bluuebunny/crossref_metadata_2025 huggingface dataset:
Testing the effects of nutrient additions on mudflat macroinfaunal assemblages in the presence and absence of shorebird predators
Authors: Morris Liz , Keough Michael J.
Published: December 2003

An issue that is of increasing concern worldwide relates to the possibility that areas subject to conservation agreements, owing to the resident and migratory bird populations they support, will be adversely affected by attempts to reduce organic inputs into nearshore environments. In the present study, we investigated the effects of nutrient additions and shorebird exclusion on the infaunal assemblages of an intertidal mudflat. Where responses to nutrient additions were observed they only occurred in the high-dose treatments, indicating that a high nutrient loading is required before infaunal responses are initiated at this site. There was no evidence to support the idea that nutrient additions would only stimulate macroinfaunal assemblages where shorebird foraging was reduced. Instead, nutrient additions were detectable separately from any effects of shorebird predation and, contrary to expectations, appeared to be of more importance than shorebird predation in this environment. There was also no evidence to suggest that shorebird predation has a strong interaction with the infaunal prey assemblage and, although further studies will be needed to support this statement, it is possible that moderate changes in nutrient status will not impact on the shorebird populations at this site.
Crabs on cue for the coast: the use of underwater sound for orientation by pelagic crab stages
Authors: Jeffs Andrew , Tolimieri Nick , Montgomery John C.
Published: December 2003

Several studies have suggested that underwater sound may provide an orientation cue for the pelagic stages of coastal crustacea, such as crabs and lobsters, to find their way from the open ocean to the coast where they can settle. Yet, there has been no field evidence to support this phenomenon and it is unclear whether pelagic crustacean stages even have the ability to orient towards sources of underwater sound, such as that which emanates from reefs. Artificial sources of natural underwater sound were deployed offshore in conjunction with light traps to determine if the larval and post-larval stages of coastal crabs were attracted to coastal reef sound. The results demonstrated that the pelagic stages of crabs respond to underwater sounds and that they may use underwater sound to orient towards the coast. The orientation behaviour was modulated by lunar phase, being evident only during first- and last-quarter moon phases, at the time of neap tides. Active orientation during neap tides may take advantage of these incoming night-time tides for predator avoidance or may permit more effective directed swimming activity than is possible during new and full moon spring tides.
Chemical diversity in south-eastern Australian saline lakes II: biotic implications
Authors: Radke L. C. , Juggins S. , Halse S. A. , Deckker P. De , Finston Terrie
Published: December 2003

This study explores how differences in ionic composition of south-eastern Australian saline lake waters, caused by path differentiation according to the Eugster–Jones–Hardie models of solute evolution and halite recycling, influence species composition of ostracod faunas. Ostracod occurrences are reported as physiologically important ionic ratios set in a marine–meteoric framework, with chemical boundaries determined by mixing and evaporation models. The occurrence of halophilous ostracods coincides with changes in the ionic structure of lake waters. Chemical diversity is found to be biologically important, with most ostracods preferring a specific pathway of the Eugster–Jones–Hardie models. Path preference predominantly reflects the different tolerance ranges of species to a combination of Na+/H+, Na+/Ca2+ and alkalinity/Cl– activity ratios, which probably govern acid–base balance and Na+ and Ca2+ regulation. An alkalinity/Cl– activity ratio of ~–2.3 corresponds to the main division in the ostracod data and reflects the abrupt change in alkalinity/Cl– ratios that occurs when a seawater-like solute matrix is diluted with a large amount of meteoric water (95%). Most halobiont ostracods occur in waters enriched with Na–Cl as a result of halite recycling. Evidence is presented that the same geochemical processes are relevant to other aquatic organisms (e.g. zooplankton, diatoms, insects) found in salt lakes.
Colonisation of the south-west Australian coastline by mud crabs: evidence for a recent range expansion or human-induced translocation?
Authors: Gopurenko David , Hughes Jane M. , Bellchambers Lynda
Published: December 2003

Mud crabs (Portunidae; Scylla spp.) have become established recently in some south-west Australian estuaries – almost 1000 km south of their recorded distribution. Colonisation may have occurred by a natural range expansion from the north-west or by translocation from source(s) within the Indo-West Pacific. To identify the species and the potential source population(s), genetic analyses was used to compare south-west crabs (N = 32) to other populations. Levels of diversity at two independent genetic markers were also compared to obtain relative estimates of effective population size between colonist and suspected source population(s). Comparisons of mitochondrial DNA sequences (COI) indicated that all south-west crabs were Scylla serrata. Indeed, the sole haplotype found among colonists was identical to one prevalent but endemic to more diverse north-west Australian populations. In contrast, source and colonist populations had equally high levels of genetic diversity at two microsatellite loci. It is argued that the south-west region was colonised by large numbers of S. serrata from north-west Australia through a recruitment event enhanced by the strong 1999/2000 Leeuwin Current. Differences in diversity among nuclear and mitochondrial loci may reflect different responses to the colonisation process; it is predicted that such differences are prevalent among plankton-dispersed species.
Evaluation of visible implant fluorescent elastomer (VIE) as a tagging technique for spiny lobsters (Jasus edwardsii)
Authors: Woods Chris M. C. , James Philip J.
Published: December 2003

