bluuebunny/crossref_metadata_2025 huggingface dataset:
Using the adverse reactions register to study the effects of age and sex on adverse drug reactions
Authors: Simpson Judy M. , Bateman D. N. , Rawlins M. D.
Published: April 2007

Many countries maintain a register of reports of adverse reactions to drugs. Although reports are made voluntarily by doctors and dentists these registers contain much information that may be useful in pharmacoepidemiological studies. We show how the epidemiology of adverse drug reactions (ADRs) can be studied using data from such a register, together with estimates of the numbers of prescriptions of the drug, categorized by age and sex of the patient. Reporting rates of ADRs are compared for different ages and sexes by logistic analysis, using extrapyramidal reactions to metoclopramide as an example. Highly significant effects of sex and age on reporting rates are found, with young women being most at risk. We consider possible alternative explanations of this finding, and show that relative overdosage does not account for the differences between the age and sex groups. Other possible errors in the data are also considered unlikely to alter these conclusions; these include differential bias in reporting ADRs for various age‐sex groups, and errors in the prescription data. Studies based on the adverse reactions registers are useful for formulating hypotheses which can be tested in a prospective study.
The Cardiff health survey: Teaching survey methodology by participation
Authors: Lewis P. A. , Charny M.
Published: April 2007

Medical students were taught survey methodology by participating in all phases of a large community survey. The survey examined health beliefs, knowledge and behaviour in a sample of 5150 people drawn from the electoral register of the City of Cardiff. The study achieved several educational objectives for the medical students: they met well people in their own homes and had an opportunity to get to know a community; by taking part in a study from the initial phases to the conclusion they could appreciate the context of the theoretical teaching they were being given concurrently in their undergraduate course; they learnt to analyse raw data and produce reports; and they gained insights into the health knowledge, behaviour, attitudes and beliefs of a population. In addition, the survey produced a substantial quantity of valuable data which staff and students are analysing and intend to publish.
Evaluating the survival of cancer cases detected by screening
Authors: Walter S. D. , Stitt L. W.
Published: April 2007

Early detection of cancer by screening advances the date of diagnosis, but may or may not affect survival. To assess the survival benefit associated with early detection, one must estimate the distribution of time survived post lead‐time, that is, after the unknown date when clinical diagnosis would have occurred in the absence of screening. One can then compare the adjusted survival of screen‐detected cancer cases to other groups of cases not diagnosed by screening. This paper describes a model for the survival of screen‐detected cases, with a hazard function that depends on an individual's lead time, the duration of preclinical disease, and the time since diagnosis. The model is fitted to the ten year survival data from the 132 screen‐detected cases of breast cancer in the well‐known HIP (Health Insurance Plan of Greater New York) study. Comparison with the survival of several groups of cancer cases not detected by screening (interval cases arising clinically in persons previously screened, cases among persons who refuse screening, and cases among randomized controls not offered screening) yields various estimates of benefit. Use of the interval cases for comparison gives an estimate of about 21 breast cancer deaths prevented among 20, 166 women screened in the HIP study; use of the data from the randomized controls gives an estimate of about 25 prevented deaths. The former estimate derives from the screened group of women only, and so the same method of evaluation may also be applied to community screening programmes and other situations that do not entail randomization.
Early termination of clinical trials with prolonged observation of individual patients: A case study
Authors: Van Es Gerrit‐Anne , Tijssen Jan G. P. , Lubsen Jacobus , van Strik Roel
Published: April 2007

Stopping rules for a placebo controlled clinical trial of anticoagulants after acute myocardial infarction were evaluated by means of computer simulation for the case of five interim analyses. The trial will be terminated and the null hypothesis of no treatment effect rejected when the one‐sided P‐value (logrank test) is lower than 0.005, 0.005, 0.005, 0.014, and 0.023 at the respective interim analyses, and 0.032 at final evaluation. This implies a total size α = 0.05 and a power close to that of fixed sample size testing. The trial will also be terminated, without rejecting the null hypothesis, when the one‐sided P‐value exceeds 0.95, 0.88, 0.81, 0.74, and 0.67 at the respective interim analyses. This modification hardly affects size and power.
Improved estimates of discordance ratios in twin studies
Authors: Franti C. E. , Wiggins A. D. , Kraus J. F.
Published: April 2007

In the study of monozygotic twins relative to disease and risk factors, particular interest focuses on the subset who are discordant for some suspected risk factor (for example, smoking), since such twins constitute a natural case‐control pair. In such studies, questionnaires designed to identify the status of all twin pairs are sometimes error prone and can yield misleading estimates of the concordance‐discordance ratios. Greater efforts to verify the characteristics of apparently discordant pairs than to verify those of apparently concordant pairs can result in the ‘unequal ascertainment’ fallacy.

