bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estimating reference ranges in clinical pathology: An objective approach
Authors: Merkouriou Savvas , Dix Douglas 
Published: April 2007

AbstractConventional reference ranges evolve from subjective criteria for health and disease. We offer an objective method for distinguishing typical from atypical values by purely statistical criteria. We define typical values as those exhibiting a linear relationship with percentiles on a value versus percentile plot. Identification of percentiles at which deviation from linearity occurs results from calculation of correlation coefficients between values and percentiles over centrally expanding ranges of percentiles. One selects arbitrarily some minimum value for these correlation coefficients, for example, 0.990, as the criterion for deviation from linearity. Values encompassed by these percentiles of deviation constitute an objective reference range. Identification of any correlations between atypical values and symptoms of disease requires clinical follow‐up studies.
Testing for a change‐point in registry data with an example on hypospadias
Authors: Simpkin J. M. , Downham D. Y. 
Published: April 2007

AbstractThe Poisson distribution is often suitable for analysing non‐infectious disorders with low prevalence rates. The numbers of babies born with hypospadias in the Liverpool Congenital Malformations Registry during 1960 to 1982 do not fit a Poisson distribution with constant prevalence rates, but a change‐point Poisson process does fit. A significance test is described and its power is considered in two simulation studies. A small discrepancy is noted that does not diminish appreciably when Bartlett's correction is applied.
Investigation of the associations of a number of HLA antigens with psoriasis and psoriatic arthritis
Authors: Green Jack , Montasser Mandouh , Low Heng Chin , Woodrow J. C. 
Published: April 2007

AbstractA method, using the GLIM computer package, for determining primary and secondary HLA associations with disease is described and is applied to data from patients with psoriasis and psoriatic arthritis.
Loss of power from an optimistic alternative hypothesis
Authors: Blumenson Leslie E. 
Published: April 2007

AbstractIn the planning of a clinical trial to compare the proportion of responses to two treatments one determines the sample size to yield the desired power of achieving a significant difference at a pre‐selected type I error under the assumption that the expected treatment difference exceeds a prescribed minimum. To achieve a practicable sample size, an investigator may be tempted to require a large treatment difference and thereby risk the chance of missing a somewhat smaller but clinically important difference. We obtain in this paper an expression for this loss of power if the true treatment difference is smaller than the minimum used to plan the study. The expression does not explicitly depend on the sample size and for most practical purposes does not depend on the actual response rates but rather varies only as a function of the fractional difference between the required minimum and true treatment difference. With provision of a prior distribution for this fractional difference, we can use the expression to calculate an expected power for the study. An illustration considers the case where the prior follows a beta distribution.
Some analysis strategies for three‐period changeover designs with two treatments
Authors: Hafner Kerry B. , Koch Gary G. , Canada Andrew T. 
Published: April 2007

AbstractAlternative analysis strategies for the three‐period crossover design with two treatments are discussed in this paper. One analysis strategy involves a parametric model that incorporates the effects of interest. To implement this method, one usually assumes that the covariance structure for the data has the sphericity, or circularity, property. Alternative approaches that do not require this assumption are described. They are based on the parametric and non‐parametric analysis of appropriate within‐subject linear functions of the data. The advantage of these methods is that one only needs the assumption that the resulting linear functions for the respective subjects are independent and have a common distribution. The parametric approach also requires normality of the resulting within‐subject linear functions for small sample situations. An extension of the non‐parametric method is considered for cases in which the treatment sequences are randomly assigned within strata. The various methods are illustrated for a three‐period crossover design involving two strata with randomly assigned treatment sequences of the form A:B:A and B:A:B.
Summary attributable risk estimation from unmatched case‐control data
Authors: Kuritz Stephen J. , Landis J. Richard 
Published: April 2007

AbstractWe propose an alternative method to obtain summary estimators, variances and confidence intervals for attributable risk measures. This method combines weighted exposure prevalences for cases and controls across strata formed by the cross‐classification of relevant covariates to form estimates of attributable risk among the exposed and attributable risk in the target population. The major benefit of this approach over those previously proposed in the literature is that it operates on data summed across strata rather than on estimation of statistics within each stratum. This alternative method for attributable risk measures utilizes the Mantel–Haenszel estimate of an average odds ratio, and can be implemented using the matrix procedure in SAS. This method is appropriate even when the within‐stratum sample sizes are too small for other methods to be valid. Simulation results indicate that this method is superior to others with respect to bias and coverage probability for confidence intervals.
Evaluating the discriminatory power of a multiple logistic regression model
Authors: Green Manfred S. 
Published: April 2007

