bluuebunny/crossref_metadata_2025_split huggingface dataset:
Some statistical issues in HIV vaccine trials
Authors: Rida Wasima N. , Lawrence Dale N. 
Published: April 2007

AbstractEfficacy trials of prophylactic HIV vaccines will be among the most difficult clinical trials ever attempted. Not only will there be challenges with the recruitment and retention of high‐risk uninfected individuals, there will be many statistical challenges to the design, conduct, analysis, and interpretation of these trials. General features of an efficacy trial are described, including choice for the primary endpoint and testing for and estimating vaccine efficacy. Secondary objectives of trials are also discussed. These include determining the correlates of protective immunity, assessing the impact of HIV genetic variation on vaccine efficacy, and using biological markers such as viral load and CD4+ lymphocyte cell count to gain insight on a vaccine's ability to prevent or delay disease. The use of biological markers as surrogates for disease outcome is discussed. Last, trial designs for studying several candidate vaccines or other HIV prevention strategies in a single trial are examined.
A method for evaluating needle exchange programmes
Authors: Kaplan Edward H. 
Published: April 2007

AbstractThis paper details a statistical method for evaluating needle exchange programmes. The approach relies only on needle exchange operations data and the results of HIV tests conducted on needles. We develop statistical models describing the needle infection process and how needle exchange interrupts this process. The method is illustrated using 20 months of data collected in conjunction with the evaluation of New Haven, Connecticut's needle exchange programme, and the results suggest that needle‐borne HIV transmission among participating clients has been reduced by at least 33 per cent.
Mid‐p confidence intervals for the poisson expectation
Authors: Cohen Geoffrey R. , Yang Shu‐Ying 
Published: April 2007

AbstractConventionally a confidence interval (CI) for the standardized mortality ratio is set using the conservative CI for a Poisson expectation, μ. Employing the mid‐P argument we present alternative CIs that are shorter than the conventional ones. The mid‐P intervals do not guarantee the nominal confidence level, but the true coverage probability is only lower than the nominal level for a few short ranges of μ. The implications for mid‐P confidence intervals of various proposed definitions of two‐sided tests for discrete data are discussed.
On prediction of future observation in growth curve model
Authors: Tian Jason J. , Shukla Rakesh , Buncher C. Ralph 
Published: April 2007

AbstractRao proposed and compared several approaches for predicting future observations in a growth curve model. The assessment of associated prediction efficiency for different prediction methods were evaluated by Cross‐Validation Assessment Error (CVAE). He used three data sets, each with a limited number of subjects (13‐27) and also with a limited number of repeated measurements (4‐7) per subject, to illustrate the prediction methods. In the present paper, we applied four of the prediction methods discussed by Rao, on a data set with a relatively large number of subjects (174) and also with a larger number of measurements (21) per subject, using the polynomial function and log‐linear function. We propose to use the restricted cubic spline function as an alternative growth curve model and compare its performance with the polynomial function and log‐linear function. It turns out that, at least for larger data sets such as that used in this paper, the prediction methods perform somewhat better when the growth is described by restricted cubic spline function than when the growth is described by polynomial function and log‐linear function.
Testing for omitted variables and non‐linearity in regression models for longitudinal data
Authors: Palta Mari , Yao Tzy‐Jyun , Velu Raja 
Published: April 2007

AbstractWhen fitting regression models to investigate the relationship between an outcome variable and independent variables of primary interest, there is often concern whether omitted variables or assuming a different functional relationship could have changed the conclusion or interpretation of the results. In longitudinal studies of ageing, the concern with omitted variables is well known in the context of cohort and period effects, which refer to unmeasured variables systematically related to the individual's year of birth and secular trends in outcome, respectively. We present and compare three approaches to detecting omitted confounders and non‐linearity in the random effects model for longitudinal data (Laird and Ware, 1982) with random slope and intercept across individuals. The first approach compares simple unweighted within and between regression coefficients, the second is the Hausman specification test for regression models, and the third approach involves testing directly the significance of functions of individual specific covariate means x̄i, in the random effects regression model. This last approach is motivated by the models that arise when cohort or period effects are ignored. We compare the three approaches, and illustrate their application.
Cox regression analysis of multivariate failure time data: The marginal approach
Authors: Lin D. Y. 
Published: April 2007