Using the results of a questionnaire with known error rates and the ‘apparent’ frequencies yielded, we present unbiased, maximum likelihood estimates of the ‘true’ proportions of concordant and discordant pairs. We also present approximate covariances among these estimates.
A longitudinal view of blood pressure during childhood: The muscatine study
Authors: Lauer Ronald M. , Clarke William R.
Published: April 2007

Four thousand three hundred and thirteen children beginning at five to fourteen years of age have been examined on three to six occasions in Muscatine, Iowa, on alternate years. To compare blood pressures throughout the period of observation each value was expressed as a percentile rank. For each subject the average percentile rank (level), the trend in rank and the variability over time were calculated. Values for height, weight, relative weight and triceps skinfold thickness measurements were expressed in the same fashion. There is a relationship between average rank of blood pressure and average rank of body size as well as between trend of blood pressure and trend of body size percentiles. These observations indicate the importance of relative rate of growth in the establishment of the rank order of blood pressure during childhood.
Autoregressive modelling for the analysis of longitudinal data with unequally spaced examinations
Authors: Rosner B. , Muǹoz A.
Published: April 2007

Missing and/or unequally spaced examinations are often present in longitudinal studies. An autoregressive model is presented for the analysis of such data for continuous outcome variables. The fitting of the model can be accomplished by weighted non‐linear regression methods available in standard statistical packages. Some features of the model include consideration of both time‐dependent and fixed covariates, assessment of the relationships between changes in outcome and exposure over short periods of time, and use of all available person‐time for an individual. An illustration looking at the role of personal cigarette smoking on changes in pulmonary function in children is included.
Autoregressive growth curves and Kalman filtering
Authors: Wilson P. David
Published: April 2007

The first part of this paper describes how a Kalman filter can be used to construct maximum likelihood (ML) estimates of autoregressive (AR) and polynomial parameters in polynomial growth curves with AR‐1 errors and irregularly‐spaced data. The second part introduces a disturbed highest derivative polynomial (DHDP) as a model for growth curves. This model does not depend on regression coefficients. Variances of the highest derivative disturbance and the observation error are estimated (by ML) using a Kalman filter. The estimated DHDP growth curve is obtained by optimally smoothing the output of the filter. Equally spaced data is not required. The DHDP model and analysis are developed for an individual and extended to a population growth curve using data from many individuals with covariates.
Comparison of baseline and repeated measure covariate techniques in the Framingham heart study
Authors: Cupples L. Adrienne , D'Agostino Ralph B. , Anderson Keaven , Kannel William B.
Published: April 2007

The purpose of this paper is to indicate how repeated measures on risk factors have been employed in the prediction of the development of disease in the Framingham Heart Study. Since these measures vary over time, the method accounts for time dependent covariates. The technique is a generalized person‐years approach in that it treats each observation interval (of equal length) as a mini‐follow‐up study in which the current risk factor measurements are employed to predict an event in the interval. Observations over multiple intervals are pooled into a single sample to predict the short term risk of an event. This approach is compared to the long‐term prediction of disease which utilizes only the baseline measurements and ignores subsequent repeated measures on the risk factors.
Models of the interaction of mortality and the evolution of risk factor distribution: A general stochastic process formulation
Authors: Manton Kenneth G. , Woodbury Max A. , Stallard Eric
Published: April 2007