Tagging crustaceans for growth studies is often difficult because external tags/marks may be shed or cause mortalities during moulting. In this investigation, the effectiveness of visible implant fluorescent elastomer (VIE) as an invasive tagging technique for spiny lobsters (Jasus edwardsii) was investigated over a 6-month period. Tagged lobsters were either tagged with the tag running transversely across the ventral abdominal superficial flexor muscle block (transverse VIE) in the second abdominal segment, or in-line with the ventral abdominal superficial flexor muscle block (longitudinal VIE). Non-tagged lobsters were used as the control. At the conclusion of the investigation there were no differences in growth or survival between tagged lobsters and untagged controls and tag retention rates were 100% for both tagging treatments over the 6-month period. Tag visibility was high after six months in both tagging treatments, although higher in the longitudinal VIE treatment. Tag fragmentation was frequent in the transverse VIE treatment, but infrequent in the longitudinal VIE treatment. We conclude that VIE is an effective tagging technique for J. edwardsii in terms of the high degree of tag visibility, retention, and non-detrimental impact on the growth and survival of tagged animals, provided the VIE tag is injected in-line with the orientation of the muscle fibres/tissue.
What price a “pinta”? Differentiating the market for liquid milk: Results of consumer research in the UK dairy sector
Authors: Fearne Andrew
Published: December 2003

Since de‐regulation of the UK dairy market in November 1995, the UK dairy industry has lurched from one crisis to another, as milk prices initially rose to levels that were unsustainable for all but the largest processors and then fell to levels at which even the largest and most efficient dairy farmers are struggling to survive. Considerable emphasis has been placed in recent years on cutting costs in the dairy supply chain, yet little attention has been given to the scope for adding value, particularly for the benefit of dairy farmers. Against this background, the Milk Development Council commissioned a research project, from which this paper is drawn, to explore the scope for adding value to liquid milk. The results of the comprehensive consumer research undertaken provide clear evidence that opportunities exist for differentiating the liquid milk market. The research also underlines the strategic importance of consumer research in an increasingly competitive market environment.
The effect of the brand on perceived quality of food products
Authors: Vraneševic´ Tihomir , Stančec Ranko
Published: December 2003

The chosen marketing strategy (including the branding as its integral parts) is highly important in this process. Nowadays, the brand becomes one of the basic motives for the consumers’ choice of a particular food product. The importance of the product brand shall be seen primarily in its impact on consumers’ choice and their loyalty through identifying and differentiating quality and origin, as well as creating additional values. The aim of this paper is to research the extent to which the consumer perceives the brand and how much it affects the evaluation of the functional characteristics of the product, primarily product quality. This paper analyzes the sales of tin cans (patés) as well as explores the effect of the product brand on sales. The main conclusions of the paper are that consumers do not value products based exclusively on their physical characteristics and that in the process of making a purchasing decision when choosing an alternative, consumers will first perceive the brand as “a sign of quality” and then other evaluation criteria (physical appearance and packaging, price, the reputation of the retail network).
The importance of waiting staff in restaurant service
Authors: Pratten J.D.
Published: December 2003

This study seeks to examine one of the keys to a successful restaurant – the waiting staff. Their backgrounds are investigated, together with the skills and expertise which they are expected to possess by employers and customers. This is compared to the training offered, so that recommendations can be made to the trade about the role of the waiter and waitress in the process of food enjoyment. A range of eating establishments are considered, and the views of the proprietors, their staff and customers taken, so as to offer the views of those involved.
Attitude and satisfaction in a traditional food product
Authors: José Sanzo María , Belén del Río Ana , Iglesias Víctor , Vázquez Rodolfo
Published: December 2003

The aim of this work was to analyse the relationships between three types of variables: consumer attitude towards a generic product – honey; the perceived quality of the specific brand consumed; and the satisfaction with this brand. The paper first tests the effects the different perceived quality dimensions exercise on satisfaction. Second, the paper proceeds to analyse the influence of attitudes, on the one hand, on the different quality dimensions and, on the other hand, on the effects of such dimensions on satisfaction.
From resistance to engagement: a contact‐contract action model for library instruction
Authors: Howze Philip C.
Published: December 2003

The purpose of this article is to describe a method for activating the contact‐contract‐action model, and to present findings based on its adaptation and integration into a formal library instruction course. Contact‐contract‐action, borrowed from social work practice, is used to promote strategic behavior change or “intervention” resulting from careful assessment of what the user needs (contact), what the user is willing to do to meet his or her information need (contract). After completing the contact and contract phases, the user engages in behavior to actually meet the need (action). Its theoretical bases are client self‐determination and problem solving.
Individual research consultation service: an important part of an information literacy program
Authors: Yi Hua
Published: December 2003

