bluuebunny/crossref_metadata_2025 huggingface dataset:
Discriminant analysis when all variables are ordered
Authors: Johnston B. , Seshia S. S.
Published: April 2007

Determination of the equation that relates an ordered dependent variable to ordered independent variables is sought. One solution, non‐parametric discriminant analysis (NPD), involves obtaining the best monotonic step function by means of a computer search procedure. Although one can use alternative selection criteria in obtaining the equation, the illustrative examples use absolute distance. This paper compares the prediction procedures obtained from NPD with those from linear discriminant analysis, linear regression (with and without transformed variables), and logistic regression. We show that NPD is analogous to regression tree analysis with incorporation of ordered variables and monotonicity. We use various prediction functions to predict the example data, the data using the leave‐one‐out technique, and a verification set. Consistently, non‐parametric discriminant analysis performs as good as or better than the tested alternatives.
Analysis of variance for repeated measures data: A generalized estimating equations approach
Authors: Carr Gregory J. , Chi Eric M.
Published: April 2007

Various techniques are available for the analysis of repeated measures data, and the appropriate choice depends on distributional assumptions and study design features. A correct analysis must account for potential dependence between repeated observations on the same subject. Liang and Zeger proposed a more unified approach to the analysis of repeated measures data based on the application of generalized estimating equations. We examine the application of these methods to several types of data in which one estimates the mean response directly for each combination of discrete covariates, and uses an identity link. Computations for fitting this type of model are exceptionally simple. Numerical examples suggest that the proposed approach yields estimation and hypothesis testing results consistent with more specialized methods.
Comparisons between a new drug and active and placebo controls in an efficacy clinical trial
Authors: Dunnett Charles W. , Tamhane Ajit C.
Published: April 2007

D'Agostino and Heeren (DH) discussed the multiple comparison issues that arise in evaluating both sensitivity and efficacy in over‐the‐counter drug trials. We propose a general definition of sensitivity that includes DH's definition as a special case. We also propose a test for sensitivity that coincides with the MIN test of Laska and Meisner at one extreme but has the advantage of identifying specific drugs satisfying the sensitivity criterion when some fail to do so. We suggest that the test of Dunnett as well as an extension of it may be useful for the efficacy comparisons.
A method of designing clinical trials for combination drugs
Authors: Pigeon Joseph G. , Copenhaver Margaret Diponzio , Whipple James P.
Published: April 2007

Many pharmaceutical companies are now exploring combination drug therapies as an alternative to monotherapy. Consequently, it is of interest to investigate the simultaneous dose response relationship of two active drugs to select the lowest effective combination. In this paper, we propose a method for designing clinical trials for drug combinations that seems to offer several advantages over the 4 × 3 or even larger factorial studies that have been used to date. In addition, our proposed method provides a convenient formula for calculating the required sample size.
Comparing sample size formulae for trials with unbalanced allocation using the logrank test
Authors: Hsieh F. Y.
Published: April 2007

This paper compares the sample size formulae given by Schoenfeld, Freedman, Hsieh and Shuster for unbalanced designs. Freedman's formula predicts the highest power for the logrank test when the sample size ratio of the two groups equals the reciprocal of the hazard ratio. The other three formulae predict highest powers when sample sizes in the two groups are equal. Results of Monte Carlo simulations performed for the power of the logrank test with various sample size ratios show that the power curve of the logrank test is almost flat between a sample size ratio of one and a sample size ratio close to the reciprocal of the hazard ratio. An equal sample‐size allocation may not maximize the power of the logrank test. Monte Carlo simulations also show that, under an exponential model, when the sample size ratio is toward the reciprocal of the hazard ratio, Freedman's formula predicts more accurate powers. Schoenfeld's formula, however, seems best for predicting powers with equal sample size.
The use of cusums and other techniques in modelling continuous covariates in logistic regression
Authors: Royston Patrick
Published: April 2007

