bluuebunny/crossref_metadata_2025 huggingface dataset:
Strategies for analysing ecological health data: Models of the biological risk of individuals
Authors: Manton Kenneth G. , Stallard Eric , Riggan Wilson
Published: April 2007

Frequently, the analysis of environmental health hazards using ecological data does not involve explicit recognition of the difficulties in translating health effects expressed in the aggregate to the health risks of individuals. We discuss these difficulties and suggest the need for the appropriate conceptualization of risk mechanisms at the individual level and of the population processes that determine the form in which these risk mechanisms are expressed in aggregate data. To illustrate the implications of these concepts we develop a biologically motivated model of lung cancer risk and apply it to both national and county data. In addition, to measure the total health effects of the long term elevation or depression of lung cancer incidence rates, we calculate prevalence distributions from the time series analysis of incidence patterns in county data.
Detection of minimal epidemics
Authors: Knox E. G. , Lancashire R.
Published: April 2007

Epidemiologists seeking epidemics of events in time, and attempting to distinguish real epidemics from random clusters, need to calculate the random probability ofnor more events occurring within a time window of durationw, and for any position of the window as it scans continuously across the period of observation. Exact algebraic solutions have been proposed by other workers, but, over a wide range of important values, systematic arithmetic evaluation is beyond the capacity of existing computers. This paper proposes an approximate test which is quick and simple and which achieves the same purpose. An example of its application is given.
Reliability of basic cancer patient data
Authors: Feigl Polly , Polissar Lincoln , Lane Warren W. , Guinee Vincent
Published: April 2007

Pooling patient data from multi‐institutional medical chart review occurs commonly in the study of cancer and other diseases. To determine the consistency of reporting among institutions, we presented a test set of 25 standardized medical charts to coders at 18 Comprehensive Cancer Centers and compared their resulting codes. This study measures the reproducibility of coding by different persons, but does not assess the accuracy of the underlying medical record. Among 34 data items, we found high disagreement rates in coding stage of disease (14 per cent) and date of diagnosis (8 per cent). Primary site, histologic type and other key items had good reproducibility (disagreement rates < 5 per cent). A number of minor disagreements indicated that detailed distinctions could not be reliably coded from medical charts.
Neonatal mortality in San Serriffe: A game for teaching survey methods
Authors: Macfarlane S. B. J. , Moody J. B.
Published: April 2007

The San Serriffe Game is a simulated epidemiological research exercise for demonstrating survey methods to medical postgraduates. A computer model has been developed to simulate medical and socio‐economic data relating to births and neonatal deaths on the imaginary island of Lower Caisse, San Serriffe. Participants, working in teams, are asked to investigate the extent and causes of neonatal mortality in Lower Caisse and to make recommendations which will bring about a reduction in the mortality rate. Participants are expected to implement some of the ideas learnt in parallel lecture sessions on the planning, design and analysis of survey work.
The exclusion of patients from a clinical trial
Authors: Donner Allan
Published: April 2007

In designing a clinical trial, the investigator must often decide whether or not to exclude certain patients from randomization. Using Bayesian analysis this paper proposes a criterion for making this decision, based on an extension of Colton's model for the choice between two medical treatments.
Magnitude and likelihood of loss resulting from non‐stratified randomization
Authors: Palta Mari , Amini Saeid B.
Published: April 2007

We investigate the power of detecting treatment differences by the stratified logrank test for balanced samples as compared to samples with unequal allocation to treatments within strata. Given non‐stratified randomization to treatments, we relate power losses to their probability of occurrence. In addition, we evaluate the likelihood of zero cells. For power calculations, we employ an asymptotic formula and complement by Monte Carlo simulations to verify results in small samples. In the cases investigated, our results show that large power losses due to imbalance are relatively unlikely with 2 strata. Small strata, however, involve a non‐negligible probability of wasting all observations because of zero cells or censoring.
The effect of unbalanced randomization on the progressively censored savage test
Authors: Lesser Martin L.
Published: April 2007

Equal allocation of patients to treatment in a randomized clinical trial may have disadvantages ethically if the new treatment is believed to be at least as beneficial as the standard treatment. Others have considered, in a non‐sequential setting, unbalanced randomized designs which allocate fewer patients to the potentially inferior standard treatment. This paper examines unbalanced randomized designs in a sequential comparison of two exponential survival distributions using the progressively censored Savage test. The results reveal no substantial sacrifice in asymptotic power or early stopping properties.
BCG and vole bacillus vaccination in adolescence and mortality from leukaemia
Authors: Sutherland Ian
Published: April 2007

In total, 28 deaths from leukaemia are known to have occurred among the 54,239 participants in the Medical Research Council tuberculosis vaccines trial (initially aged about 14 years), from its beginning in 1950 to the end of 1979. There is evidence that this total is likely to be very nearly complete. During the entire period (average 27.1 years) the leukaemia mortality per million person‐years was 25 in the BCG vaccinated group, 20 in the vole‐bacillus vaccinated group, and 21 in the randomly‐allocated unvaccinated (control) group.

