bluuebunny/crossref_metadata_2025 huggingface dataset:
The measurement of change of quality of life in clinical trials
Authors: Zwinderman Aeilko H.
Published: April 2007

A model is presented for the measurement of change of quality of life in clinical trials with time under the influence of one or more treatments. Quality of life is regarded as a multidimensional latent variable, and is measured through dichotomous item responses on a number of points in time. Change of quality of life is ‘explained’ with a latent logistic regression model which may include parameters for the time process, the effects of clinical treatments, and interaction parameters. By assuming the absence of patient/time interaction within treatment groups, the parameters of the time process and the treatment effects can be estimated independently of the latent quality of life parameters at the start of the treatment. Consequently, differential mortality, censoring mechanisms, and other mechanisms causing missing data can be ignored.
What statistics should we teach medical undergraduates and graduates?
Authors: Appleton Davi D. R.
Published: April 2007

It is suggested that the emphasis on teaching statistics to medical undergraduates has usually been quite wrong: that the courses have become much too long, too detailed, and irrelevant to the needs of the majority. Examples are given which may help to introduce the basic concepts which all medical (and dental) undergraduates require, and which form a basis for the more traditional teaching of analytical methods to the appropriate subset who proceed to undertake medical research.
Who should teach medical statistics, when, how and where should it be taught?
Authors: Clayden A. David
Published: April 2007

As far as we can tell, there is no single answer to any of these questions. This paper describes some of the approaches adopted in the teaching of medical statistics in the U.K. medical schools. It is suggested that collaboration between non‐statistically qualified teachers and medical statisticians is beneficial, with an emphasis in the application of statistical principles to interesting and ‘relevant’ medical topics. A block of ‘laboratory based’ teaching in the early years may be followed by occasional, clinically focused sessions later in the undergraduate course. Research oriented courses, made available when postgraduates have a real and pressing need for information, are thought likely to be most valuable and rewarding for students and statisticians. It is thought that the use of information technology to improve the communication of concepts and ‘facts’ during lectures, and for ad hoc enquiries by students, is likely to make the most of the limited teaching resources. The future is thought to be in the greater use of small group or individualized teaching which confirms or tests the knowledge gained from students use of I.T. supported activities. Unless lecturers collaborate in evaluative studies which compare different teaching methods, it will never be possible to provide valid generalizable advice to teachers of medical statistics.
Statistics for medical students in the 1990's: How should we approach the future?
Authors: Evans Stephen J. W.
Published: April 2007

Medical statistics teaching in the U.K. has moved over the past twenty years from needing justification to acceptability. In the future teachers need to involve statistical and medical colleagues to improve the content and presentation of their material. While some techniques must continue to be taught, the conceptual aspects of scientific evaluation and assessment will need to increase.
Statistical interim monitoring of the cardiac arrhythmia suppression trial
Authors: Pawitan Yudi , Hallstrom Alfred
Published: April 2007

The Cardiac Arrythmia Suppression Trial was stopped much earlier than planned. Statistical considerations played a very important role in the decision. Flexible group sequential testing was developed for the trial by implementing a Lan and DeMets procedure with use of the permutation test. We compute P‐values from the joint permutation distribution of the test statistics, so we do not need to estimate the sampling distribution which in general is rather difficult to do without strict assumptions. The method also gives an exact test for small samples and allows us to use more complicated or non‐Gaussian statistics. We also utilized stochastic curtailment ideas to evaluate various scenarios that might occur during the course of the trial, which assisted the Data and Safety Monitoring Board in making appropriate decisions.
Measuring interrater reliability among multiple raters: An example of methods for nominal data
Authors: Posner Karen L. , Sampson Paul D. , Caplan Robert A. , Ward Richard J. , Cheney Frederick W.
Published: April 2007

This paper reviews and critiques various approaches to the measurement of reliability among multiple raters in the case of nominal data. We consider measurement of the overall reliability of a group of raters (using kappa‐like statistics) as well as the reliability of individual raters with respect to a group. We introduce modifications of previously published estimators appropriate for measurement of reliability in the case of stratified sampling frames and we interpret these measures in view of standard errors computed using the jackknife. Analyses of a set of 48 anaesthesia case histories in which 42 anaesthesiologists independently rated the appropriateness of care on a nominal scale serve as an example.
Adjusting for age‐related competing mortality in long‐term cancer clinical trials
Authors: Cheuvart B. , Ryan L.
Published: April 2007

