bluuebunny/crossref_metadata_2025_split huggingface dataset:
Some experiments with factors that might affect the response of mothers to a postal questionnaire
Authors: Cartwright Ann 
Published: April 2007

AbstractThe effects of a number of controllable factors on the response rate of mothers to a postal questionnaire were assessed by a series of experiments. In one a factorial design was used to look at seven factors with a random sample of 1600 mothers. The main findings were that the responses to questionnaires of 8,16 or 24 pages were similar, but that rather more mothers replied when the questionnaires contained only factual questions than when they covered both facts and attitudes. Another experiment, based on a similar sample, compared the response rates when the questionnaires were sent out by a government organization or by the Institute for Social Studies in Medical Care, and found no difference. The final experiment looked at the effect of precoding the answers or asking respondents to tick boxes beside their replies and again found no difference in response rates. The overall response rate was 79 per cent, but this varied between 66 and 87 per cent in the ten randomly selected study areas‐a much greater variation than that found with any of the experimental factors.
Sensitivity of Fisher's exact test to minor perturbations in 2 × 2 contingency tables
Authors: Dupont William D. 
Published: April 2007

AbstractThe two tailed Fisher's exact P value is extremely sensitive to small perturbations in 2 × 2 contingency tables. An example indicates that a 1 per cent increase in the denominator of one treatment group results in a 32 per cent drop in the exact P value, but a mere 0.1 per cent decrease in the treatment success rate. This is equivalent to the increase in significance obtained by a 20 per cent increase in the sample size of both treatments without changing the observed success rates. This drop results from small changes in the probabilities of unobserved events. A systematic evaluation of 920 pairs of similar contingency tables shows that these fluctuations occur frequently over a wide range of sample sizes and significance levels. Doubling the one tailed exact P value provides a more consistent measure of inferential strength. We discuss various chi‐squared continuity corrections.
Prognostic factors, models and related statistical problems in the survival of end‐stage renal disease patients on hemodialysis
Authors: Umen Andrew J. , Le Chap T. 
Published: April 2007

AbstractWe investigate factors associated with the survival of end‐stage renal disease patients on hemodialysis. A model derived for non‐diabetics includes five significant prognostic factors: age at initiation of dialysis, arteriosclerotic heart disease, cerebrovascular accident, cancer and chronic obstructive pulmonary disease. For diabetics, age at initiation of dialysis was the only significant prognostic factor.We also show that (i) a simple exponential model adequately represents hemodialysis survival data, (ii) the relationship between age and survival hazard is not log‐linear and (iii) data for diabetics require independent analysis or inclusion of interaction terms. In this paper, we chose the first approach.
Effect of covariate measurement error in randomized clinical trials
Authors: Morgan Timothy M. , Elashoff Robert M. 
Published: April 2007

AbstractPrognostic factors often appear as covariates in clinical trials designed to estimate treatment effects. These factors are usually subject to measurement error and lead to decreased efficiency in the estimation of the treatment effect. We use Weibull regression models and asymptotic theory to derive the efficiency of estimation obtained by adjusting for one dichotomous and one continuous covariate measured with error. An application to a clinical trial involving advanced lung cancer patients illustrates the results.
Small sample behaviour of hypothesis tests related to indirect standardized rates: A Monte Carlo study
Authors: Bean Judy A. , Wiltse Curtis G. , Woolson Robert E. 
Published: April 2007

AbstractDifferent distributions of confounding variables in populations complicate any comparison of the relative frequency of an event. To resolve this, methods for fitting statistical models to tables of rates have recently been developed. One such model is the multiplicative model. We performed a Monte Carlo study of the multiplicative model for a 4 × 3 table of rates. For small samples the likelihood ratio test statistic was conservative for small expected cell counts, liberal for moderate expected counts, and performed well for large expected counts. The weighted least squares test statistic was generally more conservative and less powerful than both the likelihood ratio statistic and the Pearson statistic.
The numerical approach to classification: A medical application to develop a typology for facial pain
Authors: Wastell D. G. , Gray R. 
Published: April 2007

AbstractApplications of numerical taxonomy in medicine are relatively rare. We describe an application in which a new typology is developed for the classification of pain distribution in patients with temporomandibular pain dysfunction syndrome. The methodology of the numerical approach is presented and key issues are highlighted, especially relating to validation of taxonomic structure. From the dendrogram obtained by Ward's hierarchical method, five pain groups are distinguished which relate systematically to anatomy and are clinically meaningful. Cluster structure is subjected to a battery of reproducibility tests and is found to be broadly reproducible for different algorithms and sub‐samples of subjects. Finally, the new typology is shown to have heuristic value in providing fresh insight into the nature of a complex syndrome.
Comparison of quantitative diagnostic tests: Type I error, power, and sample size
Authors: Linnet Kristian 
Published: April 2007