Generally analyses of longitudinal studies of chronic disease risks do not directly model the change with time of risk factor values and the interactions of those changes with risk levels. Failure to account for such process characteristics can lead to incorrect inferences about the specific effects of risk factors on mortality, the inability to accurately forecast the future risk of the cohort, and inaccurate statements about the effects of specific risk factor interventions on mortality. We present a model which does describe such a process and show how it can be estimated from longitudinal studies. We also illustrate the effects of certain risk factor process features on the evolution of disease risk data from males in the Framingham, Massachusetts study.
Analysis of incomplete multivariate data using linear models with structured covariance matrices
Authors: Schluchter Mark D.
Published: April 2007

Incomplete and unbalanced multivariate data often arise in longitudinal studies due to missing or unequally‐timed repeated measurements and/or the presence of time‐varying covariates. A general approach to analysing such data is through maximum likelihood analysis using a linear model for the expected responses, and structural models for the within‐subject covariances. Two important advantages of this approach are: (1) the generality of the model allows the analyst to consider a wider range of models than were previously possible using classical methods developed for balanced and complete data, and (2) maximum likelihood estimates obtained from incomplete data are often preferable to other estimates such as those obtained from complete cases from the standpoint of bias and efficiency. A variety of applications of the model are discussed, including univariate and multivariate analysis of incomplete repeated measures data, analysis of growth curves with missing data using random effects and time‐series models, and applications to unbalanced longitudinal data.
Estimating reference ranges in clinical pathology: An objective approach
Authors: Merkouriou Savvas , Dix Douglas
Published: April 2007

Conventional 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

The 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

A 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

In 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

Alternative 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

We 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

Various 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

The 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

This 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

We 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

For 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

Many 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

In 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

Standard 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

Individual 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

This 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

This 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

This 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

Consider 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

Using 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

The 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

The 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

We 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

In 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

A 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

The 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

The 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.
Heterogeneity in survival analysis
Authors: Aalen Odd O.
Published: April 2007

I discuss the impact of individual heterogeneity in survival analysis. It is well known that this phenomenon may distort what is observed. A general class of mixing (or frailty) distributions is applied, extending a model of Hougaard. The extension allows part of the population to be non‐susceptible, and contains the traditional gamma distribution as a special case. I consider the mixing of both a constant and a Weibull individual rate, and also discuss the comparison of rates from two populations. A number of practical examples are mentioned. Finally, I analyse two data sets, the main one containing data from the Norwegian Cancer Registry on the survival of breast cancer patients. The statistical analysis is of necessity speculative, but may still provide some insight.
Improving the quality of data in randomized clinical trials: The compact computer package. Compact steering committee
Authors: Chilvers C. E. D. , Fayers P. M. , Freedman L. S. , Greenwood R. M. , Machin D. , Palmer N. , Westlake A. J.
Published: April 2007

One crucial component for a successful clinical trial is that the data gathered have a high level of reliability and completeness. This paper reviews some problems of data management and describes the computer package COMPACT which has been developed to deal with such problems. The package allows range and consistency checks and can monitor complex follow‐up schedules. A unique feature of the package is a PROBLEMS file which has use both for identification of queries about the data and of patients with particular characteristics of interest. The ability to monitor drug dosages and to signal deviations from the protocol is of particular value. COMPACT has the syntax necessary to create a ‘flat’ file for transfer to statistical packages for analysis, and the variable description files for SAS, SPSS and MINITAB. The package is written in standard FORTRAN which enables transfer to different types of mini and micro computer systems.
Group sequential procedures: Calendar versus information time
Authors: Lan K. K. Gordon , Demets David L.
Published: April 2007

This paper describes the relationship between information time and calendar time in the use of group sequential procedures to monitor interim analyses of clinical trials. Information time is the proportion of maximum subjects or events already observed. Interim analyses often occur at specified calendar times while the definition of classic group sequential procedures occurs in terms of information time. We extend the general group sequential approach of Lan and DeMets1 to include this situation as well.
A survey of models for repeated ordered categorical response data
Authors: Agresti Alan
Published: April 2007