Individual Research Consultation Service (IRCS) has long played an important role in teaching and assisting students to find information resources. Based on a study of IRCS at California State University San Marcos (CSUSM) Library, this article discusses the important contributions IRCS has made to the information literacy (IL) program. Using quantitative data and qualitative evidence, the article demonstrates how the IRCS has supplemented and enhanced the formal IL program at CSUSM. Further the author argues that if formally recognized as a component of the IL program, IRCS will play a more prominent role in building student information competency skills.
African American health issues: a selective annotated bibliography
Authors: Jenkins James H.
Published: December 2003

African American men and women suffer from health problems such as hypertension, cardiovascular disease, diabetes, AIDS, sickle cell anemia, and various forms of cancer, often at a higher rate than the rest of the population. There is a need for information about these and other health problems affecting this particular community. This annotated bibliography includes recent articles, books, Internet resources, and Web sites. The audience for this essay includes the layperson, health‐care professionals, and information specialists who wish to provide information to patrons on these important health issues.
Consumer privacy and the Internet in Europe: a view from Germany
Authors: Singh Tanuja , Hill Mark E.
Published: December 2003

Despite the widely varying estimates about the strength of the global Internet economy, there is general agreement among experts about the dramatic influence of this medium on consumers as well businesses. However, one area that has generated conflicting views is the issue of Internet privacy. As businesses develop more sophisticated technologies to collect, store and disseminate information on consumers, privacy and security of this information are raising concerns among consumers and public policy advocates. Anecdotal evidence seems to suggest that consumers in some European countries view privacy protection as a very important issue. Investigates consumer attitudes in the Federal Republic of Germany. The findings indicate that consumers in Germany have very strong views about protecting their privacy. They believe that both companies and governments are obligated to protect the information of their consumers and citizens. To this end, German consumers are willing to support stricter legislation. Results also suggest that German consumers’ views about Internet use and on‐line behaviors, are affected, among other things, by their views regarding privacy in general, their personal expertise in Internet technologies, and how they view the role of the government and the role of companies in protecting consumer privacy.
“To legislate or not to legislate”: a comparative exploratory study of privacy/personalisation factors affecting French, UK and US Web sites
Authors: Gurau Calin , Ranchhod Ashok , Gauzente Claire
Published: December 2003

The trade off between customer privacy and Web site personalisation is currently moving to the forefront of academic and practical debate in marketing. The new Internet applications allow marketers to develop detailed customer databases where personal information is connected with buying patterns, providing a detailed behavioural profile. The collection and use of the data is regulated differently in the European Union and the USA. While Europe considers it important to implement formal legislation for the protection of customers’ privacy rights, the US authorities consider privacy policy to be determined through voluntary regulation by industry. Considering these different approaches, the present study explores and compares the privacy/personalisation dimensions of French, British and US Web sites.
The relational oxymoron and personalisation pragmatism
Authors: Evans Martin
Published: December 2003

Although very much in vogue in both academic discourse and practitioner rhetoric, presents a case for a need to be concerned over the use of the “R” (relational) word in marketing. But even this needs to be implemented with caution and sensitivity as evidence on how consumers react to the approach shows. In an era of self service and disintermediation, marketers are increasingly turning to customer data instead of the tacit understanding of customers they used to possess when interaction was on a more personal basis. There are, however, concerns over the nature of the data collected and the way in which it is used, that lead to a proposition that relationship marketing can be an oxymoron. Also, however, suggests a number of compromise solutions in an era in which marketers are unlikely to abandon the paradigm. If marketing reverted to earlier paradigms rather than promising cynical consumers a “relationship”, perhaps all parties might actually start to gain more trust in each other. Personal rather than relational interaction would indeed be more pragmatic.
Diagnostics for Joint Longitudinal and Dropout Time Modeling
Authors: Dobson Angela , Henderson Robin
Published: December 2003

Summary. We present a variety of informal graphical procedures for diagnostic assessment of joint models for longitudinal and dropout time data. A random effects approach for Gaussian responses and proportional hazards dropout time is assumed. We consider preliminary assessment of dropout classification categories based on residuals following a standard longitudinal data analysis with no allowance for informative dropout. Residual properties conditional upon dropout information are discussed and case influence is considered. The proposed methods do not require computationally intensive methods over and above those used to fit the proposed model. A longitudinal trial into the treatment of schizophrenia is used to illustrate the suggestions.
Testing for Spatial Correlation in Nonstationary Binary Data, with Application to Aberrant Crypt Foci in Colon Carcinogenesis
Authors: Apanasovich Tatiyana V. , Sheather Simon , Lupton Joanne R. , Popovic Natasa , Turner Nancy D. , Chapkin Robert S. , Braby Leslie A. , Carroll Raymond J.
Published: December 2003