The 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

I 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

Objective 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

The 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

A 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

Various 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

Random 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

Longitudinal 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

This 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

Ethical 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

The 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

Standard 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

The 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

The 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

Non‐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

Analysis 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

We 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

Intervention 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

A 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

Survival 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

AIDS 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.
Measurement error in dietary assessment: An investigation using covariance structure models. Part I
Authors: Plummer Martyn , Clayton David
Published: April 2007

Repeated measures of diet are analysed in an attempt to discover the measurement error properties of various dietary assessment methods. It is customary in such studies to assume that one reference measurement is ‘valid’ (without error) but this assumption is not tenable. An alternative approach, widely used in social science, is to model the covariance matrix of the repeated measures. We apply this methodology to assessments of nitrogen intake, which is essentially equivalent to protein intake.
Modelling lactation using an inverse polynomial in a multilevel statistical model
Authors: Drewett R. F. , Goldstein H.
Published: April 2007

A method is outlined for modelling the relationship between breast‐milk production and time from delivery, suitable for data collected longitudinally. The relationship is described using inverse polynomials. In a two‐level model the coefficients are specified as random variables across subjects, allowing within‐ and between‐subject variation to be separately estimated. In a three‐level model, day‐to‐day variation can also be separately estimated. The model is illustrated using data from the Chiang Mai Lactation Project. It allows the use of covariates that vary over time, and provides a method of analysis that is compatible with the practical constraints on the timing of data collection that are inherent in longitudinal studies.
On population and individual bioequivalence
Authors: Schall Robert , Luus Herman G.
Published: April 2007

In a traditional assessment of the bioequivalence of two formulations of a drug one compares the average bioavailability from the two formulations. Anderson and Hauck argued that in some situations it is not sufficient to demonstrate average bioequivalence, and they proposed a method for the assessment of what they called individual bioequivalence, which essentially is the comparison of the individual responses to the two drug formulations within subjects. In this paper we propose a unified strategy for the assessment of bioequivalence that encompasses new approaches to the assessment of both population bioequivalence, which is the comparison of the marginal or population distributions of bioavailabilities, and individual bioequivalence, which is the comparison of the conditional or within‐subject distributions of bioavailabilities. The general idea is to use a comparison of the reference formulation to itself as the basis for the comparison of the test with the reference formulation. The new approaches overcome the main weakness of the current methods for the assessment of bioequivalence by considering the variability of bioavailabilities in addition to their means. The current methods for the assessment of bioequivalence, namely the conventional assessment of average bioequivalence and the proposal by Anderson and Hauck for the assessment of individual bioequivalence, emerge as special cases. One can evaluate the new bioequivalence criteria statistically by use of bootstrap confidence intervals.
An index of disease activity in rheumatoid arthritis
Authors: Jones P. W. , Ziade M. F. M. , Davis M. J. , Dawes P. T.
Published: April 2007

This paper describes the Stoke Index which has been designed to give a global measure of disease activity in rheumatoid arthritis. The index is based on two objective laboratory measurements, one subjective and two semi‐objective clinical measurements, chosen from 13 measurements using clinical judgement. Variable selection routines in principal components analysis are used to demonstrate that the index measures clinically defined disease activity. Its sensitivity and reversibility are also considered. A comparison is carried out with another index (Mallya‐Mace) and a modification is suggested.
Influence of model‐building strategies on the results of a case‐control study
Authors: Blettner Maria , Sauerbrei Willi
Published: April 2007

We evaluate the analysis of a case‐control study in which many variables were investigated simultaneously. The purpose of the study was to explore some rather unspecific hypotheses about potential risk factors for adult brain tumour. Our aim is to show that in the analysis of case‐control studies many decisions are necessary which are usually not published in detail. As in most studies these decisions are made during analysis and are data dependent. We demonstrate that the data allow sensible alternative decisions which influence the final results. A sensitivity analysis of several aspects of the analysis such as different measurement scales, variable selection, handling of missing values and interactions was performed, and demonstrated variation in the results based on the strategy for analysis. We conclude that details of the final analysis should be decided in the planning phase of a case‐control study, and that more details of model‐building strategies must be published. Results from a study where the analysis is highly data dependent must be interpreted with caution and validation of the results with new studies is essential.
Comparison of methods for the analysis of longitudinal interval count data
Authors: Stukel Thérèse A.
Published: April 2007

