to quantify the bias due to misclassification in prospective cohort studies of vaccine efficacy. Limitations of methods based on quantifying misclassification in 2 × 2 tables are discussed. The model is applied to data from three examples of the design and analysis of studies of pertussis vaccine efficacy.
Adjusting for misselection using subsampling in epidemiological studies
Authors: Blettner Maria , Becher Heiko 
Published: April 2007

AbstractIn epidemiological research it is sometimes necessary to conduct a case‐control study in a part of the population which is not exposed to certain risk factors. Such a study design may be useful to investigate the risk related to a weak carcinogen in presence of other strong risk factors. It may happen that some individuals are wrongly included in the study group due to misreporting of the true exposure status. This misselection may cause biased odds ratio estimates of the factors of interest. It is therefore recommended that an evaluation study to validate the selection procedure is undertaken. We propose a two‐stage sample design, consisting of a case‐control study and a validation study in a subsample. Misselection rates in cases and control for different exposure groups may be estimated in the subsample and used to correct the odds ratio estimation from the first stage. It is shown how the total sample size should be attributed to the case‐control sample and to the second‐stage sample in order to give an unbiased estimate with minimal variance. The allocation is shown to be dependent on a number of parameters which is illustrated numerically and graphically. Efficiency considerations are also addressed.
Test statistics and sample size formulae for comparative binomial trials with null hypothesis of non‐zero risk difference or non‐unity relative risk
Authors: Farrington Conor P. , Manning Godfrey 
Published: April 2007

AbstractWhen it is required to establish a materially significant difference between two treatments, or, alternatively, to show that two treatments are equivalent, standard test statistics and sample size formulae based on a null hypothesis of no difference no longer apply. This paper reviews some of the test statistics and sample size formulae proposed for comparative binomial trials when the null hypothesis is of a specified non‐zero difference or non‐unity relative risk. Methods based on restricted maximum likelihood estimation are recommended and applied to studies of pertussis vaccine.
Statistical methods for determining risk factors of chronic otitis media with effusion
Authors: Le Chap T. , Lindgren Bruce R. 
Published: April 2007

AbstractWe use logistic regression with paired Bernouilli outcomes to analyse data on subjects who have either one or two organs (e.g. ears) each of which may develop disease. In this model, subject‐specific covariates are related to the probability of developing disease. The proposed method is applied to determine risk factors for chronic otitis media with effusion.
Sample size estimation for comparing two or more treatment groups in clinical trials
Authors: Day Simon J. , Graham David F. 
Published: April 2007

AbstractMethods for estimating required sample size for comparing two population means have been published. Most involve the use of complicated formulae and tables. These methods are limited to comparing two groups. Although techniques exist to determine sample sizes for comparing more than two groups, they are intrinsically far more complicated. A simple linear nomogram is proposed as a solution to these problems, and its use is illustrated with examples of parallel group, ordered parallel group and factorial designs.
Methodological pitfalls in the analysis of contraceptive failure
Authors: Trussell James 
Published: April 2007

AbstractAlthough the literature on contraceptive failure is vast and is expanding rapidly, our understanding of the relative efficacy of methods is quite limited because of defects in the research design and in the analytical tools used by investigators. Errors in the literature range from simple arithmetical mistakes to outright fraud. In many studies the proportion of the original sample lost to follow‐up is so large that the published results have little meaning. Investigators do not routinely use life table techniques to control for duration of exposure; many employ the Pearl index, which suffers from the same problem as does the crude death rate as a measure of mortality. Investigators routinely calculate ‘method’ failure rates by eliminating ‘user’ failures from the numerator (pregnancies) but fail to eliminate ‘imperfect’ use from the denominator (exposure); as a consequence, these ‘method’ rates are biased downward. This paper explores these and other common biases that snare investigators and establishes methodological guidelines for future research.
Epidemiologic oversight of the medical care provided to medicare beneficiaries
Authors: Krakauer Henry , Bailey R. Clifton 
Published: April 2007

AbstractThe Health Care Financing Administration is charged by law with the assurance of the quality of the medical care rendered to Medicare beneficiaries, a function carried out through the Peer Review Organizations. To guide and support this activity, a programme of epidemiologic surveillance of the health of such persons has been devised and is being implemented. Its focus is on the objective measures of health‐mortality, morbidity, disability and expenditures for health care. Its principal components are analyses of trends in those measures over time and of their variations among geographic areas, as problem‐finding techniques, and evaluations of the comparative effectiveness of strategies of management of patients, as problem‐solving tools. Examples of the feasibility and utility of this strategy include an evaluation of the longitudinal impact of administrative changes undertaken in 1983‐1984, the assessment of variations in patient mortality rates among hospitals, the characterization of the management of patients with ischemic heart disease, and a demonstration of a methodology for the observational evaluation of revascularization in various types of patients hospitalized for acute myocardial infarction. The objectives of the programme are the improvement of review of medical practices as carried out by the Peer Review Organizations, assistance to clinicians in the management of patients, and guidance to planners in the allocation of resources.
Empirical evaluation of statistical models for counts or rates
Authors: Wolfe Robert A. , Petroni Gina R. , McLaughlin Catherine G. , McMahon Laurence F. 
Published: April 2007

AbstractWe consider methods for selecting the joint specification of the mean and variance functions in statistical models for rates or counts. Based on analyses of diagnosis‐specific hospital discharge rates in Michigan, we show that a Poisson model with an extra variance component for the systematic variation is superior to several other probability models with regard to specification of the error structure. Further, the deviance residual appears superior to the Pearson residual. The proper specification of such variation is crucial for many types of analyses, such as identification of outliers and regression analyses designed to explain the systematic component of the variation.
Comparison of the proportions of affected relatives of cases and controls: Analysis and minimum sample size formula
Authors: Commenges Daniel , Letenneur Luc 
Published: April 2007

AbstractThe problem of familial aggregation has frequently been approached by comparing the proportion of affected relatives of index cases with the proportion of affected relatives of index controls. This type of study has an analogy with the case‐control design and is frequently analysed as if it was one. It is however an essentially different design which may involve dependent observations. We show that conventional tests for comparing proportions of affected subjects are still valid with this design; we give a formula for computing the minimum sample size required to detect a given degree of aggregation measured by the intracluster correlation coefficient, which can be estimated very simply by the difference in proportions of affected relatives in the two groups.
Fatigue load computation of wind turbine gearboxes by coupled finite element, multi‐body system and aerodynamic analysis
Authors: Heege Andreas , Betran Jaume , Radovcic Yvan 
Published: April 2007

AbstractThe main concern of the present publication is the computation of dynamic loads of wind turbine power trains, with particular emphasis on planetary gearbox loads. The applied mathematical approach relies on a non‐linear finite element method, which is extended by multi‐body system functionalities, and aerodynamics based on the blade element momentum theory. Copyright © 2007 John Wiley & Sons, Ltd.
Gas chromatographic determination of tocopherols and sterols in soya sludges and residues — an improved method
Authors: Nelson J. P. , Milun A. J. , Fisher H. D. 
Published: April 2007

AbstractAn improved method is described for determining the tocopherol and sterol content of soya sludges and residues. Samples are saponified and the extracted unsaponifiables are derivatized prior to gas chromatography to eliminate interferences. Data are presented to demonstrate the improvements realized.