Summary. In an experiment to understand colon carcinogenesis, all animals were exposed to a carcinogen, with half the animals also being exposed to radiation. Spatially, we measured the existence of what are referred to as aberrant crypt foci (ACF), namely, morphologically changed colonic crypts that are known to be precursors of colon cancer development. The biological question of interest is whether the locations of these ACFs are spatially correlated: if so, this indicates that damage to the colon due to carcinogens and radiation is localized. Statistically, the data take the form of binary outcomes (corresponding to the existence of an ACF) on a regular grid. We develop score‐type methods based upon the Matern and conditionally autoregressive (CAR) correlation models to test for the spatial correlation in such data, while allowing for nonstationarity. Because of a technical peculiarity of the score‐type test, we also develop robust versions of the method. The methods are compared to a generalization of Moran's test for continuous outcomes, and are shown via simulation to have the potential for increased power. When applied to our data, the methods indicate the existence of spatial correlation, and hence indicate localization of damage.
Random Effects Selection in Linear Mixed Models
Authors: Chen Zhen , Dunson David B.
Published: December 2003

Summary. We address the important practical problem of how to select the random effects component in a linear mixed model. A hierarchical Bayesian model is used to identify any random effect with zero variance. The proposed approach reparameterizes the mixed model so that functions of the covariance parameters of the random effects distribution are incorporated as regression coefficients on standard normal latent variables. We allow random effects to effectively drop out of the model by choosing mixture priors with point mass at zero for the random effects variances. Due to the reparameterization, the model enjoys a conditionally linear structure that facilitates the use of normal conjugate priors. We demonstrate that posterior computation can proceed via a simple and efficient Markov chain Monte Carlo algorithm. The methods are illustrated using simulated data and real data from a study relating prenatal exposure to polychlorinated biphenyls and psychomotor development of children.
Flexible Implementations of Group Sequential Stopping Rules Using Constrained Boundaries
Authors: Burington Bart E. , Emerson Scott S.
Published: December 2003

Summary.  Group sequential stopping rules are often used during the conduct of clinical trials in order to attain more ethical treatment of patients and to better address efficiency concerns. Because the use of such stopping rules materially affects the frequentist operating characteristics of the hypothesis test, it is necessary to choose an appropriate stopping rule during the planning of the study. It is often the case, however, that the number and timing of interim analyses are not precisely known at the time of trial design, and thus the implementation of a particular stopping rule must allow for flexible determination of the schedule of interim analyses. In this article, we consider the use of constrained stopping boundaries in the implementation of stopping rules. We compare this approach when used on various scales for the test statistic. When implemented on the scale of boundary crossing probabilities, this approach is identical to the error spending function approach of Lan and DeMets (1983).
Demographic Analysis from Summaries of an Age‐Structured Population
Authors: Link William A. , Royle J. Andrew , Hatfield Jeff S.
Published: December 2003

Summary. Demographic analyses of age‐structured populations typically rely on life history data for individuals, or when individual animals are not identified, on information about the numbers of individuals in each age class through time. While it is usually difficult to determine the age class of a randomly encountered individual, it is often the case that the individual can be readily and reliably assigned to one of a set of age classes. For example, it is often possible to distinguish first‐year from older birds. In such cases, the population age structure can be regarded as a latent variable governed by a process prior, and the data as summaries of this latent structure. In this article, we consider the problem of uncovering the latent structure and estimating process parameters from summaries of age class information. We present a demographic analysis for the critically endangered migratory population of whooping cranes (Grus americana), based only on counts of first‐year birds and of older birds. We estimate age and year‐specific survival rates. We address the controversial issue of whether management action on the breeding grounds has influenced recruitment, relating recruitment rates to the number of seventh‐year and older birds, and examining the pattern of variation through time in this rate.
Shape‐Invariant Modeling of Circadian Rhythms with Random Effects and Smoothing Spline ANOVA Decompositions
Authors: Wang Yuedong , Ke Chunlei , Brown Morton B.
Published: December 2003

Summary.  Medical studies often collect physiological and/or psychological measurements over time from multiple subjects, to study dynamics such as circadian rhythms. Under the assumption that the expected response functions of all subjects are the same after shift and scale transformations, shape‐ invariant models have been applied to analyze this kind of data. The shift and scale parameters provide efficient and interpretable data summaries, while the common shape function is usually modeled nonparametrically, to provide flexibility. However, due to the deterministic nature of the shift and scale parameters, potential correlations within a subject are ignored. Furthermore, the shape of the common function may depend on other factors, such as disease. In this article, we propose shape‐invariant mixed effects models. A second‐stage model with fixed and random effects is used to model individual shift and scale parameters. A second‐stage smoothing spline ANOVA model is used to study potential covariate effects on the common shape function. We apply our methods to a real data set to investigate disease effects on circadian rhythms of cortisol, a hormone that is affected by stress. We find that patients with Cushing's syndrome lost circadian rhythms and their 24‐hour means were elevated to very high levels. Patients with major depression had the same circadian shape and phases as normal subjects. However, their 24‐hour mean levels were elevated and amplitudes were dampened for some patients.
Smoothing for Spatiotemporal Models and Its Application to Modeling Muskrat‐Mink Interaction
Authors: Zhang Wenyang , Yao Qiwei , Tong Howell , Chr. Stenseth Nils
Published: December 2003