Mortality related to causes other than the treated disease may have a significant impact on overall survival in long‐term clinical trials. We present a model that adjusts for age‐related competing mortality when cause of death is missing or only partially available. Through use of a piecewise exponential survival model, we extend relative survival methods to continuous follow‐up data, allowing the competing mortality to differ from that of the general population by a scale parameter. An EM algorithm provides a simple way to compute the maximum likelihood estimators (MLEs) and to test hypotheses using widely available software. We compare the bias and relative efficiency of this model to a piecewise exponential Cox model for overall survival. Theoretical results are confirmed by simulations and illustrated with data from a clinical trial in colorectal cancer. This example also shows how age‐related and disease‐related mortality can be confounded in an analysis of overall survival. We conclude with a discussion of the advantages and dis‐advantages of the model.
Estimability and estimation of expected years of life lost due to a hazardous exposure
Authors: Robins James , Greenland Sander
Published: April 2007

Expected years of life lost is an important concept in public‐health and legal issues. We describe conditions under which the expected years of life lost due to hazardous exposure is estimable (identifiable) from epidemiologic data. We show that, in general, the average years of life lost among exposed subjects dying at a given age (the age‐specific expected years of life lost) is not identifiable, although the average years of life lost among all exposed subjects (the unconditional expected years of life lost) is identifiable from an unbiased epidemiologic study. We also show that the average years of life lost among all exposed subjects dying of a specific cause (the cause‐specific expected years of life lost) is not identifiable. We discuss the implications of these results for compensation schemes based on years of life lost, and compare such schemes with those based on the probability of causation.
Behavioural and biological determinants of fertility transition in sub‐saharan Africa
Authors: Frank Odile , Bongaarts John
Published: April 2007

In the transition from high to low fertility, different biological and behavioural proximate determinants play roles of varying importance in mediating the change. In most regions of the world, the practice of contraception has come to play the major role, so much so that there is a close relationship worldwide between the level of practice of contraception and the level of fertility. In sub‐Saharan Africa, the prevalence of contraceptive practice is low, and fertility levels are exceptionally high for recorded levels of contraceptive practice, even where levels of contraceptive practice are comparable to other regions. The discrepancies are explained to a very large extent by differences between Africa and other regions in other proximate determinants‐notably exposure to the risk of pregnancy, and abstinence after delivery. It would seem that transition in African countries will follow one of two patterns that are different to the pattern of transition observed in all other regions. First, fertility may rise before it declines, due to abandonment of traditional fertility regulation for some time prior to the eventual adoption of contraceptive practice. Second, the prevalence of contraceptive practice may rise for a time before there is an observable decline in fertility, because at the same time that contraception is adopted, traditional regulation of fertility is being abandoned, offsetting any effect on fertility. Kenya is an example of the first pattern, while Botswana, Ghana, and Zimbabwe are probably examples of the second.
The description of menstrual bleeding patterns: Towards fewer measures
Authors: Belsey Elizabeth M. , Carlson Nancy
Published: April 2007

The disturbance in menstrual bleeding induced by many methods of contraception is an important factor in their acceptability, and women participating in clinical trials of new methods are usually asked to keep a calendar record of the occurrence of bleeding. A recent WHO report recommends that, for analysis and presentation, each menstrual diary should be divided into successive periods, and the woman's bleeding pattern in each period summarized in ten indices. These indices are simple to calculate and easily understood by clinicians, but comparison of several groups is problematic because of the large number of summary statistics generated.

Principal components analysis was therefore used to determine whether the indices could be reduced to a smaller number of measures. The analyses showed that three of the indices ‐ the range and maximum value of bleeding/spotting episode lengths and the minimum bleeding‐free interval ‐ rarely measure their intended dimension of the bleeding pattern. Most of the essential information about a woman's bleeding pattern is contained in only four of the ten indices: the number of bleeding/spotting episodes, the mean lengths of episodes and intervals, and the range of bleeding‐free interval lengths. Together, these indices describe the most important dimensions of a pattern: the amount, frequency and variability of the bleeding.
Estimation of the spontaneous abortion risk in the presence of induced abortions
Authors: Hilden J. , Modvig J. , Damsgaard M. T. , Schmidt L.
Published: April 2007

We propose a method of estimating the miscarriage risk in a setting where counts of births, miscarriages and induced abortions are available, and also the gestational week of each induced abortion. Unlike previously proposed methods, ours takes into account the fraction of the miscarriage risk to which each interrupted pregnancy has been exposed. For this purpose, we draw on an extraneous standard foetal survival curve and stipulate that the survival curve of the study population is a scaled version thereof. Three such scaling models are discussed, and it is shown that the choice is largely a matter of computational convenience. Separate attention is given to a competing‐risk model of miscarriages and interruptions, and examples are given of reasons why the crucial assumption that these two sources of termination operate independently is unlikely to be met. Finally, it is argued that pregnancy wishes, especially those of habitual aborters, shape the miscarriage rate to the extent that it becomes as much a cultural parameter as a marker of biological hazards.
A simulation study comparing designs for dose ranging
Authors: Sheiner Lewis B. , Hashimoto Yukiya , Beal Stuart L.
Published: April 2007

Only with knowledge of the (prior) distribution of dose‐response parameters in a population, can one determine both the initial dose of a drug for chronic administration to an individual (such as the dose producing a fixed degree of response in a fixed proportion of the population) and an appropriate subsequent (adjusted) dose (such as the dose yielding a desirable response according to the posterior parameter distribution, given an observed response to an initial dose).