AbstractVarious measures for estimating the goodness‐of‐fit of the multiple logistic regression (MLR) model have been suggested, although there is no clear consensus as to which measure is most suitable. In this paper, a simple measure of the discriminatory power of the fitted MLR model, based on maximization of Youden's J index (J*), is proposed and compared with several goodness‐of‐fit statistics described previously. The relative effectiveness of the measure is illustrated using data from the Lipid Research Clinics Prevalence Study. It is suggested that J* may be a useful alternative index of goodness‐of‐fit of an MLR model, with the added advantage of having a simple practical interpretation.
An uncertainty measure in logistic discrimination
Authors: Lesaffre E. , Albert A. 
Published: April 2007

AbstractThe effect of sampling variation on individual decisions and error rates in logistic discriminant analysis is discussed. The concept of the β‐confidence allocation rule is introduced, which allows testing of whether observations are (in)correctly assigned at a given significance level. The procedure applied to sample data adds valuable information on the sharpness and the stability of the estimated classification rule. The method also suggests that individual posterior probabilities should be associated with a credibility measure. The potential of the approach is illustrated by an example from patients with liver disease.
Multiple reading procedures: The performance of diagnostic tests
Authors: Lachenbruch Peter A. 
Published: April 2007

AbstractThis paper examines the effects on sensitivity and specificity of various multiple reading procedures. Multiple reading procedures entail the performance of a diagnostic test several times and consequent assignment of the subject to an ‘affected’ or ‘unaffected’ group. A Unanimity rule (that is, all tests must be positive) leads to the largest predictive value positive, but may have unacceptably low sensitivity. The rule which classifies the subject as positive based on the majority of the tests increases both the sensitivity and specificity of the individual test. Variability of subjects' sensitivity and specificity (that is, case of correct diagnosis on a test) affects the performance of these rules. We also study alternative procedures in which the final test is a better, but more expensive, test.
Optimal two‐stage designs for clinical trials with binary response
Authors: Thall Peter F. , Simon Richard , Ellenberg Susan S. , Shrager Richard 
Published: April 2007

AbstractWe present a simple two‐stage design for a randomized clinical trial with dichotomous outcomes. It is based on a design of Ellenberg and Eisenberger which permits early acceptance of the null hypothesis after the first stage. We have optimized the design by minimizing the average expected sample size subject to constraints on the type 1 and type 2 errors. The resulting designs have maximum sample size only slightly larger than that of single stage trial, with 40–45 per cent of this maximum allocated to the first stage, and null hypothesis probability of early acceptance in excess of 0.60.
A random walk model for evaluating clinical trials involving serial observations
Authors: Hopper John L. , Young Graeme P. 
Published: April 2007

AbstractFor clinical trials where the variable of interest is ordered and categorical (for example, disease severity, symptom scale), and where measurements are taken at intervals, it might be possible to achieve a greater discrimination between the efficacy of treatments by modelling each patient's progress as a stochastic process. The random walk is a simple, easily interpreted model that can be fitted by maximum likelihood using a maximization routine with inference based on standard likelihood theory. In general the model can allow for randomly censored data, incorporates measured prognostic factors, and inference is conditional on the (possibly non‐random) allocation of patients. Tests of fit and of model assumptions are proposed, and application to two therapeutic trials of gastroenterological disorders are presented. The model gave measures of the rate of, and variability in, improvement for patients under different treatments. A small simulation study suggested that the model is more powerful than considering the difference between initial and final scores, even when applied to data generated by a mechanism other than the random walk model assumed in the analysis. It thus provides a useful additional statistical method for evaluating clinical trials.
Contingency table estimation of genetic parameters and disease risks
Authors: Khamis H. J. 
Published: April 2007

AbstractMany genetic variables, categorical in nature, allow for analysis by use of contingency table techniques and thereby lead to maximum likelihood estimators. This paper describes these techniques for the classical direct effect model under Mendelian segregation to illustrate how one obtains maximum likelihood estimators for penetrance probabilities and recurrence risks when the data appear in the form of a semi‐symmetric intraclass contingency table. The method presented for the 23 table is based exclusively on the generalized cross‐product ratio and the Pearson chi‐squared statistic, and thereby avoids complex statistical methodology and unwieldy computations.
Proportional hazards models for average data for groups
Authors: Dobson Annette J. 
Published: April 2007

AbstractIn ecological studies it is sometimes tempting to apply statistical models derived from longitudinal studies of individuals to cross‐sectional data which may be available only in aggregate form for groups of individuals. This paper examines the assumptions and approximations that are made when average data for groups are used with predictive equations derived for individuals, in particular for the proportional hazards model. It is shown that this method underestimates age‐specific hazard functions but that if ratios of hazard functions are used to compare groups then the approach is valid provided that certain plausible conditions hold. A numerical example is given about trends in heart disease mortality in Australia. Group data are available on risk factor levels and mortality. A proportional hazards model derived from the Framingham study is used to estimate the effects on mortality which may be attributed to risk factor changes and the effects attributable to other factors such as improved medical treatment. The interpretation of the results is discussed.
Prospective epidemiological studies involving paired organs
Authors: Whitehead John , Dorse Cameron 
Published: April 2007