Although there was neither a benefit nor a disadvantage from vaccination over the whole period, detailed figures suggested that there may have been a beneficial effect against leukaemia during the first 15 years after entry (that is between age 15 and 30 years) and a deleterious effect after longer intervals (or above the age of 30 years). Alternatively this swing may simply represent an unusual chance fluctuation.

There has been no sign in recent years of any substantial decrease in leukaemia mortality in England and Wales at ages 15–29 years, although the proportion of children given BCG vaccine at about age 13 years has risen from less than 1 per cent (for the cohort aged 15–19 years in 1951–1955) to more than 70 per cent 25 years later. It has therefore been provisionally concluded that chance is the explanation for the apparent swing from prevention to enhancement, and that BCG vaccination at age 13–14 years in Great Britain does not affect subsequent mortality from leukaemia.
Clinical trials: Some reflections
Authors: Holland Walter W. , Breeze Ellie , Swan Anthony V.
Published: April 2007

The principles and historical development of clinical trials are outlined briefly. Some issues that extend the basic philosophy first put forward by Sir Austin Bradford Hill 40 years ago and that will need consideration in the future application of clinical trials are discussed.
Epidemiology of prenatal infections: An extension of the congenital rubella model
Authors: Knox E. G.
Published: April 2007

The properties of prenatal infections are studied through the development of a theoretical model. The responses of such epidemic systems to natural changes in transmission rates, age at maternity, social stratification, geographical heterogeneity, epidemic instability and the introduction of vaccination, are examined. The effects of age‐at‐vaccination, efficacy of vaccination, wild virus interaction, and vaccine‐immunity decay rates, are also examined in some detail. Several powerful putative influences upon the evolution of prenatally determined infective diseases are identified. They provide scientific tools for detecting processes of this kind.
An analysis of repeated biopsies following cardiac transplantation
Authors: Spiegelhalter D. J. , Stovin P. G. I.
Published: April 2007

Biopsy specimens are taken from the heart at regular intervals during the weeks following cardiac transplantation. Three specimens at most have been taken at each session, and classified by the pathologist on a histological four‐point scale of rejection. Since the rejection reaction in the myocardium is uniform neither in intensity nor distribution, there is often disagreement between the findings from a single session; even after three negative specimens there is some doubt as to whether rejection has taken place. In an attempt to quantify this residual uncertainty, we have adapted a procedure of Dawid and Skene1 for ‘estimating error rates’ when the true state is not known. The model is shown to provide a good explanation of the observed data, and provides guidance on the number of negative specimens required to give a defined level of certainty that rejection is not taking place.
Unbiased assessment of treatment effects on disease recurrence and survival in clinical trials
Authors: Kay Richard , Schumacher Martin
Published: April 2007

Recently there has been considerable discussion concerning the analysis of data and presentation of results from clinical trials in breast cancer. A problem stems from there being several events of interest, notably disease recurrence and death. Current methods based on ‘so‐called’ disease‐free survival are criticized on the grounds that they confuse events, such as disease recurrence and death, in the treatment comparison and consequently could be very misleading. Alternative methods of analysis, based on separate measures of treatment effect are presented and illustrated.
Log‐linear model selection in a rural dental health study
Authors: Oler Jacqueline , Bentley J. Marvin
Published: April 2007

This field study sought to measure the effects of dental delivery and school‐based, dental health education on use of dental health care by children in grades K‐6. We attempted to control for two potential confounding factors by an approximate randomization of children into treatment groups with stratification on grade and initial oral disease levels. A backward elimination log‐linear model selection procedure for the 5‐factor classification permitted tests for higher‐order interaction, namely effect‐modification, confounding and collapsibility. We found that the effect of dental health education on use of dental care depended on the mode of dental delivery.
Bias correction in maximum likelihood logistic regression
Authors: Schaefer Robert L.
Published: April 2007

This paper provides an expression for bias of the maximum likelihood logistic regression estimates for use with small sample sizes. This bias correction is based on an expansion of the maximum likelihood equation. Simulation results show these corrections to be highly effective in small samples.
Between medicine and law
Authors: Finney D. J.
Published: April 2007