AbstractFor a quantitative laboratory test the 0.975 fractile of the distribution of reference values is commonly used as a discrimination limit, and the sensitivity of the test is the proportion of diseased subjects with values exceeding this limit. A comparison of the estimates of sensitivity between two tests without taking into account the sampling variation of the discrimination limits can increase the type I error to about seven times the nominal value of 0.05. Correct statistical procedures are considered, and the power and required sample size are studied for Gaussian and log‐Gaussian distributions of diagnostic test values. The results may be useful for the planning phase of studies to evaluate quantitative diagnostic tests.
Statistical analysis of heart rates in subsequent victims of sudden infant death syndrome
Authors: Spicer C. C. , Lawrence C. J. , Southall D. P. 
Published: April 2007

AbstractAn analysis was made of heart rate records obtained prospectively from a group of full‐term infants. The group consisted of 16 subsequent victims of sudden infant death syndrome (SIDS) and a set of 49 controls. The power spectra were calculated for each record and this together with the birth weight, gestational age and age at recording provided the basis for a discriminant analysis. The analysis identified a periodicity of 6–8 heart beats, in addition to the known effect of low birth weight, as associated with the risk of SIDS.
On the modelling of human growth
Authors: Karlberg Johan 
Published: April 2007

AbstractA new approach to modelling human linear growth from birth to maturity is presented. The model splits growth into three additive and partly superimposed components, appropriately named infancy, childhood and puberty; we refer to it as the ICP‐model for obvious reasons. A key feature of this model, compared with others, is that the components correspond with known features of the endocrinological regulation of growth and can be considered in isolation from one another.
Bias in indirectly adjusted comparisons due to taking the total study population as the reference group
Authors: Greenland Sander 
Published: April 2007

AbstractIt is well known that comparisons of indirectly adjusted statistics, such as standardized morbidity ratios (SMRs), can be biased when the joint effect of the study exposure and thecovariates is not multiplicative. This paper describes a related bias in SMR comparisons, one that can arise if the total study population is used as the referent. This bias can occur even if the exposure‐covariate effects are multiplicative.
Problems in the medical interpretation of overviews
Authors: Wittes Robert E. 
Published: April 2007

AbstractRecently, investigators have combined formally the results of all available randomized trials testing a particular therapy to get a better estimate of the effectiveness of that treatment than any single trial can provide in isolation. It seems intuitively clear, however, that formal overviews will yield medically meaningful results only under certain defined circumstances. First, the treatments that are pooled should be similar enough that any inferences about the effect of treatment will refer to something more specific than an idealized ‘average therapy’. Second, patient selection in the pooled trials should be uniform enough that the inferences will be applicable to some defined patient population. Third, although the potential biases of excluding trials from pooling are substantial, so are the problems of including trials whose execution might be flawed in a biased manner; it is not clear what can be done about this, since biased studies probably cannot be identified in an unambiguous manner. Finally, it would seem prudent to consider the medical context during which trials were performed; it is probably not reasonable to assume that quantitative measures of treatment effect obtained by pooling studies from different eras of treatment will be an accurate reflection of what current treatment can achieve, even if everything else is held constant. For these reasons the quantitative measures of treatment effect that derive from formal overviews may have little relevance to medical decision‐making. Overviews might still be useful in indicating the general direction of a treatment effect, provided that no qualitative interactions are present. Although such interactions may seem improbable, some recent examples from the cancer literature suggest that their presence cannot be ruled out a priori.
Interpretation of results from subset analyses within overviews of randomized clinical trials
Authors: Gelber Richard D. , Goldhirsch Aron 
Published: April 2007

AbstractEvaluating treatment effects within different subsets of patients is a common practice in the analysis of individual randomized clinical trials. Such analyses are limited, however, by the number of patients available. Overviews, by providing evidence based on large numbers of patients, can be useful for overcoming the difficulties of detecting therapeutic effects within subsets of patients. However, inconsistent subset definitions, misclassification of patients, and incomplete availability of patient subsets from the trials included in the overview bias the estimates of effect size.Separate analyses ofsubsets of studiesare also possible within an overview. Studies being pooled generally differ with respect to treatments applied, control groups, patient eligibility, quality control, study conduct, and follow‐up maturity. Separate comparisons within subsets defined by these features will be misinterpreted unless confounding factors are recognized. Indirect comparisons between overviews have the same informative value as nonrandomized trials with historical controls.
Biases in the assessment of diagnostic tests
Authors: Begg Colin B. 
Published: April 2007

