bluuebunny/crossref_metadata_2025_split huggingface dataset:
The use of cusums and other techniques in modelling continuous covariates in logistic regression
Authors: Royston Patrick 
Published: April 2007

AbstractThe assessment of continuous covariates singly as possible predictors in a multivariable logistic regression model is an important first step in the analysis. An approach to plotting which uses a cusum (cumulative sum) of the binary response variable is described. Extreme‐deviation statistics associated with the cusum may be used to detect monotonic and non‐monotonic trends. Probability plots of the covariate in the two groups defined by the response variable may help to determine the appropriate scale (transformation) of the covariate and to anticipate possible problems with the logistic fit. The ratio of the variances in the response/non‐response groups is informative about the need for a quadratic term in the logistic model. Smoothed scatterplots of the response are valuable in displaying the observed and fitted values. The techniques are illustrated with two data sets.
Morphology of the normal visual field in a population‐based random sample: Principal components analysis
Authors: Oden Neal 
Published: April 2007

AbstractI applied principal components analysis to Humphrey central 24‐2 threshold values from both eyes of 304 clinically normal persons selected by simple random sample from Barbados, WI. The first component, accounting for 62 per cent of the variation, is equivalent to the average threshold value within persons. The first eigenvector, when represented by grey scale maps depicting a pair of eyes, reveals that, as average threshold increases, the visual field rises and flattens, like an umbrella that, initially closed, is simultaneously opened and thrust upwards. I verify three numerical predictions based upon this umbrella description. Much less important sources of variation involve disparity between fellow eyes, and hemimeridional and other symmetric differences within eyes. I discuss briefly possible physiologic explanatory mechanisms.
A model for estimating level and net severity of spinal cord injuries
Authors: Holford Theodore R. , Bracken Michael B. 
Published: April 2007

AbstractObjective and detailed neurological assessments are essential in studies of the treatment and the epidemiology of acute spinal cord injuries. In practice, investigators use the expanded score, found by taking the total of the individual determinations, but this summary obscures important detail as to the level and the overall severity of injury. To address this issue, we present a method for estimating level and net severity of injury that makes use of isotonic regression and the Spearman‐Kärber estimator. We describe the method for both sensory and motor assessments of neurologic function. In the special case where one gives an identical weight to the response at each level, these estimators algebraically partition the expanded score into separate contributions due to level and net severity. We provide a numerical example using data from the first National Acute Spinal Cord Injury Study, and we present a summary of the distribution of these parameters for this population.
Childhood blood pressure tracking correlations corrected for within‐person variability
Authors: Gillman Matthew W. , Cook Nancy R. , Rosner Bernard , Beckett Laurel A. , Evans Denis A. , Keough Mary Ellen , Taylor James O. , Hennekens Charles H. 
Published: April 2007

AbstractThe correlation coefficient between initial and subsequent blood pressure (BP) measurements is referred to as the tracking correlation. Childhood BP tracking correlations, although positive, have been considered too low to make accurate predictions for an individual. These correlations, however, can be raised substantially by averaging BP over multiple weekly visits in each year, which partially accounts for withinperson variability.In a cohort of 333 school children, we measured BP 3 times on each of 4 successive weekly visits, in each of 4 consecutive years, using a random‐zero sphygmomanometer. Approximately 90 per cent of subjects had data for one or more follow‐up years, and 75 per cent of subjects who entered in the first year had data for all four years.With a model that allows estimation of correlations and that uses all available longitudinal data, we calculated tracking correlations completely corrected for within‐person variability, the statistical equivalent of measuring BP on an infinite number (∞) of visits and measurements per visit. Age‐sex adjusted tracking correlations for 3 years of follow‐up based on the means from 1, 2, 3, 4, and ∞ visits are, for systolic BP, 0.43, 0.56, 0.62, 0.66, and 0.73, respectively, and for diastolic BP, 0.20, 0.37, 0.46, 0.50, and 0.70, respectively. With longer follow‐up, the use of corrected tracking correlations would allow determination of the maximal extent to which childhood BP can predict adult levels, and therefore the usefulness of screening to identify children at high risk of developing hypertension.
Digit preference in estimated gestational age
Authors: Pickering R. M. 
Published: April 2007

AbstractA digit preference model is developed to describe the preference for estimating gestational age at birth as an even week during the 20th to 36th week of gestation. The model incorporates a probability of misclassification to adjacent even weeks at odd gestational ages, while even gestational ages are assumed correctly classified. The model is extended to allow the misclassification probabilities to decrease linearly with week during the period. A piecewise exponential model is used to model relative risks of delivery associated with a previous spontaneous abortion and a model incorporating digit preference is fitted as a generalized bilinear model in GLIM. The estimates of relative risk in the underlying survival model are virtually the same whether the misclassification is incorporated in the model or ignored.
Power and sample size evaluation for the mcnemar test with application to matched case‐control studies
Authors: Lachin John M. 
Published: April 2007