Summary. For a set of spatially dependent dynamical models, we propose a method for estimating parameters that control temporal dynamics by spatial smoothing. The new approach is particularly relevant for analyzing spatially distributed panels of short time series. The asymptotic results show that spatial smoothing will improve the estimation in the presence of nugget effect, even when the sample size in each location is large. The proposed methodology is used to analyze the annual mink and muskrat data collected in a period of 25 years in 81 Canadian locations. Based on the proposed method, we are able to model the temporal dynamics which reflects the food chain interaction of the two species.
Design Considerations for Efficient and Effective Microarray Studies
Authors: Kathleen Kerr M.
Published: December 2003

Summary.  This article describes the theoretical and practical issues in experimental design for gene expression microarrays. Specifically, this article 1) discusses the basic principles of design (randomization, replication, and blocking) as they pertain to microarrays, and 2) provides some general guidelines for statisticians designing microarray studies.
Modeling Longitudinal Data with Nonignorable Dropouts Using a Latent Dropout Class Model
Authors: Roy Jason
Published: December 2003

Summary.  In longitudinal studies with dropout, pattern‐mixture models form an attractive modeling framework to account for nonignorable missing data. However, pattern‐mixture models assume that the components of the mixture distribution are entirely determined by the dropout times. That is, two subjects with the same dropout time have the same distribution for their response with probability one. As that is unlikely to be the case, this assumption made lead to classification error. In addition, if there are certain dropout patterns with very few subjects, which often occurs when the number of observation times is relatively large, pattern‐specific parameters may be weakly identified or require identifying restrictions. We propose an alternative approach, which is a latent‐class model. The dropout time is assumed to be related to the unobserved (latent) class membership, where the number of classes is less than the number of observed patterns; a regression model for the response is specified conditional on the latent variable. This is a type of shared‐parameter model, where the shared “parameter” is discrete. Parameter estimates are obtained using the method of maximum likelihood. Averaging the estimates of the conditional parameters over the distribution of the latent variable yields estimates of the marginal regression parameters. The methodology is illustrated using longitudinal data on depression from a study of HIV in women.
Estimating the Generalized Concordance Correlation Coefficient through Variance Components
Authors: Carrasco Josep L. , Jover Lluís
Published: December 2003

Summary.  The intraclass correlation coefficient (ICC) and the concordance correlation coefficient (CCC) are two of the most popular measures of agreement for variables measured on a continuous scale. Here, we demonstrate that ICC and CCC are the same measure of agreement estimated in two ways: by the variance components procedure and by the moment method. We propose estimating the CCC using variance components of a mixed effects model, instead of the common method of moments. With the variance components approach, the CCC can easily be extended to more than two observers, and adjusted using confounding covariates, by incorporating them in the mixed model. A simulation study is carried out to compare the variance components approach with the moment method. The importance of adjusting by confounding covariates is illustrated with a case example.
Inference in Spline‐Based Models for Multiple Time‐to‐Event Data, with Applications to a Breast Cancer Prevention Trial
Authors: Berhane Kiros , Weissfeld Lisa A.
Published: December 2003

Summary. As part of the National Surgical Adjuvant Breast and Bowel Project, a controlled clinical trial known as the Breast Cancer Prevention Trial (BCPT) was conducted to assess the effectiveness of tamoxifen as a preventive agent for breast cancer. In addition to the incidence of breast cancer, data were collected on several other, possibly adverse, outcomes, such as invasive endometrial cancer, ischemic heart disease, transient ischemic attack, deep vein thrombosis and/or pulmonary embolism. In this article, we present results from an illustrative analysis of the BCPT data, based on a new modeling technique, to assess the effectiveness of the drug tamoxifen as a preventive agent for breast cancer. We extended the flexible model ofGray (1994, Spline‐based test in survival analysis,Biometrics50,640–652) to allow inference on multiple time‐to‐event outcomes in the style of the marginal modeling setup ofWei, Lin, and Weissfeld (1989, Regression analysis of multivariate incomplete failure time data by modeling marginal distributions,Journal of the American Statistical Association84,1065–1073). This proposed model makes inference possible for multiple time‐to‐event data while allowing for greater flexibility in modeling the effects of prognostic factors with nonlinear exposure‐response relationships. Results from simulation studies on the small‐sample properties of the asymptotic tests will also be presented.
Semiparametric Estimation of Tag Loss and Reporting Rates for Tag‐Recovery Experiments Using Exact Time‐at‐Liberty Data
Authors: Cadigan N. G. , Brattey J.
Published: December 2003