Longitudinal studies are often concerned with estimating the recurrence rate of a non‐fatal event. In many cases, only the total number of events occurring during successive time intervals is known. We compared a mixed Poisson‐gamma regression method proposed by Thall and a quasi‐likelihood method proposed by Zeger and Liang for the analysis of such data, in the case where the mean was correctly specified, using simulation techniques with large samples. Both methods produced similar standard errors in most situations, except in the case of time‐dependent covariates with non‐Poisson‐gamma data where they were seriously underestimated by the Thall method. A simple method for discriminating between the variance forms of the two methods is described. The findings are applied to the analyses of clinical trials of non‐melanoma skin cancer and familial polyposis. This study extends the findings of Breslow concerning variance misspecification in overdispersed Poisson and quasi‐likelihood models to the longitudinal setting.
A case for bayesianism in clinical trials
Authors: Berry Donald A.
Published: April 2007

This paper describes a Bayesian approach to the design and analysis of clinical trials, and compares it with the frequentist approach. Both approaches address learning under uncertainty. But they are different in a variety of ways. The Bayesian approach is more flexible. For example, accumulating data from a clinical trial can be used to update Bayesian measures, independent of the design of the trial. Frequentist measures are tied to the design, and interim analyses must be planned for frequentist measures to have meaning. Its flexibility makes the Bayesian approach ideal for analysing data from clinical trials. In carrying out a Bayesian analysis for inferring treatment effect, information from the clinical trial and other sources can be combined and used explicitly in drawing conclusions. Bayesians and frequentists address making decisions very differently. For example, when choosing or modifying the design of a clinical trial, Bayesians use all available information, including that which comes from the trial itself. The ability to calculate predictive probabilities for future observations is a distinct advantage of the Bayesian approach to designing clinical trials and other decisions. An important difference between Bayesian and frequentist thinking is the role of randomization.
Statistical and ethical issues in monitoring clinical trials
Authors: Pocock Stuart J.
Published: April 2007

Most randomized clinical trials require periodic monitoring of the accumulating data. While the efficiency of trial management is enhanced by data monitoring, ethical reasons should primarily dictate the need to terminate or change a trial in response to interim findings.

This article focuses on the ethical dilemma of when to stop a clinical trial and places statistical stopping rules in the context of such ethical decision making. Other issues include the organization of data monitoring committees and the problems of premature publication and exaggerated estimation in trials that stop early. Several topical examples are used to convey the relevance of these issues to current practice.
Applying Bayesian ideas in drug development and clinical trials
Authors: Spiegelhalter David J. , Freedman Laurence S. , Parmar Mahesh K. B.
Published: April 2007

The Bayesian paradigm emphasizes that studies are not performed in isolation, and that external evidence can be used formally in the design, monitoring and reporting of clinical trials. A variety of tools for assessing the current evidence for treatment efficacy are presented, making use of graphical display to provide insight into ethical and efficiency issues in starting and stopping trials – these are illustrated with a trial in osteosarcoma that is currently taking place. Finally we recommend that an additional ‘interpretation’ section is placed in clinical reports to provide a bridge between ‘results’ and ‘discussion’ – it is this section that would contain the Bayesian perspective.
The application of large gaussian mixed models to the analysis of 24 hour ambulatory blood pressure monitoring data in clinical trials
Authors: Selwyn Murray R. , Difranco Donna M.
Published: April 2007

We propose the use of Gaussian mixed models to analyse statistically 24 hour ambulatory blood pressure data from clinical trials. We develop specific models and apply them to data from a clinical study that compares two angiotensin‐converting enzyme inhibitors. We investigate and discuss computing issues related to the implementation of such methods. We conclude that this methodology provides a sophisticated but practical approach to the analysis of such data.
A strategy for assembling samples of adult twin pairs in the United States
Authors: Goldberg Jack , Henderson William G. , Eisen Seth A. , True William , Ramakrishnan Viswanathan , Lyons Michael J. , Tsuang Ming T.
Published: April 2007