AbstractVarious expressions have appeared for sample size calculation based on the power function of McNemar's test for paired or matched proportions, especially with reference to a matched case‐control study. These differ principally with respect to the expression for the variance of the statistic under the alternative hypothesis. In addition to the conditional power function, I identify and compare four distinct unconditional expressions. I show that the unconditional calculation of Schlesselman for the matched case‐control study can be expressed as a first‐order unconditional calculation as described by Miettinen. Corrections to Schlesselman's unconditional expression presented by Fleiss and Levin and by Dupont, which use different models to describe exposure association among matched cases and controls, are also equivalent to a first‐order unconditional calculation. I present a simplification of these corrections that directly provides the underlying table of cell probabilities, from which one can perform any of the alternative sample size calculations. Also, I compare the four unconditional sample size expressions relative to the exact power function. The conclusion is that Miettinen's first‐order expression tends to underestimate sample size, while his second‐order expression is usually fairly accurate, though possibly slightly anti‐conservative. A multinomial‐based expression presented by Connor, among others, is also fairly accurate and is usually slightly conservative. Finally, a local unconditional expression of Mitra, among others, tends to be excessively conservative.
Computational aspects of analysing random effects/longitudinal models
Authors: Rubin Donald B. 
Published: April 2007

AbstractRandom effects and longitudinal models are becoming increasingly popular in the analysis of many types of data, including medical and biopharmaceutical, because of their richness and flexibility. They can be, however, difficult to fit using traditional statistical tools. Fortunately, there now exists a burgeoning collection of newer computational methods that can be applied to draw inferences with such models. This review attempts to provide an introduction to some of these techniques by describing them as extensions of the EM algorithm, currently a standard tool for the analysis of longitudinal and random effects models. For clarity of exposition, the extensions are classified into three types: large‐sample iterative; large‐sample simulation, and small‐sample simulation.
Intentionally incomplete longitudinal designs: I. Methodology and comparison of some full span designs
Authors: Helms Ronald W. 
Published: April 2007

AbstractLongitudinal designs are important in medical research and in many other disciplines. Complete longitudinal studies, in which each subject is evaluated at each measurement occasion, are often very expensive and motivate a search for more efficient designs. Recently developed statistical methods foster the use of intentionally incomplete longitudinal designs that have the potential to be more efficient than complete designs. Mixed models provide appropriate data analysis tools. Fixed effect hypotheses can be tested via a recently developed test statistic, FH. An accurate approximation of the statistic's small sample non‐central distribution makes power computations feasible. After reviewing some longitudinal design terminology and mixed model notation, this paper summarizes the computation of FH and approximate power from its non‐central distribution. These methods are applied to obtain a large number of intentionally incomplete full‐span designs that are more powerful and/or less costly alternatives to a complete design. The source of the greater efficiency of incomplete designs and potential fragility of incomplete designs to randomly missing data are discussed.
Statistical handling of drop‐outs in longitudinal clinical trials
Authors: Heyting A. , Tolboom J. T. B. M. , Essers J. G. A. 
Published: April 2007

AbstractThis paper considers the statistical complexities that arise due to outcome related drop‐outs in longitudinal clinical trials of the randomized parallel groups design with fixed assessment times and an explanatory aim. The shortcomings of currently popular methods of coping with the problem of drop‐outs are discussed. It is proposed that progress can be made by applying the modern methodology that was primarily developed for sample surveys with non‐response and for observational studies. A practical application using the Hamilton Rating Scale for Depression is presented.
Using toxicity grades in the design and analysis of cancer phase i clinical trials
Authors: Gordon N. H. , Willson J. K. V. 
Published: April 2007

AbstractEthical considerations in a cancer phase I trial require a design allowing determination of the maximum tolerated dose with a minimum number of patients treated at low ineffectual or high overly toxic doses. It would also be advantageous to complete the phase I trial in as short a period of time and with as few patients as possible to allow further resources for later studies in which patients are treated at the optimal dose. Several dose escalation schemes are compared. These are the Fibonacci, two two‐stage schemes, and a proposed scheme which uses knowledge of all toxicity grades. Estimates of the maximum tolerated dose are obtained and compared using the dose escalation schemes alone, a logit model, and a proposed mean response model. Confidence intervals using the delta method are obtained from the logit and mean response models. The proposed scheme and the two‐stage schemes have the advantage of requiring fewer patients, particularly at low doses. Confidence intervals obtained from the mean response model have better coverage than those from the logit model. Data from a cancer phase I trial of dipyridamole and acivicin is presented to illustrate the methods.
Comparison of adjusted attributable risk estimators
Authors: Gefeller Olaf 
Published: April 2007