AbstractMultivariate failure time data are commonly encountered in scientific investigations because each study subject may experience multiple events or because there exists clustering of subjects such that failure times within the same cluster are correlated. In this paper, I present a general methodology for analysing such data, which is analogous to that of Liang and Zeger for longitudinal data analysis. This approach formulates the marginal distributions of multivariate failure times with the familiar Cox proportional hazards models while leaving the nature of dependence among related failure times completely unspecified. The baseline hazard functions for the marginal models may be identical or different. Simple estimating equations for the regression parameters are developed which yield consistent and asymptotically normal estimators, and robust variance‐covarinace estimators are constructed to account for the intra‐class correlation. Simulation results demonstrate that the large‐sample approximations are adequate for practical use and that ignoring the intra‐class correlation could yield rather misleading variance estimators. The proposed methodology has been fully implemented in a simple computer program which also incorporates several alternative approaches. Detailed illustrations with data from four clinical or epidemiologic studies are provided.
On the development of the medical research council trial of α‐interferon in metastatic renal carcinoma
Authors: Fayers P. M. , Cook P. A. , Machin D. , Donaldson N. , Whitehead J. , Ritchie A. , Oliver R. T. D. , Yuen P. 
Published: April 2007

AbstractThis paper describes the steps taken by the British Medical Research Council (MRC) in developing the MRC RE01 trial, a randomized clinical trial for patients with metastatic renal cancer; we discuss the reasons for adopting a triangular sequential design and the impact that this has upon the monitoring of the trial. It had been suggested to the MRC that a trial of biological agents for metastatic renal carcinoma should be initiated. The Cancer Therapy Committee (CTC) of the MRC, through its associated site specific working parties, is responsible for designing and co‐ordinating randomized trials of alternative treatments in cancer in solid tumours. Since no MRC working party for renal carcinoma existed at that time, development began by the formation of an ad hoc group set up under the auspices of the CTC. They assessed, by means of a postal questionnaire, U.K. interest in the trials of, and modalities utilized for, treatment of renal cancer. The responses focused attention on the important questions to ask and indicated the level of potential collaboration. These responses and related clinical and statistical issues suggested a protocol to compare medroxy‐progesterone acetate (MPA) against α‐interferon (α‐IFN). In view of the special problems of comparing an expensive and potentially toxic therapy with an inexpensive and non‐toxic standard, a sequential design was used rather than a fixed sample size design. Statistical issues raised and solutions provided are described. The method of establishing the trial data monitoring committee and a brief review of mortality from renal carcinoma in England and Wales are also included. The trial opened to patient recruitment on 1 January 1992. The formal statements regarding statistical issues that appear in the formal trial protocol (RE01) are set out in the Appendix.
A step‐down procedure for multiple tests of treatment versus control in each of several groups
Authors: Cheung Siu Hung , Holland Burt 
Published: April 2007

AbstractCheung and Holland extended Dunnett's treatment versus control multiple comparison procedure to the case of several groups. Dunnett and Tamhane provided a step‐down procedure more powerful than that of Dunnett for situations where the researcher's interest is in testing and not in simultaneous confidence interval estimation. In this paper we show how one can use the approach of Dunnett and Tamhane to devise a testing procedure for the multi‐group problem with power greater than that of Cheung and Holland. We illustrate the new procedure with reanalyses of published data from a clinical experiment.
The paired availability design: A proposal for evaluating epidural analgesia during labor
Authors: Baker Stuart G. , Lindeman Karen S. 
Published: April 2007

AbstractThe paired availability design (PAD) can reduce selection bias when it is not possible to randomize subjects. PAD consists of independent pairs of experimental and control groups. Within each pair, the intervention is the availability of treatment not its receipt. In the experimental group, the new treatment is made available to all subjects although some may not receive it. In the control group, the experimental treatment is generally not available to subjects although some may receive it in special circumstances. We present a statistic to test a null hypothesis that the receipt of intervention will increase response by a specified non‐zero amount δ. We propose this design for use in a study of the effect of epidural analgesia on the rate of Caesarean section.
A direct, general approach based on isobolograms for assessing the joint action of drugs in pre‐clinical experiments
Authors: Machado Stella G. , Robinson Gregory A. 
Published: April 2007

AbstractPharmacologists and other biologists frequently use methods based on the interpretation of isobolograms to quantify the extent of synergy or antagonism between drugs used in combination in pre‐clinical studies. Most methods have been unsatisfactory from a statistical viewpoint, many because they have relied solely on visual evaluation, others because the methods have not taken into account the variability of the measurements. We describe a direct approach for quantifying the joint potency of two drugs, a central feature being the use of simple isobole models that lead directly to response surface models for the expected experimental outcomes. The approach is general in the sense that one can use it for discrete or continuous responses, different underlying probability distributions, linear or non‐linear dose‐response functions of the drugs used singly, and a variety of experimental designs. Our approach extends the suggestions made by Hewlett for measuring the joint potency of drugs, and is similar in spirit to the approaches proposed by Greco et al. and Weinstein et al. We describe the analysis of data from an in vitro experiment conducted to evaluate the efficacy of the antiviral drugs AZT and ddI used in combination.
On a model‐based approach to estimating efficacy in clinical trials
Authors: Albert Jeffrey M. , Demets David L. 
Published: April 2007