A recent experience as an expert witness in a legal action intended to prevent the fluoridation of water supplies has emphasized to me some of the problems of explaining statistical reasoning to persons unfamiliar with the mode of thought. The procedures of cross‐examination are not ideal for clarifying scientific truth, and regrettably the language of statistics offers much scope for misunderstanding when words used technically are read with more colloquial meaning. I illustrate this by discussing the meaning of significance tests and by examples relating to the combination of independent test results, the misunderstanding of independence, covariance analysis, the use of interpolation, the relation between source of data and interpretation, and spurious correlation.
The importance of internal quality control data in national external quality assessment schemes. Plasma progesterone assays
Authors: Kay C. , Kemp K. W. , Nix A. B. J. , Rowlands R. J. , Groom G. V. , Wilson D. W. , Griffiths K.
Published: April 2007

Co‐ordinators of external quality assessment schemes in the U.K. despatch samples of quality control material to participant laboratories at frequent intervals to assess laboratory performance. We show, via a controlled experiment on the plasma progesterone assay, that the current analysis performed by the external assessors is inadequate and often leads to erroneous conclusions about a laboratory's performance. It is concluded that for a proper assessment of a laboratory's performance, the external assessor should prepare large pools of plasma and distribute them to all participants in the scheme to use as internal quality control material.
Are definitive (reference) methods and Shewhart's principle the best approach towards accuracy?
Authors: Leijnse B.
Published: April 2007

The current state of quality control in clinical chemistry cannot be characterized as good; the appropriate description is acceptable. This statement is illustrated by results from quality control programmes. The influence of the matrix in which the analyte is embedded points to serious analytical deficiences in the methods used in clinical chemistry. The abundant application of statistics is criticized and it is argued that such application can be avoided by improving the accuracy and precision of the analytical methods. Difficulty in defining a definitive method results from accuracy and ‘true value’ not being determinate. The approved IFCC definition of the reference method and the connection between this definition and the basis of quality control in clinical chemistry is discussed. The pioneering work of Shewhart on quality control in industry in the 1930s is revealed. It is pointed out that the main principle of this method, a continuous process of tracing and eliminating assignable sources of variation, should be the aim of quality control in clinical chemistry.
Application of cusum techniques to the routine monitoring of analytical performance in clinical laboratories
Authors: Rowlands R. J. , Griffiths K. , Kemp K. W. , Nix A. B. J. , Richards G. , Wilson D. W.
Published: April 2007

Quality control data from a radioimmunoassay of progesterone are analysed. The measurements are found to have a lognormal distribution. A likelihood analysis of the change‐point is described. Some rival continuous inspection schemes are compared and it is pointed out that more efficient schemes than Shewhart's can be implemented in clinical laboratories with the aid of a computer.
A method of analysis of laboratory data in an epidemiological study where time trends are present
Authors: Thompson S. G.
Published: April 2007

Where data are collected over an extended period, in either cross‐sectional or prospective studies, time trends in laboratory measurements can have misleading effects on observed associations, especially where it has not been possible to randomize the order of entry of participants to the study. In an ongoing prospective study of ischaemic heart disease, a modified cusum technique is used to examine the data for time trends. The paper considers a method for estimating where changes may have occurred, a method for adjusting for such changes in investigating the associations between variables and the appropriateness of making such adjustments.
Deficiencies in clinical reports for registration of drugs
Authors: De Jonge H.
Published: April 2007

A considerable number of the clinical reports which are presented to the Dutch Board for the Evaluation of Drugs, have deficiencies and/or shortcomings. A number of these, including loose description of the target population and sampling method, methodological flaws, incorrect treatment of withdrawals, confounding of patients and observations per patient, incomplete or incorrect description of the data and incorrect or inappropriate use of statistical tests, are discussed.
Stopping rules for clinical trials
Authors: Freedman L. S. , Lowe D. , Macaskill P.
Published: April 2007

We describe a new method of formulating stopping rules for clinical trials, one that incorporates opinion on what difference is clinically important. We compare the method with conventional group sequential designs and illustrate it by application to a study of Pancuronium Bromide for prevention of haemorrhage in pre‐term infants.
Critical reflections on clinical trials
Authors: Rümke Chr. L.
Published: April 2007

There is often concern about the large number of patients needed for a particular clinical trial. However, one could be equally concerned that a trial is designed with a number of patients that is too small to obtain a precise enough estimate of the difference between the success rates of the treatments. The design of the trial should ensure that statistical significance is only reached if the treatment difference exceeds a specified value of clinical importance. Designs with this property generally require more than the usual number of patients. It is hoped that discussion on the ethical acceptability of this consequence will be stimulated by this paper.
The performance of logistic discrimination on myocardial infarction data, in comparison with some other discriminant analysis methods
Authors: Schmitz P. I. M. , Habbema J. D. F. , Hermans J.
Published: April 2007