The currently FDA‐sanctioned design for a dose‐ranging study, the parallel‐dose design, assigns just one of several doses to each patient. It does not provide good information on the distribution of individual dose‐response parameters. A cross‐over design assigns several dose levels to each patient. It therefore can provide better information, but does not resemble clinical practice. Consequently, study participants must be restricted to patients who can tolerate such non‐therapeutic drug exposure, posing problems in extrapolation of study results to other types of patients. A titration or dose‐escalation design begins all patients on placebo and, except for those patients assigned to a placebo‐only group, escalates the dose for a patient at preset intervals only when clinical response at lower doses is inadequate. It both exposes patients to several dose levels and resembles good clinical practice, allowing study of a representative patient sample.

We report here the simulation results of parameter estimation for the three designs when the data arise from complex and realistic dose‐response models and/or with certain complications in study execution. The dose‐escalation design clearly performs better overall than the parallel‐dose design for the models considered here, and generally, just a little worse than the cross‐over design. These results support the conclusion that for dose ranging, depending on the demands of the clinical situation, one should use either the cross‐over or the dose‐escalation design.
A model for the identification of hormone pulses
Authors: Kushler Robert H. , Brown Morton B.
Published: April 2007

Several hormones are released into the blood in a pulsating manner, that is, in short bursts which cause a rapid increase in the circulating concentration. The concentration then declines due to excretion, chemical breakdown, and redistribution into other compartments. Based on a series of observations of the level of hormone in the blood, investigators desire to quantify characteristics of these pulses, that is, timing, amplitude and rate of decay. We describe a statistical model for hormone pulse data and introduce a new method for estimating the characteristics of the pulses.
A statistical method for assessing a threshold in epidemiological studies
Authors: Ulm K.
Published: April 2007

I describe a method for estimating and testing a threshold value in epidemiological studies. A threshold effect indicates an association between a risk factor and a defined outcome above the threshold value but none below it. An important field of application is occupational medicine where, for a lot of chemical compounds and other agents which are non‐arcinogenic health hazards, so‐alled threshold limit values or TLVs are specified. The method is presented within the framework of the logistic regression model, which is widely used in the analysis of the relationship between some explanatory variables and a dependent dichotomous outcome. In most available programs for this and also for other models the concept of a threshold is disregarded. The method for assessing a threshold consists of an estimation procedure using the maximum‐likelihood technique and a test procedure based on the likelihood‐ratio statistic R, following under the null hypothesis (no threshold) a quasi one‐sided X2 distribution with one degree of freedom. This use of this distribution is supported by a simulation study. The method is applied to data from an epidemiological study of the relationship between occupational dust exposure and chronic bronchitic reactions. The results are confirmed by bootstrap resampling.
Determining efficacy of monitoring devices: Evaluating new technologies
Authors: Tolley Elizabeth A. , Somes Grant W. , Willey Elaine S. , Phelps Stephanie J.
Published: April 2007

We point out the connection between electronic monitoring and repeated screening tests, and suggest a flexible and practical method to determine the efficacy of monitoring devices and new technologies. We point out the benefits of the Mantel‐Haenszel estimator of an odds ratio for determining diagnostic test indices. From estimates of sensitivities and specificities, we produce receiver operating characteristic (ROC) curves to compare the performance of two or more monitoring devices in a clinical setting.
The effect of non‐differential outcome misclassification on estimates of the attributable and prevented fraction
Authors: Hsieh Chung‐heng
Published: April 2007