AbstractTreatment efficacy is of primary importance in phase III clinical trials. Determining the true size of the treatment effect is often complicated by patient non‐compliance with the regimen. This paper examines a model‐based approach in the spirit of Efron and Feldman utilizing drug and placebo compliance information. One of the assumptioqs of this analysis is ‘comparability’ of drug and placebo compliance. Robustness in estimation of subgroup and population treatment effects when this assumption is violated is investigated in a simulation study. We find that even moderate non‐comparability (for example, normalized compliance correlations of 0.4) may produce severely biased estimates. The bias is modulated by the strength of the relationship between compliance and the response on placebo.
The use of a square array scheme in blood testing
Authors: Phatarfod R. M. , Sudbury Aidan 
Published: April 2007

AbstractWhen testing blood samples for the presence of disease, considerable efficiencies may be achieved by pooling samples and testing them as a batch. It is shown that placing the samples in a square array and pooling rows and columns has substantial advantages, particularly in the reduction of false negatives. The commonly used 8 × 12 array is also considered.
Attributable fraction estimates and case definitions for malaria in endemic
Authors: Smith Tom , Schellenberg Joanna Armstrong , Hayes Richard 
Published: April 2007

AbstractAsymptomatic carriage of malaria parasites occurs frequently in endemic areas and the detection of parasites in a blood film from a febrile individual does not necessarily indicate clinical malaria. In areas of low and moderate endemicity the parasite prevalence in fever cases can be compared with that in community controls to estimate the fraction of cases which are attributable to malaria. In areas of very high transmission such estimates of the attributable fraction may be imprecise because very few individuals are without parasites. Furthermore, non‐malarial fevers appear to suppress low levels of parasitaemia resulting in biased estimates of the attributable fraction. Alternative estimation techniques were therefore explored using data collected during 1989‐1991 from a highly endemic area of Tanzania, where over 80 per cent of young children are parasitaemic. Logistic regression methods which model fever risk as a continuous function of parasite density give more precise estimates than simple analyses of parasite prevalence and overcome problems of bias caused by the effects of non‐malarial fevers. Such models can be used to estimate the probability that any individual episode is malaria‐attributable and can be extended to allow for covariates. A case definition for symptomatic malaria that is used widely in endemic areas requires fever together with a parasite density above a specific cutoff. The choice of a cutoff value can be assisted by using the probabilities derived from the logistic model to estimate the sensitivity and specificity of the case definition.
Age‐related reference ranges: Significance tests for models and confidence intervals for centiles
Authors: Wade A. M. , Ades A. E. 
Published: April 2007

AbstractA method of fitting age‐related reference ranges using maximized likelihood is presented. The method is illustrated using CD4 counts of uninfected children born to HIV‐1 infected women. The likelihood incorporates exponential functions to describe the Box‐Cox transformation parameter that induces Normality and the mean and standard deviation of the transformed data, at all ages in the range. This guarantees that the centiles are asymptotic to notional adult values and avoids edge effects. Likelihood ratio tests were used to assess the significance of the model parameters, and profile likelihood confidence intervals were constructed around the fitted centiles. The asymptotes of the resulting CD4 reference range for the childhood dataset were compared with CD4 counts available from a group of uninfected adults. The proposed approach limits the need for arbitrary decisions about grouping of the data, degree of smoothing or choice of model.
Determining the size of a cross‐sectional sample to estimate the age‐specific incidence of an irreversible disease
Authors: Marschner Ian C. 
Published: April 2007

AbstractThe design of a cross‐sectional survey to estimate the age‐specific incidence of an irreversible disease is considered, where the incidence rate is not changing over time and the risk of mortality is not affected by the onset of disease. The sample is assumed to give information on the current age and disease status of individuals, but not on age at onset of the disease. We consider the problem of determining overall sample size in this context, as well as how best to choose the distribution of sampling across various age groups. These issues are considered with the aim of obtaining incidence estimates achieving acceptable levels of precision. The proposed methods are illustrated by measles incidence estimation.
Publications from multicentre clinical trials: Statistical techniques and accessibility to the reader
Authors: Marsh Marta J. , Hawkins Barbara S. 
Published: April 2007

AbstractArticles from multicentre randomized clinical trials were analysed by methods adapted from Emerson and Colditz and Juzych et al. to compare the frequency with which different statistical methods are used by clinical trials investigators with the frequency used by other researchers, and to determine how much statistical knowledge is required to interpret the statistical treatment of data from clinical trials. We observed differences between the frequency of usage of statistical methods and the accessibility of the clinical trials publications and those of all medical research articles published by specific journals. Clinical trials publications are less accessible than others in medical journals to the reader who knows only descriptive statistics, t‐tests, contingency tables, power calculations, and life table methods. Many more statistical methods must be known by a reader to understand fully publications regarding treatment group comparisons for the primary outcomes of interest from clinical trials.
Correspondence analysis applied to grouped cohort data
Authors: Grassi M. , Visentin S. 
Published: April 2007