AbstractThe estimation of attributable risk in the presence of confounding and effect modification is studied in this paper. Different adjustment methods for the attributable risk are reviewed. The results of a simulation study comparing these methods under the unrestricted multinomial sampling model are reported. From the study it is concluded that the maximum likelihood estimator resulting from the ‘case load weighting’ of the stratum‐specific attributable risk estimates will be the best overall choice in all practical situations with relatively large sample sizes. Other adjusted attributable risk estimators depend heavily on the underlying structure of the multinomial model.
A latent class model for repeated measurements experiments
Authors: Skene A. M. , White S. A. 
Published: April 2007

AbstractStandard models for the analysis of repeated measurements assume a common response profile for all experimental units within a treatment group. However, in many applications this under‐represents the nature of the response. There may be several distinct modes of response within a group (for example, responders versus non‐responders to a given treatment), or there may be a set of distinct response profiles which are common to all the treatment groups. In these situations the effect of treatment can be characterized both by the shape of the fitted profiles and by estimating the proportion of cases who exhibit each particular response profile. This paper describes how such experiments may be analysed through the introduction of a latent variable into the standard model. Maximum likelihood estimation is straight‐forward using the EM algorithm. Model choice requires some care, but good‐fitting models can be identified via inspection of residuals and the use of empirical semi‐variogram plots. Once the number of distinct profiles has been determined, treatment effects can be investigated using likelihood‐ratio statistics. The approach is illustrated with a re‐analysis of a dataset first described by Grizzle and Allen.
Analysis of factors influencing the efficacy of pooled platelet transfusions
Authors: Matthews Jane P. , Yuen Kally 
Published: April 2007

AbstractThe results of 839 platelet transfusions in 115 patients were studied to establish the relative importance of 10 clinical factors in determining the efficacy of pooled donor transfusions. Efficacy was measured by the one hour corrected increment in platelet count. The number of transfusions available for study from individual patients varied widely from 1 to 37. Two methods of analysis are presented. The first makes assumptions about the correlation between transfusions within patients, and the variation between patients. The second is based on a repeated sampling procedure whereby unbiased estimates of the parameters of interest are obtained from random samples containing only one transfusion per patient.
Identification of pulses in hormone time series using outlier detection methods
Authors: Thomas Guy , Plu Genevieve , Thalabard Jean‐Christophe 
Published: April 2007

AbstractThe identification of discrete hormonal secretory pulses is of critical importance in clinical endocrinology. Pulses are defined as sudden increases in hormone concentration followed by exponential decay. We propose a model‐based iterative procedure for pulse detection in pulsatile hormone time series. Our model is seen to be analogous to the model for innovation outliers in autoregressive series, and outlier detection techniques for pulse identification are adapted to the endocrine context. An original feature of the procedure is that it distinguishes between true pulses and gross observation outliers in the series. Simulation experiments are used to investigate the behaviour of the method under physiologically or clinically relevant circumstances. Five experimental endocrine series from rhesus monkeys, where the times of the pulses are known from the concomitant recording of the electrical activity of the hypothalamus, are analysed.
24‐Hour blood pressure measurement in antihypertensive drug trials: Data requirements and methods of analysis
Authors: Dickson Dorothy , Hasford Joerg 
Published: April 2007

AbstractNon‐invasive ambulatory blood pressure monitoring is an appropriate technique for the identification of the target population requiring antihypertensive treatment, since the systematic bias seen in casual clinic measurement is removed. The use of the technique in controlled clinical trials leads to a reduction in the sample size required to show a treatment difference in antihypertensive effect compared to sporadic single measurements, although in practice the number of recruited patients can considerably exceed the number of evaluable patients, due to poor compliance or incompleteness of data. In addition, the equality of observation essential in clinical trials cannot be controlled to the same degree as is possible with clinic measurements. Comparison of estimators of the overall characteristic blood pressure reveals that the 24‐hour mean value produces an adequate estimator. A description of the individual blood pressure profile is obtained using smoothing procedures, the moving interval average providing a robust and simple approach. Clinically meaningful characteristics of the profile are difficult to define due to a dearth of information on prognostic importance of the features of the 24‐hour blood pressure profile. Smoothed individual profiles can be combined to produce graphical descriptive treatment group summaries.
Covariate imbalance and conditional size: Dependence on model‐based adjustments
Authors: Maxwell Scott E. 
Published: April 2007

AbstractAnalysis of covariance (ANCOVA) is frequently recommended to correct for covariate imbalance and to control conditional size of hypothesis tests in randomized designs. Such control, however, depends on the accuracy of the ANCOVA model used to make the adjustments. Examination of residuals together with knowledge of the subject matter are important for obtaining an accurate model. Stratified assignment procedures lessen the dependence of proper control of conditional size on the specific model used in the adjustment procedure.
A method to test for a recent increase in HIV‐1 seroconversion incidence: Results from the multicenter AIDS cohort study (MACS)
Authors: Zhou Susan Y. J. , Kingsley Lawrence A. , Taylor Jeremy M. G. , Chmiel Joan S. , He David Y. , Hoover Donald R. 
Published: April 2007