This paper considers the effect of non‐differential outcome misclassification on the population attributable fraction and the population prevented fraction. I examine the bias in the attributable and the prevented fraction derived from a risk ratio estimate as a function of the sensitivity and specificity of the outcome classification, the true risk ratio, the prevalence of the exposure, and the baseline disease frequency. With outcome misclassified, disease frequency is an important determinant of the magnitude of the bias; the rarer the disease, the more severe is the bias. For both the attributable and the prevented fraction, the specificity of the outcome classification has a greater influence on the magnitude of the bias than the sensitivity; this is in contrast to the dominant effect of sensitivity in situations of exposure misclassification. Also, unlike the findings in the exposure misclassification, the bias due to outcome misclassification does not increase monotonically with increased prevalence of exposure. For the attributable and prevented fraction derived from an odds ratio estimate, the specificity of the outcome classification does not have a greater influence on bias than the sensitivity, and a perfect specificity alone does not lead to unbiased effect estimates if the sensitivity of the outcome classification is imperfect.
Death after marital bereavement‐is the risk increased?
Authors: Jagger Carol , Sutton Christopher J.
Published: April 2007

Previous studies on the effect of marital bereavement on mortality have suggested various time periods during which the risk of mortality is increased. As many of the studies compared the widowed group with national mortality statistics for the married, there has been no opportunity to adjust for confounders which might themselves be responsible for this increased risk after bereavement. In this paper the various hypotheses proposed are reviewed and then modelled on a dataset of 344 elderly persons who were living with a spouse and who were part of a survey of a population of people aged 75 years and over. The 344 index‐ases and their spouses were followed up for seven years and the times of death (for those who died) of the index‐ase and spouse were noted. The data were analysed by fitting a proportional hazards model to the subject's survival time after adjustment for other factors such as mental and physical health which had already been shown to be associated with mortality. The bereavement effects were fitted as time‐dependent covariates. The best fitting model for females and males indicated an increased relative risk of mortality which lasted for approximately six months after bereavement. In the case of widows this relative risk was significantly increased, being 3.8 with 95 per cent confidence interval (1.4, 10.3) while for widowers the risk was 0.03 with 95 per cent confidence interval (0.00, 37.3).
A qualifier Q for the survival function to describe the prevalence of a transient condition
Authors: Pepe Margaret Sullivan , Longton Gary , Thornquist Mark
Published: April 2007

We propose an estimator of the prevalence of a transient condition among surviving patients using right censored data. The prevalence of opportunistic infection among surviving AIDS patients and the probability of being in tumour response following cancer therapy conditional on being alive are two examples of such functions. In essence these functions describe a major aspect of the quality of life for surviving patients and may be useful when viewed in conjunction with the survival curves themselves. The method is illustrated using data from a randomized trial of bone marrow transplant patients where the prevalence of chronic graft‐versus‐host disease is of interest. The non‐parametric estimator which we have proposed is contrasted with estimators derived from Markov and semi‐Markov models.
Confidence intervals for post‐test probability
Authors: Monsour Michael J. , Evans Arthur T. , Kupper Lawrence L.
Published: April 2007

Confidence intervals are a natural way to describe the uncertainty of post‐test probability in diagnostic tests. We consider confidence intervals for two different scenarios. At a site, for example, hospital emergency room or student health centre, with measured values of disease prevalence, sensitivity and specificity available, the confidence interval is similar to results in the literature, but at a site where measured values of these indices are unavailable, we develop a method, using the values of disease prevalence, sensitivity and specificity from other sites, to obtain a confidence interval for post‐test probability. We use the diagnosis of strep throat to illustrate the results. We also obtain confidence intervals from simulations to compare with the results of both scenarios.
Sample sizes for repeated measurements in dichotomous data
Authors: Lui Kung‐Jong
Published: April 2007

When the measurement of outcome varies within studied subjects and the cost of additional subjects is high, taking more than one measurement for each subject constitutes a useful alternative to increase the power or to reduce the total cost of the study. In this paper, I present sample size formulae for repeated measurements in dichotomous data under different situations. I also discuss optimal sample allocation for repeated measurements.
Using routinely collected data for clinical research
Authors: Safran Charles
Published: April 2007

Clinical research involving prospective data collection in randomized controlled trials is not always feasible. Increasingly, hospitals are developing large clinical databases that are waiting to be mined. We have developed a computer program, ClinQuery, that facilitates such exploration and analysis. We have also shown in a series of studies that the use of clinical data is a powerful tool in health services research. In some cases, we have shown that coded data are inaccurate and that alternative clinical data are preferable. In other cases, a combination of clinical data and coded discharge diagnoses is preferable.
Methods for the analysis and assessment of clinical databases: The clinician's perspective
Authors: Pryor David B. , Lee Kerry L.
Published: April 2007

Innovative approaches to analysing clinical databases can be considered from a perspective of innovations that improve the analytic approach or from a more global perspective in which clinical databases themselves are evaluated as a technology. The analytic approach for using a database to estimate risk can be considered as a matrix of three methodologic concerns: the predictive method; the assessment of the quality of the predictions; and the assessment of the validity or generalizability of the predictions. Considering databases as a technology places in perspective the merit of clinical databases and defines their potential value to the health care system. An awareness of both the clinical and analytic problem encourages innovation and can lead to creative solutions to the many problems present in the analysis of clinical databases.
Using databases to evaluate therapy
Authors: Hlatky Mark A.
Published: April 2007