Summary.  We present a semiparametric likelihood approach to estimating reporting rates and tag‐loss rates from the tags returned from capture‐recapture studies. Such studies are commonly used to estimate critical population parameters. Tag loss rates are estimated using double‐tagged animals, while reporting rates are estimated using information from high‐reward tags. A likelihood function is constructed based on the conditional distribution of the type of tag returned (low or high reward, single or double tag), given that a tag has been returned. This involves many sparse 5 × 1 tag‐return contingency tables, and choosing a good functional form for the tag loss rate is difficult with such data. We model tag‐loss rates using monotone‐smoothing splines, and use these nonparametric estimates to diagnose the parametric form of the tag‐loss rate. The nonparametric methods can also be used directly to model tag‐loss rates.
Semiparametric Analysis of Recurrent Events Data in the Presence of Dependent Censoring
Authors: Ghosh Debashis , Lin D. Y.
Published: December 2003

Summary.  Dependent censoring occurs in longitudinal studies of recurrent events when the censoring time depends on the potentially unobserved recurrent event times. To perform regression analysis in this setting, we propose a semiparametric joint model that formulates the marginal distributions of the recurrent event process and dependent censoring time through scale‐change models, while leaving the distributional form and dependence structure unspecified. We derive consistent and asymptotically normal estimators for the regression parameters. We also develop graphical and numerical methods for assessing the adequacy of the proposed model. The finite‐sample behavior of the new inference procedures is evaluated through simulation studies. An application to recurrent hospitalization data taken from a study of intravenous drug users is provided.
Modeling Tumor Growth with Random Onset
Authors: Albert Paul S. , Shih Joanna H.
Published: December 2003

Summary.  The longitudinal assessment of tumor volume is commonly used as an endpoint in small animal studies in cancer research. Groups of genetically identical mice are injected with mutant cells from clones developed with different mutations. The interest is on comparing tumor onset (i.e., the time of tumor detection) and tumor growth after onset, between mutation groups. This article proposes a class of linear and nonlinear growth models for jointly modeling tumor onset and growth in this situation. Our approach allows for interval‐censored time of onset and missing‐at‐random dropout due to early sacrifice, which are common situations in animal research. We show that our approach has good small‐sample properties for testing and is robust to some key unverifiable modeling assumptions. We illustrate this methodology with an application examining the effect of different mutations on tumorigenesis.
Profile Analysis of 24‐Hours Measurements of Blood Pressure
Authors: Hirotsu Chihiro , Ohta Eri , Hirose Nobuyoshi , Shimizu Kenichiro
Published: December 2003

Summary.  A method is proposed for classifying subjects according to their convex, flat, or concave change patterns of 24‐hours blood pressure measurements. To obtain such a classification is useful for detecting subjects who show abnormal change patterns and giving them appropriate medical treatments. Therefore, an appropriate statistic is proposed for detecting a systematic change along the time axis, as well as a statistic with its inverse characteristic appropriate for evaluating the noise variation. The method is based on the ratio of those two types of statistics; it is verified to work well on real data, giving a classification of subjects into four types of subgroups: extreme dipper, dipper, nondipper, and inverted dipper. It also suggests that there might be an ultra‐extreme dipper subgroup.
Incorporating Covariates into Standard Line Transect Analyses
Authors: Marques Fernanda F. C. , Buckland Stephen T.
Published: December 2003

Summary. An implicit assumption of standard line transect methodology is that detection probabilities depend solely on the perpendicular distance of detected objects to the transect line. Heterogeneity in detection probabilities is commonly minimized using stratification, but this may be precluded by small sample sizes. We develop a general methodology which allows the effects of multiple covariates to be directly incorporated into the estimation procedure using a conditional likelihood approach. Small sample size properties of estimators are examined via simulations. As an example the method is applied to eastern tropical Pacific dolphin sightings data.
Meta‐analysis of Diagnostic Test Accuracy Assessment Studies with Varying Number of Thresholds
Authors: Dukic V. , Gatsonis C.
Published: December 2003

Summary. Current meta‐analytic methods for diagnostic test accuracy are generally applicable to a selection of studies reporting only estimates of sensitivity and specificity, or at most, to studies whose results are reported using an equal number of ordered categories. In this article, we propose a new meta‐analytic method to evaluate test accuracy and arrive at a summary receiver operating characteristic (ROC) curve for a collection of studies evaluating diagnostic tests, even when test results are reported in an unequal number of nonnested ordered categories. We discuss both non‐Bayesian and Bayesian formulations of the approach. In the Bayesian setting, we propose several ways to construct summary ROC curves and their credible bands. We illustrate our approach with data from a recently published meta‐analysis evaluating a single serum progesterone test for diagnosing pregnancy failure.
Bayesian Modeling of Age‐Specific Survival in Bird Nesting Studies under Irregular Visits
Authors: He Chong Z.
Published: December 2003