AbstractStandard methods of analysing survival data or case‐control data normally concern factors affecting a subject as a whole. However, in a study of a condition that might develop in one or both of a pair of bodily organs information on response and on covariates may be available for each separately. This information can be used to investigate whether the presence of a factor on one side is associated with the condition on that same side, and thus leads to more direct evidence concerning aetiology. In this paper methods of analysing data on paired organs are described. The techniques are illustrated using data from a case‐control study of breast cancer, in which the role of breast calcifications was of interest.
Investigations of excess environmental risks around putative sources: Statistical problems and a proposed test
Authors: Stone Richard A. 
Published: April 2007

AbstractIndividual reactions to a report which identifies an excess of risk near a putative source are determined mainly by some quoted significance level. One reaction, involving a commonly used ‘coincidence’ argument is given a simple Bayesian explanation. It is argued that interpretations of such reports should if possible allow both for data selection and for uncertainty in the null expectations underlying the significance levels. Tests are proposed, based on the first isotonic regression estimator under an order restriction, which allow for the effects of selecting a study region in the light of the data and have a simple form. Data on cancer incidence around two nuclear plants are used to illustrate.
The statistical analysis of treatment effects in 24‐hour ambulatory blood pressure recordings
Authors: Marler Matthew R. , Jacob Rolf G. , Lehoczky John P. , Shapiro Alvin P. 
Published: April 2007

AbstractThis paper presents a statistical analysis of treatment effects in 24‐hour ambulatory blood pressure recordings. The statistical models account for circadian rhythms, subject effects, and the effects of treatment with drugs or relaxation therapy. In view of the heterogeneity of the subjects, we fit a separate linear model to the data of each subject, use robust statistical procedures to estimate the parameters of the linear models, and trim the data on a subject by subject basis. We use a meta‐analytical method to combine the results of all subjects in the study.
Variance estimation for epidemiologic effect estimates under misclassification
Authors: Greenland Sander 
Published: April 2007

AbstractThis paper presents basic methods for construction of variance estimators for epidemiologic effect estimates when adjusting for misclassification. Methods are described for differential and non‐differential misclassification, and for external and internal estimates of classification rates. The methods take account of sampling variability in both the observed data and the estimated classification rates. The methods are illustrated in a case‐control analysis of the association of antibiotic use during pregnancy with sudden infant death syndrome.
Sample size requirements for studies estimating odds ratios or relative risks
Authors: Lemeshow Stanley , Hosmer David W. , Klar Janelle 
Published: April 2007

AbstractThis paper presents formulae for determining the number of subjects necessary, in either a case‐control or a cohort study, to estimate the odds ratio or relative risk, respectively, to within a selected percentage (ε) of the true population value with some specified probability. This approach differs somewhat from previous comparable work that estimated the log odds ratio within a stated fixed distance rather than as a percentage of the actual odds ratio. Comparable development for relative risk has not previously appeared in the literature. These formulae provide guidelines for determination of study size that does not depend on hypothesis testing considerations.
Confidence intervals for causal parameters
Authors: Robins James M. 
Published: April 2007

AbstractConsider an unbiased follow‐up study designed to investigate the causal effect of a dichotomous exposure on a dichotomous disease outcome. Under a deterministic outcome model, a standard ‘95 per cent binomial confidence interval’ may fail to cover the causal parameter of interest at the nominal rate when we take the causal parameter to be a parameter associated with the observed study population (regardless of whether the observed study population was sampled from a larger superpopulation). I propose new interval estimators that, in this setting, improve upon the performance of the standard ‘binomial confidence interval.’
A Markov process interpretation of Sullivan's index of morbidity and mortality
Authors: Newman Stephen C. 
Published: April 2007

AbstractUsing intuitive arguments Sullivan1 described a method of combining morbidity data and certain ordinary life table functions to produce an estimate of illness‐free life expectancy. In this paper we use an increment–decrement life table specified in terms of a Markov process to characterize illness‐free life expectancy. We show that when the illness under consideration satisfies certain properties, Sullivan's approach provides a convenient method of approximation. We illustrate theoretical results with hospital morbidity data on Canadian males for 1981.
A new calculation of the carcinogenic risk of obstetric X‐raying
Authors: Bithell J. F. , Stiller C. A. 
Published: April 2007