Clinical and administrative databases are increasingly used for clinical research. Descriptive studies and analyses of prognostic factors are established research uses of databases, but using them to compare therapies remains controversial. Such comparisons may be possible when a validated model of prognosis can account for the effect of clinically recognized variables on outcome. Models meeting these criteria have been developed using the Duke Cardiovascular Disease Database. They were applied to compare medical therapy to surgical therapy for coronary artery disease. Predictions from these models agreed well with the results of the three major randomized trials of bypass surgery versus medical therapy. These findings indicate that when data is reliable and understanding of factors affecting prognosis is good, researchers can use statistical techniques to minimize the bias due to non‐random treatment assignment. Carefully performed analyses of observational clinical data can complement and extend randomized studies.
Constructing time‐specific reference ranges
Authors: Royston Patrick
Published: April 2007

Reference ranges which take time (such as age) into account are often required in medicine, but simple, systematic and efficient statistical methods for constructing them are lacking. A method is described which is based on low order polynomial curves (linear, quadratic or occasionally cubic), together with guidelines for when and how to apply a logarithmic transformation to the variable analysed, testing for departures from normality, and assessment of the adequacy of the reference range which is constructed from the regression line plus or minus a multiple of the standard deviation. Standard statistical packages may be used to carry out the calculations. The question of comparing two or more groups of patients is addressed. Three examples are discussed in detail.
Estimation of reference ranges from normal samples
Authors: Royston P. , Matthews J. N. S.
Published: April 2007

Reference ranges are very widely used in medicine, and are typically computed as mean plus or minus two standard deviations. However, their precise statistical basis is rarely discussed, and is open to different interpretations. They are sometimes calculated using the Student t distribution and satisfy the condition that the expected coverage of the reference population is some nominal value such as 95 per cent or 99 per cent. A case is made for using reference ranges which are based on estimating symmetric centiles of the underlying normal distribution, and appropriate formulae are given. The simplest such estimator, the sample mean plus or minus the normal‐based number of sample standard deviations, is shown to have both theoretical and practical advantages.
A proposal for examining and reporting stepwise regressions
Authors: Hauck Walter W. , Miike Rei
Published: April 2007

A common mode of regression analysis is a stepwise regression. One of the problems associated with the stepwise algorithm is that the data analyst may wrongly identify the selected variables as the important variables. We propose a simple table as an aid in examining and reporting stepwise regression analyses. The key to our proposal is recognition of ‘close alternatives’, that is, those variables excluded from selection by the inclusion of another variable. This presentation should encourage the analyst and reader to think in terms of sets of variables that, together, represent factors associated with the outcome.
The effects of model selection on confidence intervals for the size of a closed population
Authors: Regal Ronald R. , Hook Ernest B.
Published: April 2007

One encounters in the literature estimates of some rates of genetic and congenital disorders based on log‐linear methods to model possible interactions among sources. Often the analyst chooses the simplest model consistent with the data for estimation of the size of a closed population and calculates confidence intervals on the assumption that this simple model is correct. However, despite an apparent excellent fit of the data to such a model, we note here that the resulting confidence intervals may well be misleading in that they can fail to provide an adequate coverage probability. We illustrate this with a simulation for a hypothetical population based on data reported in the literature from three sources. The simulated nominal 95 per cent confidence intervals contained the modelled population size only 30 per cent of the time. Only if external considerations justify the assumption of plausible interactions of sources would use of the simpler model's interval be justified.
A note on the calculation of expected survival, illustrated by the survival of liver transplant patients
Authors: Thomsen Birthe Lykke , Keiding Niels , Altman Douglas G.
Published: April 2007

Based on historical regression analyses of survival one may calculate expected survival curves for patients in a study group, based on their observed covariates. This note discusses this calculation and illustrates it on a comparison of the survival of a certain group of liver transplant patients to their prognosis under conservative treatment.
Analytic methods for two‐stage case‐control studies and other stratified designs
Authors: Flanders W. Dana , Greenland Sander
Published: April 2007