The Imminent Myocardial Infarction study Rotterdam (IMIR), concerns patients who visit their general practitioners and have complaints suspected to be of cardiac origin. The study aims to develop a protocol for diagnosing myocardial infarction without laboratory assistance. We use the IMIR data, consisting of continuous and binary variables, to compare the diagnostic performance of logistic discrimination with some other discriminant analysis techniques. We discuss which characterizations of mixed data sets may give indications for an appropriate choice from among the alternative methods for discrimination.
Evaluation of clinical decision‐aids, with an application to a system for dyspepsia
Authors: Spiegelhalter D. J.
Published: April 2007

The evaluation of clinical decision‐aids is discussed both in general and in the particular case of a microcomputer‐based system designed to help general practitioners in deciding whether to refer patients with dyspepsia for specialist care. Parallels are drawn with the established framework for evaluating a new therapy, including a description of four phases of evaluation and the contrast between pragmatic and explanatory trials. Past studies are reviewed, emphasizing the difficulties of establishing a credible control group, and including some relevant examples from the areas of evaluating new diagnostic technology, medical information systems and audit procedures.
Assessing tumour markers
Authors: Tate Helen
Published: April 2007

This paper explores the factors involved in assessing the value of a medical test in a given clinical situation. It examines the problems involved in designing studies to investigate the role for a tumour marker in differential diagnosis and patient monitoring. An overview is given, including a critical evaluation of the preliminary research, the laboratory assay technique and potential clinical problems. Some examples are given. Specific approaches to the analysis of monitoring data are outlined, including the application of a sequential Bayesian model. This is illustrated using data from patients in the Medical Research Council's series of studies on the tumour marker Carcinoembryonic antigen.
The leicestershire perinatal mortality study: A case study of multi‐group discriminant analysis with complex sampling
Authors: Clayton David G.
Published: April 2007

Case‐control studies are usually analysed by two‐group discriminant analysis or by a related method. However, in case‐control studies of perinatal mortality the cases (perinatal deaths) are far from homogeneous, and it is likely that some risk factors are relevant only to certain subgroups of cases. This paper proposes a seven‐category classification of perinatal deaths and reports an analysis using multi‐group discriminant analysis. The problem is further complicated by non‐random sampling of controls.
Bimodality of blood pressure levels
Authors: McManus I. C.
Published: April 2007

I examine distribution of systolic blood pressure by means of maximum likelihood fitting of various statistical models to the extensive data of Bøe et al., and find evidence for a compound or mixed log‐normal distribution, rather than the single log‐normal distribution proposed by Pickering. I find a second distribution with a mean blood pressure above the ordinary range. I demonstrate further evidence for the existence of this subgroup in the abnormalities of regression to the mean found in the same data set.
Stratified analysis of multivariate clinical data: Application of a mantel‐haenszel approach
Authors: Mantel Nathan , Mocarelli Paolo , Marocchi Alessandro , Brambilla Paolo , Baretta Roberto
Published: April 2007

Laboratory determinations on children aged 6 to 10 years obtained over a 5‐year period are analysed by a method described in detail for differentiating between children from exposed and control areas of Seveso, Italy. In the analysis, stratification is employed to distinguish the separate days of laboratory measurement. The analyses permit the study of differences based on all variables simultaneously as well as on each variable separately. Results are obtained for each individual year and for longer intervals of 2 successive years, 3 successive years, 4 successive years, and all 5 years. The results and some statistical aspects of the analysis are discussed.
The need for randomization in the study of intended effects
Authors: Miettinen Olli S.
Published: April 2007

The need for randomization as a means of controlling confounders is accentuated in the study of intended effects (efficacy) as compared with unintended ones (toxicity). The basic reason is that the indication for intervention is inherently a confounder in the study of efficacy but not of toxicity, whereas contraindications represent only a minor confounder even in toxicity research. Moreover, control of the indication in non‐experimental terms is commonly infeasible owing to the complexity and subtlety of the indication.
Analysis of survival data by the proportional odds model
Authors: Bennett Steve
Published: April 2007

A model is presented for the analysis of lifetime data in which the rates of mortality for separate groups of patients converge with time. A non‐parametric estimate is given for the survivor function. The theoretical basis for the model assumes that prognostic factors have a multiplicative effect on the odds against survival beyond any given time. The model is fitted to data using maximum likelihood estimation, and an example of its use in the analysis of a lung cancer trial is given.
An analysis of survival differences between clinically and screen‐detected cancer patients
Authors: Habbema J. D. F. , Van Oortmarssen G. J. , Van Putten D. J.
Published: April 2007

Survival differences between clinically and screen‐detected cancer patients partly result from biases. Well known are lead‐time, length bias and overdiagnosis.

The survival of the clinically detected patients in the study group of the HIP breast cancer screening project is corrected for these biases. The resulting survival curve is only slightly worse than the survival of the screen‐detected patients. This suggests a very modest mortality reduction by screening.

A much larger reduction is obtained from an analysis of the complete HIP results, including those of the control group.