AbstractDiagnostic tests are traditionally characterized by simple measures of efficacy such as the sensitivity and the specificity. These measures, though widely recognized and easy to understand, are subject to definitional arbitrariness. Moreover, studies constructed to estimate the sensitivity and specificity are susceptible to a variety of biases. In this paper the various potential problems are described with reference to examples from the diagnostic literature. These difficulties have implications for the design of diagnostic test evaluations, and the choice of suitable measures of test efficacy.
Models for temporal variation in cancer rates. II: Age–period–cohort models
Authors: Clayton D. , Schifflers E. 
Published: April 2007

AbstractOur first paper reviewed methods for modelling variation in cancer incidence and mortality rates in terms of either period effects or cohort effects in the general multiplicative risk model. There we drew attention to the difficulty of attributing regular trends to either period or cohort influences. In this paper we turn to the more realistic problem in which neither period nor cohort effects alone lead to an adequate description of the data. We describe the age‐period‐cohort model and show how its ambiguities surrounding regular trends ‘intensify’. We recommend methods for presenting the results of analyses based upon this model which minimize the serious risk of misleading implications and critically review previous suggestions. The discussion is illustrated by an analysis of breast cancer mortality in Japan with special reference to the phenomenon of ‘Clemmesen's hook’.
Modelling binary data from a three‐period cross‐over trial
Authors: Jones Byron , Kenward Michael G. 
Published: April 2007

AbstractA new method of analysing binary data from a three‐treatment, three‐period cross‐over trial is described. This method is based on a log‐linear model and mirrors the analysis of continuous data. It is an extension of the method we introduced recently for the analysis of binary data from a two‐treatment, two‐period crossover trial. We illustrate our method using data from a trial which compared two analgesics and a placebo for the relief of primary dysmenorrhea.
Issues of efficiency in combining proportions of deaths from several clinical trials
Authors: Buyse Marc , Ryan Louise M. 
Published: April 2007

AbstractThe Mantel–Haenszel test provides a straightforward method to combine results from several clinical trials when only summary information, such as the proportion of deaths, is available for each trial. More efficient tests, such as the stratified logrank test, should be used if the survival and censoring times are known for all individuals, but in practice, the cost and effort of obtaining this information may be prohibitive. The purpose of this paper is to derive a general expression for the asymptotic relative efficiency (ARE) of the Mantel–Haenszel test with respect to the stratified logrank test, and to compute the ARE in situations which are likely to be of practical interest. The results show that under realistic assumptions about the survival distribution, losses to follow‐up and duration of accrual, the ARE frequently exceeds 80 per cent. An example is given to show the usefulness of the approach when combining proportions of deaths from several cancer clinical trials.
Some considerations in the analysis of rates of change in longitudinal studies
Authors: Palta Mari , Cook Thomas 
Published: April 2007

AbstractThis paper discusses and compares several estimators of mean rate of change in unbalanced longitudinal data based on a model with randomly distributed regression coefficients across individuals. The estimators are unweighted and weighted means of these coefficients. The paper also evaluates commonly used variance estimates corresponding to the estimators. Results show that in situations of very slight imbalance, the choice of method is not critical. When imbalance is substantial, however, one should weight the regression coefficients by their estimated precision. An example using data from a nutritional study on premature neonates illustrates some issues encountered in the analysis of longitudinal clinical data sets.
Non‐random sampling in human genetics: Estimation of familial correlations, model testing, and interpretation
Authors: Chakraborty Ranajit , Hanis Craig L. 
Published: April 2007

AbstractBy choice or necessity, human geneticists and genetic epidemiologists often design studies that involve non‐random sampling of clusters of individuals, and yet address hypotheses appropriate to the population as a whole. Failure to adjust for the non‐randomness of data often leads to biased parameter estimates and misspecification of predictive models that cause familial resemblance of traits. We develop an approach to adjust for common forms of non‐randomness in the context of estimating familial correlation with minimal distributional assumptions and discuss its implications in connection with adjustments for concomitant variables.
Evaluating the efficacy of a combination therapy
Authors: Snapinn Steven M. 
Published: April 2007

AbstractStandard multiple comparison techniques do not adequately address the situation in which one must demonstrate a combination therapy's superiority to both of its components. This paper proposes several alternative tests to deal with this situation, and evaluates the tests with a Monte Carlo sampling experiment that compares the actual with the nominal significance levels of the tests. Data from a clinical trial that compares the efficacy of a combination analgesic/muscle relaxant to its components and placebo in the treatment of low back pain and spasm illustrate the tests.
Effective sample sizes for confidence intervals for survival probabilities
Authors: Dorey Frederick J. , Korn Edward L. 
Published: April 2007