We survey models for analysing repeated observations on an ordered categorical response variable. The models presented are univariate models that permit correlation among repeated measurements. The models describe simultaneously the dependence of marginal response distributions on values of explanatory variables and on the occasion of response. We present models for three transformations of the response distribution: cumulative logits, adjacent‐category logits, and the mean for scores assigned to response categories. We discuss three methods for fitting the models: maximum likelihood, weighted least squares, and semi‐parametric. Weighted least squares is easily implemented with SAS, as illustrated with a study designed to compare a drug with a placebo for the treatment of insomnia.
Estimation of prevalence on the basis of screening tests
Authors: Lew Robert A. , Levy Paul S.
Published: April 2007

Estimates of disease prevalence based on screening tests can be severely biased unless adjusted for the sensitivity and specificity of the screening test. One such adjusted estimate, the maximum likelihood estimator proposed by Levy and Kass, can yield an extreme estimate of zero or one that has undesirable characteristics such as a standard error of zero. We develop here a Bayesian estimator which always falls between zero and one. Users without specialized software can use the maximum likelihood estimate for most circumstances and, in special cases, such as a zero estimate of prevalence, turn to the Bayesian estimate. Others can use software to carry out a complete Bayesian solution. We have provided a method to obtain numerical values for the Bayesian estimate for those ranges of sample size (20–100), sensitivity (07–0.9) and specificity (0.7–0.9) for which the use of this estimator seems most practical.
Does top management team diversity promote or hamper foreign expansion?
Authors: Barkema Harry G. , Shvyrkov Oleg
Published: April 2007

Prior research suggests that top management team (TMT) diversity increases strategic innovation. We extended this argument to the case of entering new geographic areas. In addition to exploring the cognitive implications of TMT diversity, as done in prior research, we explored when diversity may lead to the formation of subgroups within TMTs hampering communication and the propensity to enter new geographic areas. We also examined how these positive cognitive and negative social implications change over time as TMT members interact over the years. The hypotheses were tested using ordinal probit analysis and data on 2,159 expansions of 25 companies over a period of more than three decades. Copyright © 2007 John Wiley & Sons, Ltd.
Entry mode and equity level: A multilevel examination of foreign direct investment ownership structure
Authors: Mani Sudha , Antia Kersi D. , Rindfleisch Aric
Published: April 2007

Over the last two decades, strategy researchers have sought to understand the ownership structure of firms' foreign direct investments (FDI) as reflected in entry mode and equity level. However, prior FDI research has ignored the interrelated nature of these key FDI decisions. In addition, prior research does not fully account for the fact that individual ownership structure decisions occur within the context of a firm's broader FDI portfolio, and thus reflect a wide and frequently unobserved range of parent firm and host nation effects. Our research seeks to address both of these limitations. Using a rich dataset of 4,459 subsidiaries established by 858 Japanese firms across 38 countries over a 9‐year period, we specify a conditional bivariate, cross‐classified multilevel model of FDI ownership structure. Our model enables the joint estimation of entry mode and equity level, accounts for the portfolio nature of FDI, and compares the relative predictive power of transaction cost‐ and experience‐based explanatory variables across both facets of ownership structure. Copyright © 2007 John Wiley & Sons, Ltd.
XRF analysis of Zn–Fe alloy coatings by using measurements at two take‐off angles
Authors: Kataoka Y. , Kohno H. , Furusawa E. , Mantler M.
Published: April 2007

For the analysis of Fe concentrations and coating weights of galvanneal coated sheet steel, a multichannel x‐ray spectrometer with two element channels featuring a low and a high take‐off angle for Zn K as well as Fe K lines has been developed. For the quantification of coating weights and Fe concentrations a new thin‐film fundamental parameter method has been developed that allows the use of intensity ratios of the Zn K to Fe K lines, for the low as well as the high take‐off angle. The accuracy for Fe concentrations obtained in galvanneal sheet steel coatings is 0.28 mass% and therefore satisfactory for the intended practical application. Among the additional useful features of the spectrometer and the developed fundamental parameter method is the possibility to simultaneously analyze the coating weight of pretreatment layers, such as phosphate, on the Zn‐Fe alloy coating. Copyright © 2007 John Wiley & Sons, Ltd.
Fabrication of array detectors with 100 superconducting tunnel junctions and Ta x‐ray absorbers
Authors: Ukibe M. , Kushino A. , Chen Y. , Ohkubo M.
Published: April 2007