It is concluded that a large unexpected selection bias is present. This bias would not have been detected if the HIP study had not contained a randomized control group. A misleading and pessimistic conclusion on the effectiveness of breast cancer screening would thus have resulted. This conclusion reinforces the need for randomized studies.
Fitting regression models to censored survival data
Authors: Hudec M. , Platz H.
Published: April 2007

A short review of regression models for the analysis of censored survival data is given. These include multiplicative hazard rate models, log‐linear models (accelerated failure time models), linear models and polynomial models. An application of some of these models to the analysis of a large retrospective study on carcinomas of the oral cavity is described. The results obtained by parametric and semiparametric analyses are compared.
Prognostic factors and risk groups: Some results given by using an algorithm suitable for censored survival data
Authors: Marubini E. , Morabito A. , Valsecchi M. G.
Published: April 2007

The problem of identifying the role of various prognostic factors when the response variable is the patient's survival time is discussed. Morgan and Sonquist's approach1of constructing groups at similar risk is useful and an algorithm which implements the method for survival time data with censored observations is described. Examples of its application to two sets of medical data are given, arising from studies of prognosis following renal transplantation and treatment for stage I malignant melanoma of the skin.
Statistical consulting in clinical research: The two‐way street
Authors: Moses Lincoln , Louis Thomas A.
Published: April 2007

Clinical research often rests on statistical interpretation of numerical data. Thus, effective collaboration between clinician and statistician can have central importance. Interaction in the planning phases of a project can identify tractable scientific and statistical problems that will need attention and can help avoid intractable ones. The central need is for clear, broad, specific two‐way communication on scientific issues and research roles.
A comparison of standardized and proportional mortality ratios
Authors: Roman Eve , Beral Valerie , Inskip Hazel , McDowall Michael , Adelstein Abe
Published: April 2007

Proportional mortality analyses are traditionally considered to be unreliable because they lack information on persons at risk. Standardized mortality ratios (SMRs) are often used in preference to proportional mortality ratios (PMRs) even when the denominator or numerator of rates is known to be biased. Examination of data from 30 randomly selected occupational units described by the U.K. Office of Population Censuses and Surveys (OPCS) revealed, however, that age‐standardized cause‐specific SMRs and PMRs have an almost constant relationship: the ratio of the cause‐specific SMR to the cause‐specific PMR closely approximating the all‐cause SMR of the group under consideration. Hence, a PMR above 100 almost always indicates that the corresponding cause‐specific SMR is greater than the all‐cause SMR (and vice versa). Furthermore, approximately 70 per cent of conditions with significantly high PMRs above 200 have corresponding SMRs which are also significantly high. When cautiously interpreted, the PMR may, therefore, be a useful indicator of an increased frequency of disease in a particular occupational or other group.
Case definition and power in case‐control studies
Authors: Rosenbaum Paul R.
Published: April 2007

A narrow case definition can lead to greater in clarity in case‐control studies, but it can also lead to either a gain or a loss in the power of statistical tests. Under plausible assumptions, the loss of power can be in excess of 30 per cent, and the gain can be in excess of 50 per cent. If at least one third of the total study size consists of narrowly defined cases, the loss of power will often be negligible, whereas the gain can be substantial.
A non‐parametric graphical representation of the relationship between survival and the occurrence of an event: Application to responder versus non‐responder bias
Authors: Simon Richard , Makuch Robert W.
Published: April 2007

Reports of cancer clinical trials often attempt to evaluate whether tumour response is associated with prolonged survival. Proper analysis requires accounting for the time‐dependent nature of response status. We review a valid and relatively simple method of significance testing for this problem, and develop a corresponding non‐parametric method for displaying the association between survival and occurrence of response. The new method applies to many other clinical problems involving representation and the association between survival and the occurrence of an event. We illustrate the method with data from two clinical trials.
Clinical trials designed to evaluate therapeutic preferences
Authors: Baskerville J. C. , Toogood J. H. , Mazza J. , Jennings Barbara
Published: April 2007

We present an experimental design for the evaluation of therapeutic preferences among well established similar modes of therapy. The measure of the degree of preference is based on clinical decisions to continue or discontinue the current treatment at each patient visit. Such a trial simulates decision‐making in ordinary clinical practice, while adhering to the scientific principles of experimental design, and it alleviates some of the ethical problems inherent in randomized allocation of a treatment for a period of fixed length in conventional controlled trials. We discuss the design and methods of analysis and illustrate their application with data from a trial comparing three alternative drug treatments for chronic asthma.