Nested case‐control studies, or case‐control studies within a cohort, combine the advantages of cohort studies with the efficiency of case‐control studies. Case‐control studies can often be viewed as having two stages; the first stage consists of vital status, disease, and basic covariate ascertainment, and the second stage consists of detailed covariate and exposure ascertainment. Breslow and Cain (1988) and Breslow and Zhao (1988) recently showed that conventional analyses of such two‐stage studies may ignore some of the available information. In this paper, we show how one can adapt the pseudo‐likelihood analyses developed by Kalbfleisch and Lawless (1988) to the analysis of data from two‐stage case‐control studies.
The construction of biochemical reference ranges and the identification of possible adverse drug reactions in the elderly
Authors: Lawrence C. J. , Trewin V. F.
Published: April 2007

In the assessment of adverse drug reactions (ADRs) it is important to establish what is a normal range of values for a given biochemical measurement. Furthermore, such ranges need to be specific to the study population, for example, the elderly. A mixture of Gaussian distributions has been used in the construction of the reference ranges with maximum likelihood used to obtain estimates of the unknown parameters. With this approach, well‐defined reference ranges have been established. Brief details are given of the numbers of ADRs identified in the study population using these ranges.
On the use of historical controls in the analysis of laboratory data
Authors: Yoshimura Isao , Hayashi Makoto
Published: April 2007

Our purpose is to propose a method of data analysis incorporating historical controls. It consists of three steps of hypothesis testing procedure. The first step is the check of concurrent controls. The second is the significance testing of treatment groups in comparison with historical controls which are composed of negative and positive controls. The third is the significance testing of a linear trend of the dose‐response relationship. The superiority of the proposed procedure is also verified.
Multiple testing in clinical trials
Authors: Bauer P.
Published: April 2007

The basic ideas of multiple testing are outlined and the problem of how to control the probability of erroneous decisions is discussed. The main emphasis is on the concept of the multiple level of significance (controlling the experiment, or family error in the strong sense) which can be achieved by applying the principle of closed tests. Various practical situations encountered in multiple testing in clinical trials are considered: more than one end point; more than two treatments, such as comparisons with a single control, comparisons using ordered alternatives, all pairwise comparisons and contrast methods; and more than one trial. Tests based on global statistics, the union intersection principle and other criteria are discussed. The application of the multiple test concept in sequential sampling is investigated. Finally some comments are made on multiple power, multiple confidence intervals and directed decisions.
A random effects model for ordinal responses from a crossover trial
Authors: Ezzet Farkad , Whitehead John
Published: April 2007

Crossover studies have been successfully conducted in the case of continuous responses. Existing procedures of analysis for ordinal responses, on the other hand, are rarely satisfactory unless strict, usually unrealistic, assumptions are made. In this paper we investigate a random effects model and show that the model is simple and general. Interpretation of parameters is easy, though with a complicated fitting procedure.
Interim analysis in clinical trials
Authors: Armitage Peter
Published: April 2007

The early development of experimental design discouraged a sequential approach to the analysis of data, yet this seems a natural form of scientific enquiry. Clinical trial investigators should continuously monitor the quality of their techniques, but will often wish to delegate data monitoring to an independent group. The history and functions of data monitoring committees (DMCs) are reviewed. DMCs come in many shapes and sizes. They will need to consider many aspects of the data before making recommendations to the investigators, who have ultimate responsibility for early termination or protocol changes.

Statistical issues form part of the assessment, and will involve management, safety and efficacy. Two broad approaches to early stopping are (i) the demonstration of strong evidence that a treatment effect falls above or below some critical value (not necessarily zero); (ii) stochastic curtailment based on prediction of final results. The latter is examined somewhat critically. Most trials will involve group sequential analyses at discrete time points. The effect of repeated data inspection on (i) is well known, although its relevance is debatable. Bayesian and likelihood methods do not entirely remove the difficulty.
Step‐down multiple tests for comparing treatments with a control in unbalanced one‐way layouts
Authors: Dunnett Charles W. , Tamhane Ajit C.
Published: April 2007

We show how a well‐known multiple step‐down significance testing procedure for comparing treatments with a control in balanced one‐way layouts can be applied in unbalanced layouts (unequal sample sizes for the treatments). The method we describe has the advantage that it provides p‐values, for each treatment versus control comparison, that take account of the multiple step‐down testing nature of the procedure. These joint p‐values can be used with any value of α, the fixed type I familywise error rate bound, that may be specified by the investigator. To determine the p‐values, it is necessary to compute a multivariate Student t integral, for which a computer program is available. This procedure is more powerful than the step‐down Bonferroni procedure of Holm1 and the single‐step procedure of Dunnett.2 An example from the pharmaceutical literature is used to illustrate the procedure.
Problems induced by meta‐analyses
Authors: Chalmers Thomas C.
Published: April 2007