AbstractThe association between obstetric X‐raying and childhood cancer was first identified by the Oxford Survey of Childhood Cancers in 1956. The present re‐analysis exploits the case‐control matching of the study while incorporating the effects of important risk determinants, notably year of birth, trimester of exposure and number of films exposed. The decline in risk over time is closely mirrored by the estimated decline in dose per film and, by constraining these two relationships to be parallel, time‐invariant estimates of the extra risk per mGy are obtained. For example, it is now estimated that irradiating 106 foetuses with 1 mGy of X‐rays would, in the absence of other causes of death, yield 175 extra cases of cancer and leukaemia in the first 15 years of life.
Confidence interval estimation of a rate and the choice of sample size
Authors: Böhning Dankmar 
Published: April 2007

AbstractThe problem of estimating a rate or proportion is considered. Four methods for constructing an approximate confidence interval are discussed and compared via a simulation study. The most accurate method is found. Also, for each method a sharp upper bound (dependent only on the sample size) is given for the length of the confidence interval. By choosing an appropriate sample size this bound enables the practitioner to achieve a prespecified maximum length for the confidence interval without knowing the population rate. The striking result is that the most accurate method has the smallest bound, thus requiring the least sample units.
Designing a clinical trial to demonstrate prevention of ulcer recurrence: Modelling simulation approaches
Authors: Elashoff Janet D. , Koch Gary G. , Chi George Y. H. 
Published: April 2007

AbstractWe describe a Markov chain model for the ulcer recurrence and healing process, review the available literature to obtain appropriate parameter estimates, and use this model to evaluate alternative clinical trial designs. We focus on designs aimed at supporting recurrence prevention claims for a duodenal ulcer maintenance treatment. Our results show that a trial with endoscopies scheduled only at four month intervals is inadequate to support recurrence prevention claims; discrimination between the null and alternative hypotheses is impossible because of the size and direction of expected biases in observed recurrences. Our results suggest that endoscopy intervals should be at most four weeks to establish a claim of ulcer prevention.
Comparing incomplete paired binomial data under non‐random mechanisms
Authors: Choi S. C. , Stablein D. M. 
Published: April 2007

AbstractIn many paired experiments designed to compare two treatments, various mechanisms can lead to the data being incomplete. Such mechanisms may be of a non‐random nature and may depend on the treatment or the outcome. This paper considers several methods for testing the equality of two correlated binomial proportions when the incompleteness is caused by non‐random mechanisms. Several simple procedures are justified in certain cases. The tests based on all available data are more efficient compared to those utilizing only portions of the data. McNemar's test based only on the complete paired observations and the likelihood test are the most robust, although no efficient test exists when the mechanisms are not independent.
Correcting for the bias caused by drop‐outs in hypertension trials
Authors: Murray Gordon D. , Findlay Janet G. 
Published: April 2007

AbstractA major source of bias in hypertension trials can arise from patients who are withdrawn during the course of the trial because of inadequate blood pressure control. We develop a mechanism which allows for such withdrawals while preserving the potential to make an unbiased comparison of the treatment effects. The approach is illustrated using data from a large multicentre trial of two anti‐hypertensive agents in patients with mild to moderate essential hypertension.
Interactions between statisticians and biomedical journal editors
Authors: Marks Ronald G. , Dawson‐Saunders Elizabeth K. , Bailar John C. , Dan Bruce B. , Verran Joyce A. 
Published: April 2007

AbstractThe increased involvement of statisticians in the publication of biomedical research has resulted in increased communication between statisticians and biomedical journal editors. This paper considers ways to enhance positive interactions between statisticians and journal editors. Specific questions addressed are: What are the most serious statistical problems in manuscripts? What statistical design information should the methods include? How can editors identify papers that need statistical review? How can editors interpret what statistical reviewers say? How can editors identify statisticians who are willing to review manuscripts?
Forecasting the demand on accident and emergency departments in health districts in the trent region
Authors: Milner P. C. 
Published: April 2007

AbstractThe annual new, return and total attendances at Accident and Emergency (A and E) Departments for Trent districts and the whole of the Trent region are forecast for the years 1986 to 1994 by using the autoregressive integrated moving average (ARIMA) time series model applied to the SH3 A and E returns for 1974 to 1985. The 1986 forecasts of annual new, return and total attendances in Trent districts are compared with the actual attendances observed; the new attendance forecasts were found accurate, the return attendance forecasts less so. The latter may reflect inability to predict changing policies on return attendances of individual A and E departments. The 1994 ARIMA forecasts of annual A and E new attendances for Trent districts are compared with the 1984 based regional guidelines for 1994 and the projections for individual districts. Both the ARIMA models and the health districts' own projections produce a different forecast to the 1994 regional guideline which seems to overestimate. The forecasting methodology used has other applications in health care planning.