Such clinical trials provide a mechanism for examining concordance between the relative efficacy of treatments predicted from conventional controlled clinical trials and their ultimate performance in ordinary clinical practice, expressed in terms of therapeutic preferences.
Analysis of linkage and association for diseases of genetic aetiology
Authors: Sturt Elizabeth
Published: April 2007

This presentation attempts to clarify certain caveats that apply to the use of linkage analysis when the genetics of one of the characters is not completely known. The effects of linkage and association can be difficult to distinguish both within pedigrees and across the general population. Linkage analysis methods are not robust to departures from the assumptions of the model. These assumptions do not allow for the possibility that association may be present which is due to both genetic systems having an effect on one of the phenotypes. Analysis directed towards detecting the presence of such association may be affected by stratification when unrelated individuals are analysed and is confounded by linkage if this is present when related individuals are analysed. Testing for and estimating linkage simultaneously with association using whole pedigree data is advocated and an outline of the required approach is given.
An application of kappa‐type analyses to interobserver variation in classifying chest radiographs for pneumoconiosis
Authors: Musch David C. , Landis J. Richard , Higgins Ian T. T. , Gilson John C. , Jones Robert N.
Published: April 2007

We investigated interobserver variation between three physician readers in the independent classification of chest radiographs from 1771 taconite workers for pneumoconiosis. We analysed variation with a general methodology for the analysis of categorical data, and quantified interobserver agreement in terms of kappatype statistics. The results revealed considerable variation in the profusion of opacities reported by each observer. This was especially so for the earliest radiographic changes, but variation also occurred with the small number of films in the series showing category 2 pneumoconiosis or over. Variation in the classification of profusion of small opacities was greater in films of poor quality, and also increased with the length of time between taking and reading the film (film age). We could not account for the effect of film age by controlling for film quality, as subjectively assessed by the readers.
The choice between analysis of variance and analysis of covariance with special reference to the analysis of organ weights in toxicology studies
Authors: Shirley Eryl A. C. , Newnham Peter
Published: April 2007

The problem of when to include a covariate in the analysis of variance is considered in the special case of organ weight analysis in animal toxicology studies. The covariate is bodyweight prior to death, which may be subject to treatment effects. A simulation study is carried out to compare four rules for deciding whether or not to include the covariate. It is concluded that if there is background information which shows a linear relationship between variate and covariate it is advisable to adjust for the covariate, however weak the relationship may appear to be on the current set of data. Alternative procedures lead to unacceptably high Type I error rates.
Bias in methods for deriving standardized morbidity ratio and attributable fraction estimates
Authors: Greenland Sander
Published: April 2007

This paper examines several methods for deriving standardized morbidity ratios (SMR) and attributable fraction (attributable risk percentage) estimates. We show that some of the proposed methods will, in general, produce biased estimators, although the low variance of certain estimators sometimes compensates for their bias. A few methods are based on statistical fallacies and should be avoided, especially the method of deriving the expected number of cases from a regression equation that does not include the exposure under study.
Survivorship analysis when cure is a possibility: A monte carlo study
Authors: Goldman Anne I.
Published: April 2007

Parametric survivorship analyses of clinical trial commonly involves the assumption of a hazard function constant with time. When the empirical curve obviously levels off, one can modify the hazard function model by use of a Gompertz or Weibull distribution with hazard decreasing over time. Some cancer treatments are thought to cure some patients within a short time of initiation. Then, instead of all patients having the same hazard, decreasing over time, a biologically more appropriate model assumes that an unknown proportion (1 ‐ π) have constant high risk whereas the remaining propotion (π) have essentially no risk. This paper discusses the maximum likelihood estimation of π and the power curves of the likelihood ratio test. Monte Carlo studies provide results for a variety of simulated trials; empirical data illustrate the methods.
An analysis of resistance times to infection under treatment
Authors: Kimber Hilary , Crowder Martin
Published: April 2007

A general model is proposed for the time taken by a subject to catch an infectious disease when there may be treatment intervention during the exposure time. Particular specifications are then made in order to apply the model to some recent data on the infectivity of whooping cough within the family.
The analysis of repeated measures designs in medical research
Authors: Keselman H. J. , Keselman Joanne C.
Published: April 2007

Medical researchers can employ repeated measures designs to study the effects of a treatment over time or when each subject receives all treatments. Univariate F tests and multiple comparison procedures for comparing means constitute the methods to test for the presence of treatment effects. For validity, however, these tests must satisfy the sphericity assumption. To circumvent the biasing effects of non‐sphericity, this paper shows the applicability of the Greenhouse and Geisser three stage approach for univariate omnibus hypothesis testing in repeated measures designs containing any number of repeated factors. In addition, we present a multiple comparison procedure which provides a valid or robust test and thus controls the overall probability of a Type I error.
Allocation of treatment to patients when not all balancing factors are known to the co‐ordinating centre
Authors: Van Lier Henk J. J. , Van Elteren Philip , Hoitsma Andries J. , Koene Robert A. P.
Published: April 2007