In this paper we develop a methodology for the identification of large numbers of U.S. adult twin pairs. Data for this study derive from the U.S. Department of Defense and the Vietnam Era Twin )VET( Registry. The Department of Defense identified potential male twins )n = 10,002( using a computerized record linkage algorithm based on the same last name, same date of birth, and the same first five digits of the Social Security number. Twinship was confirmed by comparison with the Vietnam Era Twin Registry. We developed a logistic regression model that predicts the probability that a paired record identifies twins based on the absolute difference in the last four digits in the Social Security number, the age of issuance of the Social Security number, and the frequency of occurrence of the last name. We used the estimated coefficients derived from this regression model to assign predicted probabilities of being a twin to each matched record. There is a close correspondence between the observed and expected number of twins when evaluated across deciles of predicted probabilities of being a twin; the value of the Harrell's c index )c = 0·68 ∓ 0·0004( indicates the overall predictive accuracy of the regression equation. The results from this study demonstrate the feasibility of identifying adult male–male twin pairs from any large computerized database that contains name, date of birth and Social Security number. However, the selection criteria used in the creation of the computer database must be clearly specified to avoid constructing a biased sample of twins.
Risk ratio and rate ratio estimation in case‐cohort designs: Hypertension and cardiovascular mortality
Authors: Schouten Evert G. , Dekker Jacqueline M. , Kok Frans J. , Cessie Saskia Le , Van Houwelingen Hans C. , Pool Jan , Vandnbroucke Jan P.
Published: April 2007

Multivariate analysis in case‐base designs depends on approximate methods. In the present study, new pseudo‐likelihood methods are developed for this design. With these methods, the case‐cohort risk ratio and rate ratio as well as their standard errors are easily estimated using logistic regression and Poisson regression, respectively. This is illustrated by the association between hypertension and cardiovascular mortality in a cohort, estimated by case‐cohort analysis, using samples of several sizes. The estimates are compared with those obtained in full‐cohort and nested case‐control designs. The results indicate that these methods, which require nothing but widely available computer software, are valid. The case‐cohort design, therefore, is a good, sometimes even advantageous alternative to the nested case‐control design, in studying a disease that is not very rare. Application of the risk ratio method to the full cohort, using a ‘sample’ of 100 per cent follows logically; whenever the true risk ratio is desired instead of the odds ratio, a multivariate model for its estimation is therefore available.
Tracking of markers and onset of disease among HIV‐1 seroconverters
Authors: Galai Noya , Muñoz Alvaro , Chen Kan , Carey Vincent J. , Chmiel Joan , Zhou Susan Y. J.
Published: April 2007

Repeated measurements on persons infected with HIV‐1 indicate that infection has a dynamic impact on several markers of immune suppression and activation. The objectives of this report are: )a( to provide a statistical model for the correlation structure of serial measurements of immunological markers, and )b( to identify features of marker profiles associated with the timing of AIDS diagnoses. We analyse data obtained from 328 seroconverters participating in the Multicenter AIDS Cohort Study on whom the date of HIV‐1 seroconversion is known within ∓ 4·5 months. Immunological markers considered here are CD4 cell counts, serum β2‐microglobulin and serum neopterin. The statistical model for HIV‐related changes in markers consists of )1( a piecewise linear regression model for the trajectories of markers over time and )2( a two‐parameter autocorrelation function that generalizes Markovian and simple random effects autocorrelation structures. Application of this model for marker measurements revealed a high degree of tracking, as the estimated autocorrelation function exhibited sub‐exponential decay over time. Though current marker levels are most informative on future values, there is substantial information )memory( in previous measurements. A feature suggested by the analysis of groups formed according to the length of the AIDS‐free period, is the sequential divergence of the CD4 trajectories where steeper declines occurred with a two‐year lag prior to AIDS onset. For AIDS cases diagnosed 3–5 and 5–7 years after seroconversion, the rates of decline compared with those free of AIDS for at least 4 years were steeper by 95 and 46 per cent respectively at two years prior to AIDS.
A technique for summarizing longitudinal data
Authors: Hathaway Dale K. , D'agostino Ralph B.
Published: April 2007