AbstractWe have formulated the problem of determining whether there has been an upturn in HIV‐1 seroconversion incidence over the first five years of follow‐up in the Multicenter AIDS Cohort Study (MACS) as that of locating the minimum of a quadratic regression or examination of two‐knot piecewise spline models. Under a quadratic model, we propose a method to obtain a direct estimate and a bootstrap estimate for the location of the temporal turning point (local minimum) for HIV‐1 seroconversion incidence and three methods to estimate confidence intervals for the location of the turning point for HIV seroconversion incidence: (1) Wald confidence interval estimate with or without log transformation assuming the asymptotic normality and applying the Delta method; (2) asymmetric confidence intervals using Fieller's Theorem and its modification; and (3) bootstrapping confidence intervals. Inferences for the temporal turning point based on Wald tests for a single regression term in a non‐linear regression model were not reliable compared to inferences based on confidence intervals placed on calendar time. We present results using these different method applied to the MACS data and we obtain power estimates to illustrate the performance of different methods.
The role of nchs data systems in the evaluation of intervention and prevention strategies
Authors: Feinleib Manning 
Published: April 2007

AbstractIntervention and prevention strategies for the U.S.A. for the year 2000 have been broadly defined into 22 priority areas encompassing 332 health objectives. NCHS and its data systems have the major responsibility for providing the data for half of these objectives and assisting in a wide array of other data programmes both within and outside of CDC. This paper describes the process used to arrive at these objectives, highlights a few of them, and presents four examples of objectives NCHS is engaged in tracking: breast cancer mortality, breast examinations, infant mortality and cholesterol levels.
Measuring vaccine efficacy from epidemics of acute infectious agents
Authors: Longini Ira M. , Halloran M. Elizabeth , Haber Michael , Chen Robert T. 
Published: April 2007

AbstractA good measure of field vaccine efficacy should evaluate the direct protective effect of vaccination on the person who receives the vaccine. The conventional estimator for vaccine efficacy depends on population level factors that are either unrelated or indirectly related to the direct biological action of the vaccine on persons, including population structure, duration of the study, the fraction vaccinated, and herd immunity, that is, indirect effects. Indirect effects can cause the conventional vaccine efficacy estimator to be inaccurate. We review alternative vaccine efficacy estimators that control for indirect effects at the population level. Thus, they are more accurate than the conventional estimator. We use epidemic simulations to explore the robustness of the conventional and proposed estimators under different field conditions. In addition, we apply the different vaccine efficacy estimators to data from a measles epidemic in Muyinga, Burundi.
Evaluation of protocol change in burn‐care management using the Cox proportional hazards model with time‐dependent covariates
Authors: Ichida J. M. , Wassell J. T. , Keller M. D. , Ayers L. W. 
Published: April 2007

AbstractSurvival analysis methods are valuable for detecting intervention effects because detailed information from patient records and sensitive outcome measures are used. The burn unit at a large university hospital replaced routine bathing with total body bathing using chlorhexidine gluconate for antimicrobial effect. A Cox proportional hazards model was used to analyse time from admission until either infection withStaphylococcus aureusor discharge for 155 patients, controlling for burn severity and two time‐dependent covariates: days until first wound excision and days until first administration of prophylactic antibiotics. The risk of infection was 55 per cent higher in the historical control group, although not statistically significant. There was also some indication that early wound excision may be important as an infection‐control measure for burn patients.
An analysis of AIDS incidence data by clustering trends
Authors: Kafadar Karen , Karon John M. 
Published: April 2007

AbstractAIDS incidence trends vary greatly among geographic areas in the United States. We define clusters of areas within which AIDS incidence trends are similar, as areas within a cluster may have similar human immunodeficiency virus epidemic patterns and thus may lead to similar prevention/intervention strategies. Methods of exploratory data analysis are used to define such clusters from reported quarterly AIDS incidence to December 1990 (adjusted for estimated reporting delays) in homosexual and bisexual men not using intravenous drugs in 39 metropolitan statistical areas (MSAs) in the United States. After smoothing AIDS incidence in each MSA, we define groups from cluster analysis based on a measure of similarity between pairs of MSAs. A log‐linear model gives estimates of the scale factors and the common trend for the MSAs in each group. Alternative metrics and simulated data suggest that the clustering is fairly robust to variations in AIDS incidence data. The resulting clusters separate MSAs with different trends, for example, MSAs in which AIDS incidence shows signs of reaching a plateau are separated from MSAs in which incidence continues to increase rapidly.