We have developed superconducting tunnel junction (STJ) x‐ray array detectors with a large detection area, high detection efficiency, and high counting rate. The STJ array detectors consist of 100 Nb/Al‐AlOx/Al/Nb STJs with a size of 200 × 200 µm. Each STJ has a 2 µm thick Ta absorber connected to the top Nb layer through a thin insulating layer. The absorbers act as an energy converter from high x‐ray energies to phonon energies, which are compatible with superconducting energy gaps. The array detectors realize a total detection area of 4 mm2 and a detection efficiency of ∼70% for x‐rays of energy up to 6 keV. In addition, it is expected that the spatial uniformity of the x‐ray signal outputs of the Nb‐based STJ by using the Ta absorber may be improved by a fast diffusion of quasiparticles in the Ta absorbers. In order to minimize cross talk, we have adapted a coplanar transmission waveguide (CPW) structure having an 8 µm wide signal Nb line, 7 µm wide ground gaps, 12 µm wide ground Nb lines, and a 50 Ω impedance. The fabrication processes and the detector response to x‐rays are discussed. Copyright © 2007 John Wiley & Sons, Ltd.
Surgical management of intestinal malrotation in adults
Authors: Fu Tao , Tong Wei Dong , He Yu Jun , Wen Ya Yuan , Luo Dong Lin , Liu Bao Hua
Published: April 2007

Objective

The aim of this study was to review our experience with diagnosis and surgical management of intestinal malrotation in adult patients.

Patients and Methods

A retrospective review of the surgical outcome of adults with intestinal malrotation was performed. Twelve patients were observed and treated between July 1996 and July 2006 (4 women and 8 men; the mean age of the patients was 28.5 years). Surgical outcomes, including postoperative complications, deaths, and resolution of preoperative symptoms, were measured.

Results

A diagnosis of malrotation was made preoperatively in five patients by upper gastrointestinal contrast study, barium enema, or computed tomography scan. The anomaly was discovered incidentally at laparotomy in seven patients. All cases were proved to be malrotation intraoperatively. Nine patients underwent laparotomy and three underwent laparoscopic surgery (one converted to an open procedure). Follow‐up ranged from 2 months to 118 months. Three patients had complications: one had wound infection, one had delayed gastric emptying, and one developed adhesive ileus. There were only two recurrences detected and one patient with recurrence required reoperation. No one died.

Conclusions

Intestinal malrotation is a rare but important cause of abdominal pain in adults. It may present with chronic or acute symptoms. Laparotomy and laparoscopy are alternative and feasible techniques with low rates of complications for the treatment of intestinal malrotation in adults.
Regionally selective decreases in cerebral glucose metabolism in a mouse model of phenylketonuria
Authors: Qin M. , Beebe Smith C.
Published: April 2007

Impairment of cognitive function is characteristic of untreated phenylketonuria in humans and in the pahenu2 mouse model of phenylketonuria. We measured regional cerebral metabolic rate for glucose in the adult male pahenu2 mouse to determine the effect of PKU on functional activity in brain and to discern what, if any, brain areas are affected. Our results demonstrate selective decreases (17–21%) in regions thought to be involved in executive function. Regions most significantly affected include prelimbic, anterior cingulate, orbital frontal and perirhinal cortex. Sensory and motor areas of cortex and hippocampus were remarkably unaffected.
Periprosthetic Fractures of the Femur after Hip Arthroplasty: An Analysis of 99 Patients
Authors: Holley Keith , Zelken Jonathan , Padgett Douglas , Chimento George , Yun Andrew , Buly Robert
Published: April 2007

The medical records and radiographs of 99 patients treated for a periprosthetic femur fracture after total hip arthroplasty over a 17-year period at a single institution were prospectively reviewed. Fractures were classified according to the Vancouver system and stratified as to treatment method. Sixty-six patients had complete records available and a minimum of 12 months follow-up. Overall, 86% of the patients achieved fracture union. The success rate of cemented revision in the B2 and B3 groups was 84%, whereas cement-less revision was 86% successful. The complication rate of surgical treatment was 29%. Fracture union with a stable implant was possible in the majority of cases. Our results support the use of the Vancouver classification as a treatment algorithm.