Many studies collect longitudinal data but do not use them efficiently. We propose a technique for reducing a set of longitudinal data into four common summary statistics together with time. These statistics can be used in place of the raw data in further analyses, for example in a regression analysis. Instead of arbitrarily choosing the summary statistics, we derive them mathematically, thus justifying their use. This simplifies the subsequent analyses, and also improves the interpretation of the results. An example from the Framingham Heart Study illustrates the procedure.
Bayesian analysis of binary data from an audit of cervical smears
Authors: Raab Gillian M. , Elton Robert A.
Published: April 2007

A large data set of unsatisfactory smear rates from 629 different cervical smear takers is used to illustrate a Bayesian approach to the analysis of medical audit data with a binary outcome. It is shown that this gives more relevant results in terms of characterizing individual smear takers than frequentist methods, and that the full Bayesian analysis is preferable to an empirical Bayes approximation when the number of different smear takers is small and at least one individual smear taker has contributed only a few smears. Plots of Bayesian posterior distributions with 95 per cent confidence sets are suggested as a useful way of feeding back the results to individual clinicians.
Inherent difficulties with active control equivalence studies
Authors: Senn Stephen
Published: April 2007

A simple model is used to investigate the relevance of ‘competence’ to active control equivalence studies )ACES(. It is shown that to the extent that such trials are successful the results of such trials must raise doubts regarding their competence. ACES are thus more problematic than classical clinical trials and the problems with such studies cannot be solved simply by exchanging the usual roles of null and alternative hypotheses.
Effect of shipping on quality of seeds, meals, fats, and oils
Authors: Spencer Max R.
Published: April 2007

Although few studies have been conducted relative to quality preservation of oilseeds and their products while in transportation containers, there are known causative factors of quality degradation which are applicable from long experience of storage in ordinary land‐based containers. Often the success of quality retention is a function of the basic level of quality negotiated by the buyer and seller and the inherent idiosyncrasies of the commodity when handled and when exposed to the ambient conditions of the air and container.
Loading, unloading, storage, drying, and cleaning of vegetable oil‐bearing materials
Authors: Gustafson Ewald H.
Published: April 2007

Handling of various oil‐bearing materials and special problems of loading, cleaning, drying, and storage are discussed, along with considerations for preventing quality deterioration during storage.
Oil mill energy sources and power balances in a palm oil operation
Authors: Fonade B. E.
Published: April 2007

Equipment needs for using waste materials to supply steam and electricity in palm oil mills are discussed. Energy balances are considered for mills of varying capacity.
Continuous processing of palm fruit
Authors: de Ramecourt Bernard
Published: April 2007

In the last few years we have seen a remarkable breakthrough of palm oil products into the oilseed world. The old extraction techniques, often inherited from artisan methods, have been modernized to give birth to a veritable “palm oilworks” industry. Present equipment and methods permit obtaining, under optinum yield conditions, high quality products responding well to the requirements of the manufacturers of oil and vegetable fat products.
Cleaning, cracking, dehulling, decorticating, and flaking of oil‐bearing materials
Authors: Galloway J. P.
Published: April 2007

Techniques and equipment for cleaning, cracking, dehulling, decorticating, and flaking of oil‐bearing materials are described. Particular methods and cautions for unusual materials are discussed.
Batch and continuous solvent extraction
Authors: Bernardini Ernesto
Published: April 2007

Two physical processes are used for the removal of oil from oilseeds, one called “solution extraction” and the other “diffusion extraction.” In batch type solvent extraction plants, a diffusion process takes place. Due to their high steam and labor requirements, such plants are being steadily replaced with continuous solvent extraction plants, whose main component is the extractor which can be either of the immersion or percolation type. The combined use of these two types of extractor makes it possible to extract oil directly from oilseeds, even if they have a high oil content, with no need for continuous screw presses or expellers. Comparative data on the processes in most common use are given.