The allocation of treatment to patients in a clinical trial while balancing for prognostic factors is usually done by a co‐ordinating centre when all the factors are known. In a trial comparing two treatments of acute rejection of renal allografts some prognostic factors become available to the physician only at the moment of the diagnosis of the rejection. This diagnosis is often made out of office hours, whereas immediate start of treatment is essential. It is shown here that the co‐ordinating centre is still able to control the allocation of patients to treatment groups if a small number of prognostic factors is known only to the physician.
Medical registers as historical controls: Analysis of an open clinical trial of inosiplex in subacute sclerosing panencephalitis
Authors: Hoehler Fred K. , Mantel Nathan , Gehan Edmund , Kahana Esther , Alter Milton
Published: April 2007

Clinical trials of treatments for rare or fatal diseases must often use historical rather than randomized concurrent controls. Randomized trials may not be possible if (1) the number of patients available is quite small, (2) ethical considerations discourage the assignment of patients to control treatments known to be ineffective or (3) some evidence suggests that the proposed new treatment is substantially more effective than the control. We suggest that, when randomization is not feasible, adequately maintained medical registers can serve as a source of control patients. Investigators must pay careful attention to prognostic factors that might bias the results. However, statistical techniques for controlling such bias exist and, if these are properly employed, registry‐derived historical controls can be used to evaluate the effectiveness of treatment.
Automatic classification of biomedical information when classification error is unknown
Authors: Stoddard Anne M.
Published: April 2007

This paper describes a distribution‐free method for the automatic classification of individuals by phenotype of the serum protein α1‐antitrypsin. This method achieved 74 per cent agreement and a Kappa value of 0.24 when compared to the conventional classification procedure on an independent testing sample. The methodology is appropriate for many classification problems, particularly when the true classes and the reliability of the conventional procedure are unknown.
A comparison of chi‐square partitioning and two logit analyses of ordinal pain data from a pharmaceutical study
Authors: Cox Christopher , Chuang Christy
Published: April 2007

We study three approaches for the analysis of ordinal pain data. The first is essentially non‐parametric, based on partitioning the goodness‐of‐fit statistic for testing the homogeneity model. The other two involve the modelling of quite different logit functions of the multinomial probabilities. We discuss and compare the characteristics of these three approaches using actual data from an analgesic trial.
An application of ridge regression analysis in the study of syphilis data
Authors: Hadgu Alula
Published: April 2007

We provide a brief summary of the theory of ridge regression, regress reported rates of congenital syphilis on three stages of adult syphilis using both ridge regression and least squares techniques, and discuss the results. We also develop a principal components regression model for the same example and compare the results.

The example demonstrates the usefulness of ridge regression to handle multicollinearity in data. Problems of overestimation and instability associated with ordinary least squares estimates of these non‐orthogonal data diminish with use of the ridge regression techniques.
Tying clinical research to patient care by use of an observational database
Authors: Hlatky Mark A. , Lee Kerry L. , Harrell Frank E. , Califf Robert M. , Pryor David B. , Mark Daniel B. , Rosati Robert A.
Published: April 2007

The proposition that some inherent logical incompetence attaches to an inference based on observational, as distinguished from experimental, evidence seems to have little to commend it beyond the great positiveness with which it is sometimes asserted.
A community trial strategy for evaluating treatment for symptomatic conditions
Authors: Charlton J. R. H. , D'souza M. F. , Tooley M. , Silver R.
Published: April 2007

A method has been developed for simultaneously comparing the usefulness of many treatments of established value for symptomatic medical conditions. Medical assessment of outcome is not employed. Instead patients are required to assess treatments prescribed during the course of ordinary general practice rather than under the strictly controlled settings of most clinical trials. Outcome incorporates patient compliance and treatment acceptability and is based on patients' subjective judgements of the usefulness of randomly allocated treatments as recorded in self‐completed diaries, which are mailed directly to a trial centre. Thus large and more representative samples are achieved through minimizing the efforts required, both of participating doctors and of patients. Although the approach was originally developed and tested for the comparison of hay fever treatment regimens, we believe that it can be adapted to compare many other treatments where patient‐reported symptoms validly describe the outcome of interest. The feasibility of the approach was tested in two pilot studies, and it has been employed successfully in a two‐year trial comparing seven hay fever treatments. Aspects of analysing such trials are discussed.
Dynamic evaluation of short‐term prognosis after myocardial infarction
Authors: Hougaard Philip , Madsen Erling Birk
Published: April 2007

The risk of cardiac arrest, cardiogenic shock or death in the first 44 days after myocardial infarction is evaluated using a version of the Cox regression model. The (time‐dependent) covariates include complications that have occurred, making it possible to give an individual assessment of prognosis that can be updated each day.