AbstractIn this paper we investigate application of generalized correspondence analysis (GCA) to model a two‐way table of rates consisting of a cross‐classification of case numerators and person‐time denominators. The GCA reconstitution formula is proposed as a correlation model for analysing these data. This provides two major advantages over the techniques usually applied. The number of interaction parameters to be estimated is reduced, and, moreover, they have useful interpretation; the singular values and the scores are measures of row‐column modification/interaction effects; in addition the scores allow graphical display of these effects. An asymmetrical plot is proposed for optimal representation of interaction parameters as distances. Finally, two examples are presented to illustrate the method of analysing a two‐way table of covariate by exposure and a two‐way table derived from a cross‐classification of two exposure factors.
Penalized likelihood in Cox regression
Authors: Verweij Pierre J. M. , Van Houwelingen Hans C. 
Published: April 2007

AbstractIn a Cox regression model, instability of the estimated regression coefficients can be reduced by maximizing a penalized partial log‐likelihood, where a penalty function of the regression coefficients is substracted from the partial log‐likelihood. In this paper, we choose the optimal weight of the penalty function by maximizing the predictive value of the model, as measured by the crossvalidated partial log‐likelihood. Our methods are illustrated by a study of ovarian cancer survival and by a study of centre effects in kidney graft survival.
Separation of systematic and random differences in ordinal rating scales
Authors: Svensson Elisabeth , Holm Sture 
Published: April 2007

AbstractWe introduce a new statistical method, which separates and measures different types of variability between paired ordered categorical measurements. The key to the separation is a two‐way augmented ranking approach of observations in a contingency table. It means that cases classified in a specific category by one rater will be internally ranked according to the classifications from the other. This enables us to extract the component of interobserver variation which is not systematic. The variance of the rank differences between judgements is a suitable measure of this interrater variability, which we characterize as random. The empirical measure of random interjudge disagreement, which lies between 0 and 1, is called the relative rank variance and is an estimate of a parameter defined on the multinomial probability distribution in the contingency table. The systematic differences are determined by the marginals and described by two empirical measures, relative position and relative concentration; both measures lie between ‐ 1 and 1. Our method is applied to data sets from a reliability study of two clinical rating scales for assessing hydrocephalus and subarachnoid haemorrhage.
Internal pilot studies for estimating sample size
Authors: Birkett Martin A. , Day Simon J. 
Published: April 2007

AbstractWe develop the idea of using data from the first ‘few’ patients entered in a clinical trial to estimate the final trial size needed to have specified power for rejecting H0 in favour of H1 if a real difference exists. When comparing means derived from Normally distributed data, there is no important effect on test size, power or expected trial size, provided that a minimum of about 20 degrees of freedom are used to estimate residual variance. Relative advantages and disadvantages of using larger internal pilot studies are presented. These revolve around crude expectations of the final study size, recruitment rate, duration of follow‐up and practical constraints on the ability to prevent the circulation of unblinded randomization codes to investigators and those involved in editing and checking data.
A critical discussion of intraclass correlation coefficients
Authors: Müller Reinhold , Büttner Petra 
Published: April 2007

AbstractIn general, intraclass correlation coefficients (ICC's) are designed to assess consistency or conformity between two or more quantitative measurements. They are claimed to handle a wide range of problems, including questions of reliability, reproducibility and validity. It is shown that care must be taken in choosing a suitable ICC with respect to the underlying sampling theory. For this purpose a decision tree is developed. It may be used to choose a coefficient which is appropriate for a specific study setting. We demonstrate that different ICC's may result in quite different values for the same data set, even under the same sampling theory. Other general limitations of ICC's are also addressed. Potential alternatives are presented and discussed, and some recommendations are given for the use of an appropriate method.
Growth charts for both cross‐sectional and longitudinal data
Authors: Cole T. J. 
Published: April 2007

AbstractReference centile charts are widely used to monitor child growth, and yet they are often used inappropriately. Charts derived from cross‐sectional data ought not to be used to monitor longitudinal data. Such monitoring is only valid if two distinct sets of centiles are available, one for height distance and one for height velocity. There is also the problem of regression to the mean, in that expected height velocity is negatively correlated with initial height during infancy and puberty, and this requires a regression‐based conditional standard. Furthermore, such conditional standards usually assume that the measurement of interest is normally distributed, which may not be appropriate. The paper describes modifications to the conventional growth chart which address these issues, illustrated using height data from the French Longitudinal Study.