Summary. In this article, a Bayesian model for age‐specific nest survival rates is presented to handle the irregular visit case. Both informative priors and noninformative priors are investigated. The reference prior under this model is derived, and, therefore, the hyperparameter specification problem is solved to some extent. The Bayesian method provides a more accurate estimate of the total survival rate than the standard Mayfield method, if the age‐specific hazard rates are not constant. The Bayesian method also lets the biologist look for high‐ and low‐survival rates during the whole nesting period. In practice, it is common for data of several types to be collected in a single study. That is, some nests may be aged, others are not. Some nests are visited regularly; others are visited irregularly. The Bayesian method accommodates any mix of these sampling techniques by assuming that the aging and visiting activities have no effect on the survival rate. The methods are illustrated by an analysis of the Missouri northern bobwhite data set.
Abundance Estimation from Multiple Photo Surveys: Confidence Distributions and Reduced Likelihoods for Bowhead Whales off Alaska
Authors: Schweder Tore
Published: December 2003

Summary.  Maximum likelihood estimates of abundance are obtained from repeated photographic surveys of a closed stratified population with naturally marked and unmarked individuals. Capture intensities are assumed log‐linear in stratum, year, and season. In the chosen model, an approximate confidence distribution for total abundance of bowhead whales, with an accompanying likelihood reduced of nuisance parameters, is found from a parametric bootstrap experiment. The confidence distribution depends on the assumed study protocol. A confidence distribution that is exact (except for the effect of discreteness) is found by conditioning in the unstratified case without unmarked individuals.
Using Local Correlation in Kernel‐Based Smoothers for Dependent Data
Authors: Peterson Derick R. , Zhao Hongwei , Eapen Sara
Published: December 2003

Summary. We consider the general problem of smoothing correlated data to estimate the nonparametric mean function when a random, but bounded, number of measurements is available for each independent subject. We propose a simple extension to the local polynomial regression smoother that retains the asymptotic properties of the working independence estimator, while typically reducing both the conditional bias and variance for practical sample sizes, as demonstrated by exact calculations for some particular models. We illustrate our method by smoothing longitudinal functional decline data for 100 patients with Huntington's disease. The class of local polynomial kernel‐based estimating equations previously considered in the literature is shown to use the global correlation structure in an apparently detrimental way, which explains why some previous attempts to incorporate correlation were found to be asymptotically inferior to the working independence estimator.
A New Dose‐Finding Design for Bivariate Outcomes
Authors: Ivanova Anastasia
Published: December 2003

Summary.  For some drugs, toxicity events lead to early termination of treatment before a therapeutic response is observed. That is, there are three possible outcomes: toxicity (therapeutic response unknown), therapeutic response without toxicity, and no response with no toxicity. The optimal dose is the dose that maximizes the probability of the joint event, response, and no toxicity. The optimal safe dose is the dose, from among the doses with toxicity rate less than the maximum tolerable level, that maximizes the probability of response and no toxicity. We present a new sequential design to maximize the number of subjects assigned in the neighborhood of the optimal safe dose in a dose‐finding trial with two outcomes.
Estimating Predictors for Long‐ or Short‐Term Survivors
Authors: Tian L. , Wang W. , Wei L. J.
Published: December 2003

Summary. Suppose that the response variable in a well‐executed clinical or observational study to evaluate a treatment is the time to a certain event, and a set of baseline covariates or predictors was collected for each study patient. Furthermore, suppose that a significant number of study patients had nontrivial, long‐term adverse effects from the treatment. A commonly posed question is how to use these covariates from the study to identify future patients who would (or would not) benefit from the treatment. In this article, we present “point” and “interval” estimates for thesetof covariate or predictor vectors associated with a specific patient survival status, e.g., long‐ (or short‐) term survival, in the presence of censoring. These estimates can be easily displayed on a two‐dimensional plane, even for the case with high‐dimensional covariate vectors. These simple numerical and graphical procedures provide useful information for patient management and/or the design of future studies, which are key issues in pharmacogenomics with genetic markers. The new proposal is illustrated with a data set from a cancer study for treating multiple myeloma.
Homogeneity Score Test for the Intraclass Version of the Kappa Statistics and Sample‐Size Determination in Multiple or Stratified Studies
Authors: Nam Jun‐mo
Published: December 2003