Over 150 meta‐analyses of randomized control trials have so far been published in the English language, and new ones are appearing at a rate of over fifteen per year. This explosion of a relatively new method of evaluating clinical medicine presents a number of challenges to statisticians and those responsible for health care policy. The pitfalls of retrospective research must be avoided, and the quality of the original trials should be evaluated. Heterogeneity of the control event rates and the treatment differences need to be dealt with statistically. Most important are the problems raised by the need to update meta‐analyses as new trials are published.
Maximum likelihood techniques applied to method comparison studies
Authors: Nix A. B. J. , Dunstan F. D. J.
Published: April 2007

One component of method comparison studies is the assessment of relative bias. Most authors use ordinary regression techniques for this purpose. The potential inadequacies in this approach are highlighted and a more generally applicable maximum likelihood technique proposed. The properties of the various methods of estimation are obtained by means of a simulation study, using a variety of different within‐assay precision profiles.
The potential for spread of HIV in the heterosexual population in Norway: A model study
Authors: Stigum Hein , Grønnesby J. K. , Magnus P. , Sundet J. M. , Bakketeig L. S.
Published: April 2007

A simulation model is used to investigate the potential for indigenous spread of human immunodeficiency virus (HIV) in the heterosexual population in Norway. The heterosexual population is grouped according to age, sex and whether paired or single. Estimates of various parameters of sexual behaviour are taken from a population‐based questionnaire study. The questionnaire was sent to a random sample of 10,000 individuals, with a response rate of 63 per cent. The main simulation result is that with no inflow of infection from other risk groups, the heterosexual epidemic will decline if the average transmission probability per intercourse is 1 per cent or less. This result is insensitive to changes in the initial conditions. It is sensitive to changes in sexual behaviour, and to the shape of the transmission probability distribution. A review of empirical partner study data indicates an average transmission probability about 0.1 per cent per intercourse when no transmission modulating cofactors are present. It is concluded that with present sexual behaviour, the indigenous spread of HIV is not likely to sustain an epidemic in the Norwegian heterosexual population.
An estimating equation approach for the analysis of case‐control studies with exposure measured at several levels
Authors: Sato Tosiya
Published: April 2007

Liang gave an extension of the Mantel‐Haenszel estimating procedure for a common odds ratio to logistic regression models. It is applicable to case‐control studies with multiple exposure levels, which yield K 2 × J tables. This paper provides variance and covariance estimators, which are consistent in both sparse‐data and large‐strata, for Liang's estimating functions in the K 2 × J tables case, and proposes an approximate confidence interval method for the common odds ratios.
The analysis of failure time data in crossover studies
Authors: France Lesley A. , Lewis John A. , Kay Richard
Published: April 2007

Clinical trials of new drugs in the treatment of angina pectoris frequently make use of exercise tests to evaluate efficacy. The crossover design is often employed. The methods commonly used to analyse the various exercise times, for example, ‘time to pain’, are insensitive and potentially biased by the manner in which they deal with the censored nature of the data. Survival analysis can be adapted for use in crossover trials, both in a relatively simple way, and also through the full power of the Cox model. This is considerably more sensitive and not subject to the same bias. This methodology leads to the use of median survival times to illustrate treatment effects and this provides a practical interpretation of clinical relevance. The estimation of median survival times in crossover trials poses some special problems. The methodology is illustrated throughout by means of a specific two‐period example in which atenolol was compared with the combination of atenolol and nifedipine. The three‐period design is also briefly discussed.
Recovery of inter‐block information in cross‐over trials
Authors: Chi Eric M.
Published: April 2007

For cross‐over designs, we show that one can recover information on direct and/or residual treatment effects from an inter‐block (patients as blocks) analysis as is done in an incomplete block design.1 By combining the intra‐ and inter‐block estimates, we obtain the generalized least squares estimate. In analysing cross‐over trials, we recommended this approach provided the between‐patient variance component can be estimated efficiently.
A quasi‐exact test for comparing two binomial proportions
Authors: Hirji Karim F. , Tan Shu‐Jane , Elashoff Robert M.
Published: April 2007

The use of the Fisher exact test for comparing two independent binomial proportions has spawned an extensive controversy in the statistical literature. Many critics have faulted this test for being highly conservative. Partly in response to such criticism, some statisticians have suggested the use of a modified, non‐randomized version of this test, namely the mid‐P‐value test. This paper examines the actual type I error rates of this test. For both one‐sided and two‐sided tests, and for a wide range of sample sizes, we show that the actual levels of significance of the mid‐P‐test tend to be closer to the nominal level as compared with various classical tests. The computational effort required for the mid‐P‐test is no more than that needed for the Fisher exact test. Further, the basis for its modification is a natural adjustment for discreteness; thus the test easily generalizes to r × c contingency tables and other discrete data problems.
Adjustment for non‐differential misclassification error in the generalized linear model
Authors: Liu Xinhua , Liang Kung‐Yee
Published: April 2007