Low risk patients can be discharged from hospital after a few days, whereas high risk patients must remain in hospital until their risk has fallen to an acceptable level. For the former group of patients it is possible to reduce the number of days in hospital without increased mortality and for the latter group mortality can be reduced by longer hospitalization.
The bootstrap and identification of prognostic factors via cox's proportional hazards regression model
Authors: Chen Chen‐Hsin , George Stephen L.
Published: April 2007

This paper describes the use of the bootstrap,1,2a new computer‐based statistical methodology, to help validate a regression model resulting from the fitting of Cox's proportional hazards model3to a set of censored survival data. As an example, we define a prognostic model for outcome in childhood acute lymphocytic leukemia with the Cox model and use of a training set of 224 patients. To validate the accuracy of the model, we use a bootstrap resampling technique to mimic the population under study in two stages. First, we select the important prognostic factors via a stepwise regression procedure with 100 bootstrap samples. Secondly we estimate the corresponding regression parameters for these important factors with 400 bootstrap samples. The bootstrap result suggests that the model constructed from the training set is reasonable.
The effect of validation group bias on screening tests for coronary artery disease
Authors: Green Manfred S.
Published: April 2007

The exercise electrocardiogram (ECG) is frequently used as a screening tool for coronary artery disease (CAD) in epidemiological studies and routine health evaluation. Estimates of the validity of this diagnostic test have usually been obtained by correlating the exercise ECG with the results of coronary angiography. However, coronary angiography is usually performed only on selected individuals with symptomatic CAD. If symptomatic subjects are more likely to respond positively to the exercise ECG than asymptomatic individuals with comparable severity of disease, then biased estimates of the test validity for an unselected population may be obtained. In this paper the validation group bias is shown to be a function both of the proportion of the population with symptomatic CAD and of the relative validity of the test for the symptomatic and asymptomatic subjects. The extent of this bias is examined.
A wilcoxon‐type test for trend
Authors: Cuzick Jack
Published: April 2007

An extension of the Wilcoxon rank‐sum test is developed to handle the situation in which a variable is measured for individuals in three or more (ordered) groups and a non‐parametric test for trend across these groups is desired. The uses of the test are illustrated by two examples from cancer research.
The analysis of neuronal discharge sequences: Change‐point estimation and comparison of variances
Authors: Commenges Daniel , Seal John
Published: April 2007

A key problem in neurophysiology is to determine whether, after presentation of a stimulus, there has been a modification in the discharge of a recorded neuron and if so, an attempt is made to estimate the latency of the response. The estimation problem can be considered as that of the estimation of a change‐point in a sequence of random variables. The gamma distribution is adequate to model the distribution of intervals between action potentials for different types of neurons. Simulations show that the maximum likelihood estimator based on this model is efficient and robust.

An additional problem, in the case of experiments in which a movement follows the stimulus, is to determine whether a response is related to the stimulus or to the movement. A test based on the comparison of marginal scales of a bivariate distribution is proposed. The whole procedure has been tested in simulation and with real examples.
The 2 × 2 factorial design: Its application to a randomized trial of aspirin and U.S. physicians
Authors: Stampfer Meir J. , Buring Julie E. , Willett Walter , Rosner Bernard , Eberlein Kimberly , Hennekens Charles H.
Published: April 2007

The 2 × 2 factorial design calls for randomizing each participant to treatment A or B to address one question and further assignment at random within each group to treatment C or D to examine a second issue, permitting the simultaneous test of two different hypotheses. This design can increase the efficiency of large‐scale clinical trials. The Physicians' Health Study, a randomized trial of aspirin and beta‐carotene among U.S. physicians, illustrates some features and potential problems in the design and analysis of a factorial trial. The most common concern, interaction between treatments, is generally an advantage rather than a limitation of this design. Although such interactions are relatively uncommon, this design provides a means to measure an effect which otherwise might not be apparent. If the interaction is sufficiently severe, however, then loss of power is possible.
Power, sample size and smallest detectable effect determination for multivariate studies
Authors: Greenland Sander
Published: April 2007

This paper discusses some general methods for determining approximate power, sample size, and smallest detectable effect for studies of multiple risk factors. These methods are based on standard large‐sample formulae for determining the power of chi‐square tests, and emphasis is given to determinations for Pearson χ2 tests in multiway contingency tables. The methods are illustrated in application to the design of a clinical trial of the preventive effect of α‐tocopherol, ascorbic acid and β‐carotene on colon polyp recurrence, and a case‐control study of the joint effect of smoking and asbestos exposure on lung cancer incidence.
Models and the use of signed rank tests
Authors: Maritz J. S.
Published: April 2007

Rank tests are often used to analyse medical and biological data. The lack of invariance of the paired sample Wilcoxon signed rank test with respect to transformation of observations, and the choice of an appropriate rank test in the case of the two way analysis of variance random effects model, are discussed in the context of two medical examples.