Summary.  When the intraclass correlation coefficient or the equivalent version of the kappa agreement coefficient have been estimated from several independent studies or from a stratified study, we have the problem of comparing the kappa statistics and combining the information regarding the kappa statistics in a common kappa when the assumption of homogeneity of kappa coefficients holds. In this article, using the likelihood score theory extended to nuisance parameters (Tarone, 1988, Communications in Statistics—Theory and Methods17(5), 1549–1556) we present an efficient homogeneity test for comparing several independent kappa statistics and, also, give a modified homogeneity score method using a noniterative and consistent estimator as an alternative. We provide the sample size using the modified homogeneity score method and compare it with that using the goodness‐of‐fit method (GOF) (Donner, Eliasziw, and Klar, 1996, Biometrics52, 176–183). A simulation study for small and moderate sample sizes showed that the actual level of the homogeneity score test using the maximum likelihood estimators (MLEs) of parameters is satisfactorily close to the nominal and it is smaller than those of the modified homogeneity score and the goodness‐of‐fit tests. We investigated statistical properties of several noniterative estimators of a common kappa. The estimator (Donner et al., 1996) is essentially efficient and can be used as an alternative to the iterative MLE. An efficient interval estimation of a common kappa using the likelihood score method is presented.
Extensions and Applications of the Cox‐Aalen Survival Model
Authors: Scheike Thomas H. , Zhang Mei‐Jie
Published: December 2003

Summary. Cox's regression model is the standard regression tool for survival analysis in most applications. Often, however, the model only provides a rough summary of the effect of some covariates. Therefore, if the aim is to give a detailed description of covariate effects and to consequently calculate predicted probabilities, more flexible models are needed. In another article,Scheike and Zhang(2002,Scandinavian Journal of Statistics29,75–88), we suggested a flexible extension of Cox's regression model, which aimed at extending the Cox model only for those covariates where additional flexibility are needed. One important advantage of the suggested approach is that even though covariates are allowed a nonparametric effect, the hassle and difficulty of finding smoothing parameters are not needed. We show how the extended model also leads to simple formulae for predicted probabilities and their standard errors, for example, in the competing risk framework.
Confidence Bands for Low‐Dose Risk Estimation with Quantal Response Data
Authors: Al‐Saidy Obaid M. , Piegorsch Walter W. , West R. Webster , Nitcheva Daniela K.
Published: December 2003

Summary.  We study the use of simultaneous confidence bands for low‐dose risk estimation with quantal response data, and derive methods for estimating simultaneous upper confidence limits on predicted extra risk under a multistage model. By inverting the upper bands on extra risk, we obtain simultaneous lower bounds on the benchmark dose (BMD). Monte Carlo evaluations explore characteristics of the simultaneous limits under this setting, and a suite of actual data sets are used to compare existing methods for placing lower limits on the BMD.
Estimation of Competing Risks with General Missing Pattern in Failure Types
Authors: Dewanji Anup , Sengupta Debasis
Published: December 2003

Summary. In competing risks data, missing failure types (causes) is a very common phenomenon. In this work, we consider a general missing pattern in which, if a failure type is not observed, one observes a set of possible types containing the true type, along with the failure time. We first consider maximum likelihood estimation with missing‐at‐random assumption via the expectation maximization (EM) algorithm. We then propose a Nelson‐Aalen type estimator for situations when certain information on the conditional probability of the true type given a set of possible failure types is available from the experimentalists. This is based on a least‐squares type method using the relationships between hazards for different types and hazards for different combinations of missing types. We conduct a simulation study to investigate the performance of this method, which indicates that bias may be small, even for high proportion of missing data, for sufficiently large number of observations. The estimates are somewhat sensitive to misspecification of the conditional probabilities of the true types when the missing proportion is high. We also consider an example from an animal experiment to illustrate our methodology.
Estimation of False Discovery Rates in Multiple Testing: Application to Gene Microarray Data
Authors: Tsai Chen‐An , Hsueh Huey‐miin , Chen James J.
Published: December 2003

Summary.  Testing for significance with gene expression data from DNA microarray experiments involves simultaneous comparisons of hundreds or thousands of genes. If R denotes the number of rejections (declared significant genes) and V denotes the number of false rejections, then V/R, if R > 0, is the proportion of false rejected hypotheses. This paper proposes a model for the distribution of the number of rejections and the conditional distribution of V given R, V | R. Under the independence assumption, the distribution of R is a convolution of two binomials and the distribution of V | R has a noncentral hypergeometric distribution. Under an equicorrelated model, the distributions are more complex and are also derived. Five false discovery rate probability error measures are considered: FDR = E(V/R), pFDR = E(V/R | R > 0) (positive FDR), cFDR = E(V/R | R = r) (conditional FDR), mFDR = E(V)/E(R) (marginal FDR), and eFDR = E(V)/r (empirical FDR). The pFDR, cFDR, and mFDR are shown to be equivalent under the Bayesian framework, in which the number of true null hypotheses is modeled as a random variable. We present a parametric and a bootstrap procedure to estimate the FDRs. Monte Carlo simulations were conducted to evaluate the performance of these two methods. The bootstrap procedure appears to perform reasonably well, even when the alternative hypotheses are correlated (ρ = .25). An example from a toxicogenomic microarray experiment is presented for illustration.