It is well known that estimates of association between an outcome variable and a set of categorical covariates, some of which are measured with misclassification, tend to be biased upon application of the usual methods of estimation that ignore the classification error. We propose a method to adjust for misclassification in covariates when one applies the generalized linear model. In the case where one can observe some true covariates only through surrogates, we combine a latent class analysis with the approach to incorporate multiple surrogates into the model. We include discussion on the efficacy of repeated measurements which one can view as a special case of multiple surrogates with identical distribution. We provide two examples to demonstrate the applicability of the method and the efficacy of multiple replicates for a covariate subject to misclassification in a regression framework.
An empirical bayes formulation of cohort models in cancer epidemiology
Authors: Desouza Cynthia M.
Published: April 2007

This paper concerns the incidence rates of malignant skin melanoma for several age‐sex groups and time periods in three geographic regions, uses a method of cohort analysis and employs a two‐stage random effects model. The first stage entails the assumption that the within‐region variation in the frequency of disease incidence for a fixed age‐sex‐cohort group has a Poisson distribution with mean proportional to the population at risk. The second stage, after adjusting for age and sex, entails the assumption that the between‐region geographic variation in the logarithm of the true incidence rate has a prior distribution with parameters estimated by the method of maximum likelihood. After adjusting for age effects, we estimate random geographic‐specific cohort effects for each sex with use of an empirical Bayes method and compare the results with the usual multiplicative Poisson model that assumes fixed geographic‐specific cohort effects for each sex. This comparison shows that the method presented here provides more stable estimates of geographic‐specific cohort effects, and in addition the random effects model describes these data more adequately.
Estimating departure from normality
Authors: Royston Patrick
Published: April 2007

Departure of a sample from a normal distribution should be assessed by a quantity that is meaningful in terms of the data, rather than merely by the P‐value from a test statistic. Indices of departure based on the Shapiro‐Francia W′ and the Shapiro‐Wilk W statistics are derived, and shown to have a natural interpretation in relation to the normal probability plot. A new diagnostic plot is proposed. An example is given which shows the relationship between one of the new indices and errors in calculated reference ranges due to non‐normality of the data.
Estimating kappa from binocular data
Authors: Oden Neal L.
Published: April 2007

A common error in statistical analysis of ophthalmic data is the lack of accounting for the positive correlation generally present between observations made in fellow eyes. The alternative of data analysis from only one eye in each patient may lead to loss of power and unrealistically large confidence intervals. This paper discusses a method to estimate kappa, a measure of agreement between two graders, when both graders rate the same set of pairs of eyes. The method assumes that the true left‐eye and right‐eye kappa values are equal and makes use of the correlated binocular data to estimate confidence intervals for the common kappa. Simulations show that the new estimators are better than the estimator based on only one eye; new confidence intervals had the correct coverage probability, but were usually only about 70 per cent as wide as single‐eye intervals. The general methodology described here applies to analysis of grader agreement in rating other paired body structures.
Contradictory correlations between derived scales
Authors: Thompson M. J. , Hand D. J. , Everitt B. S.
Published: April 2007

In a clinical trial one scale of pain relief is scored backwards relative to another (high on one corresponding to low on the other), with a consequent large negative correlation. But two derived scales of total pain, obtained by multiplying average pain relief on each scale by duration of pain (common to both pain relief measurements) gave an almost zero correlation. This apparent contradiction is explained by the inverse relationship between the pain relief scales and the large differences in duration of pain experienced by the patients.
A comparative phase II clinical trials procedure for choosing the best of three treatments
Authors: Palmer Christopher R.
Published: April 2007

In some clinical trials one can employ adaptive designs advantageously, although in practice such techniques are rarely used, in part due to their inherent complexity. A simple and practicable decision‐theoretic approach for the case of three treatments with binary responses is considered, using equal allocation to remaining treatments and, once eliminated, a treatment cannot be re‐employed. Having specified the overall number of patients treated within and beyond the comparative stages of the trial, the goal is to maximize the expected total number of those successfully treated. Investigation of the method involves a computer program that can handle arbitrarily large numbers of patients. It is shown empirically that the decision procedure behaves only marginally worse than if the truly superior treatment had been known and had been given to all patients. Implementation of the method uses a minimax approach that removes dependence on prior parameters. Primarily an identification procedure, one advantage of this approach over traditional hypothesis testing methods is the potential to detect small improvements in treatment efficacy. The intended application is to assist in treatment selection during phase II trials, especially with rapid responses and when the disease involved is serious enough that design‐motivating ethical considerations become paramount.