AbstractWe examine various methods to estimate the effective sample size for construction of confidence intervals for survival probabilities. We compare the effective sample sizes of Cutler and Ederer1 and Peto et al.,2 as well as a modified Cutler‐Ederer effective sample size. We investigate the use of these effective sample sizes in the common situation of many censored observations that intervene between the time point of interest and the last death before this time. We note that there is no a priori reason to treat upper and lower confidence intervals in a symmetric fashion since censored survival data are by nature asymmetric. We recommend the use of the Cutler‐Ederer effective sample size in construction of upper confidence intervals and the Peto effective sample size in construction of lower confidence intervals. Two examples with real data demonstrate the differences between confidence intervals formed with different effective sample sizes. This study also illustrates the need for caution in the application of simulation studies to real problems.
Practical aspects in data monitoring: A brief review
Authors: Demets David L. 
Published: April 2007

AbstractMonitoring interim accumulating data in a clinical trial for evidence of therapeutic benefit or toxicity is a frequent policy, usually carried out by an independent scientific committee. Repeated testing at conventional critical values can substantially inflate the type I error rate. To maintain acceptable levels, group sequential and stochastic curtailment have been developed for clinical trials. One should not view such methods as absolute rules, but as useful guides. The decision process to terminate a trial early is complex and necessitates an accounting for many factors. The Beta‐Blocker Heart Attack Trial provides an excellent example of many of these issues.
The impact of heterogeneity on the comparison of survival times
Authors: Schumacher Martin , Olschewski Manfred , Schmoor Claudia 
Published: April 2007

AbstractWe consider several sources of heterogeneity in a clinical trial with patients' survival time as the main response criterion: differences in prognosis which can be attributed to a latent or ignored prognostic factor; differences in treatment efficacy in subgroups of patients, and differences in treatment combinations received by the patients. The impact of these types of heterogeneity on the treatment comparison is studied assuming a proportional hazards model. It is measured by the size and power of the logrank and proportional hazards score tests and by the bias of the estimated treatment effect. We show that heterogeneity can seriously affect the treatment comparison and has to be considered during the planning stage as well as at the analysis of a clinical trial.
A transient state model for analysing ventilatory status in a randomized clinical trial
Authors: Jais Jean‐Philippe , Chastang Claude , Raphael Jean‐Claude 
Published: April 2007

AbstractWe designed a randomized clinical trial to determine the efficacy of plasma exchange in Guillain‐Barré syndrome, an acute neurological disease leading to paralysis in previously healthy subjects. Some patients require temporary mechanical ventilation during the course of the disease. Ventilatory status was analysed using a three‐state model with a transient state defined by use of temporary mechanical ventilation, and the probability of being mechanically ventilated modelled as a function of time since randomization. The plot of this function reflects the effect of plasma exchange on ventilatory status showing that fewer plasma‐exchanged patients than controls required ventilatory assistance and that the duration of assistance was shorter. Similar functions can be used in a more general framework when the response criterion includes a transient state.
Fluoride and dental caries: Two different statistical approaches to the same data source
Authors: Busse H. , Bergmann E. , Bergmann K. 
Published: April 2007

AbstractA recent analysis of data from earlier papers on the relationship between dental caries and drinking water fluoride concentration suggested that the commonly accepted inverse relationship did not exist. Our reanalysis of those data, however, confirms the well‐known association between fluoride concentration and dental caries. It also shows that the contrary result arose misleadingly from three simultaneous methodological errors: use of a unifactorial instead of a multifactorial model; omission of or over‐aggregation of some data, and analysis of homoscedastic probits instead of heteroscedastic counts.
A comparative study of three methods for analysing longitudinal pulmonary function data
Authors: Diem John E. , Liukkonen John R. 
Published: April 2007

AbstractWe compare three methods of longitudinal analysis of pulmonary function data. Our data set is taken from a study of exposure to toluene diisocyanate (TDI) vapours in a new manufacturing plant. The first two methods are a two‐stage weighted regression method and maximum likelihood estimation via the EM algorithm, and these give very similar results. The third method, regression with an autoregressive error structure, was not successfully implemented, and in our view needs better documentation.
Issues in the analysis of repeated categorical outcomes
Authors: Ware James H. , Lipsitz Stuart , Speizer Frank E. 
Published: April 2007

AbstractThis paper discusses statistical methods for the analysis of repeated observations of categorical variables as they might arise in longitudinal studies. Two general types of models are described:marginalmodels that give representations for the marginal distribution of response at each occasion, andtransitionalmodels that give representations for the transition probabilities between outcome states at successive occasions. The conceptual and technical differences are discussed and recent work advancing both approaches is reviewed. The two approaches are illustrated through analysis of repeated observations on interval history of the respiratory symptom ‘persistent wheeze’ in preadolescent children.