bluuebunny/crossref_metadata_2025_split huggingface dataset:
Normal Values of Biological Characteristics
Authors: Harris Eugene K. 
Published: July 2005

AbstractThis entry focuses on clinical biochemistry and hematology measurements, this being the area where most progress has been made in the estimation of normal values. Other examples are noted in passing. Parametric and nonparametric methods to estimate normal ranges are described, together with the identification and treatment of outlying observations. Calculation of normal ranges for population subgroups is discussed. There is a brief review of the establishment of time‐dependent normal values, and estimation of multivariate normal indexes or regions for correlated clinical variables.
Pharmacoepidemiology, Overview
Authors: Suissa S. 
Published: July 2005

AbstractPharmacoepidemiology is the study of patterns of medication use in the populations and their effects on diseases. Particular interest is focused on unexpected risks, especially events such as rare side effects. These can typically not be adequately assessed in the context of randomized clinical trials. This entry describes the use of Pharmacoepidemiology through the case‐crossover design, dealing with confounding in observational studies, the specification of appropriate risk functions over time, the probabilistic assessment of causality, and study methods based on the use of prescription data.
Placebos
Authors: Holbrook Anne , Goldsmith Charles H. , Leung Mova 
Published: July 2005

AbstractPlacebos have a long and controversial history in clinical research and in practice. In this chapter, we review the meaning, the pharmacology, effectiveness, safety, influences on, and ethical issues involving placebos. Various international guidelines for the use of placebos in research are available and evolving. We then suggest novel factorial designs to allow a full assessment of efficacy and safety of a new therapy while minimizing patient exposure to placebo alone.
Postmarketing Surveillance of New Drugs and Assessment of Risk
Authors: Anello C. , O'Neill R. 
Published: July 2005

AbstractThe goal of this article is to review the role, rationale, objectives, and design of quantitative methods of surveillance strategies developed for drug safety assessment over the past 30 years. Emphasis is placed on the quantitative methods that have been developed in response to regulatory requirements to monitor adverse drug event data for the purpose of assessing potential risk.
Predictive Modeling of Prognosis
Authors: Marshall G. 
Published: July 2005

AbstractPrognosis is defined in terms of the relative probability of developing one of the several alternative outcomes in the natural history of a disease. This entry discusses predictive models for prognosis using a general Markov model in which the exact transition times are not observed. Data from a longitudinal study of young patients with diabetes are used to determine factors affecting the natural course of diabetic retinopathy. Other examples mentioned include hepatocellular carcinoma and HIV infection.
Scan Statistics for Disease Surveillance
Authors: Wallenstein S. 
Published: July 2005

AbstractScan statistics provide the researcher with a measure of unusualness (statistical significance) associated with a clustering of events in time, as would occur when observing an unexpectedly large number of events in a short time period. The statistic can also be used to detect seasonal clustering, and as a method to detect geographical, time, or space–time clustering. The scan statistic can also be generalized and then applied to the analysis of DNA sequence data focusing on detecting a certain pattern.
Screening, Overview
Authors: Van Oortmarssen Gerrit J. 
Published: July 2005

Abstract
This entry describes a series of measures that may summarize the performance of a screening program, with respect to possible outcomes, impact, and frequency in the target population. A conceptual framework that may be used to establish the effectiveness of screening is presented, together with possible biases that may emerge in alternative study designs for screening evaluation. Monitoring of ongoing screening is also briefly reviewed.
Sensitivity Analysis
Authors: Goldsmith Charles H. 
Published: July 2005

AbstractSensitivity analysis is a reassessment of the model used for data summary that attempts to detect whether changing any of its assumptions leads to different interpretations of the outcome. Sensitivity analysis can be carried out simply by varying parameter values to assess whether a different interpretation of the response emerges, or more elaborate ideas from Monte Carlo analysis and factorial experiments can also be used. Sensitivity analyses have been used recently for meta‐analysis. Other techniques such as graphical displays and comparison of alternative model formulations are also briefly mentioned.
Time‐Varying Treatment Effect
Authors: Lavori Philip W. , Dawson Ree 
Published: July 2005

AbstractThis entry is concerned with assessing the effect of treatments that vary in time on the outcomes for individual patients. For example, levels of compliance with therapy may vary over time among participants in a clinical trial. Assessment of treatment effects in this situation is complicated by the fact that the relevant comparison may not be between randomized groups of patients. The so‐called “ignorability of treatment” condition is discussed, relating to the requirement that treatment actually received should be independent of potential patient responses to treatment. Other issues relating to the observational comparisons in medicine and adjustment for confounders are reviewed, together with a brief mention of recent developments in structural equation modeling of treatment effects in this context.
Vaccine Studies
Authors: Halloran M. Elizabeth 
Published: July 2005

AbstractThis entry begins with a brief overview of the biological background for vaccine action, and then describes the various phases of vaccine development, including early phases of identification of candidate vaccines, establishment of safety and immunogenicity in animals, safety and immunogenicity in humans, field efficacy trials, and post licensure studies. Measures of vaccine efficacy are described, and certain potential study biases are identified.
Cost–Benefit Analysis, Willingness to Pay
Authors: O'Brien Bernie 
Published: July 2005

Abstract
Cost–Benefit Analysis (CBA) is a technique of economic evaluation, where the benefits of programs are valued in monetary terms to permit direct comparison with program costs. There are a number of measurement and statistical challenges that arise while attempting to assign money values to health program benefits such as reduction in the risks of morbidity and mortality. The basic measurement goal is to quantify the trade‐offs that consumers are willing to make between reduced health risk and money. Specifically, to identify the maximum willingness to pay (WTP) for health benefits. In this chapter, we review several approaches to both market‐based “revealed preference” and survey‐based “stated preference” WTP estimation. A prevalent method developed in environmental economics is to ask respondents to accept/reject questions for increasingly higher monetary amounts (“bids”) and then to use survival‐type methods to estimate a bid curve, with covariates, that can be used to solve mean or median WTP.
Computerized Therapeutic Decision Support
Authors: Pifer Eric , Weiner M. G. , Williams Sankey V. 
Published: July 2005

AbstractThe increasing breadth and depth of clinical information stored electronically has enabled computerized therapeutic decision support systems to provide appropriate and timely advice to providers, which that is tailored specifically to a patient's clinical status. This chapter provides a taxonomy for therapeutic decision support systems in terms of the goals of the advice, the mechanism in which the advice is given, the information needed to generate the advice, and the underlying reasoning used. Examples of applications of therapeutic decision support systems are provided with an assessment of their utility within the complex processes of clinical care.
Admixture Mapping
Authors: Majumder Partha P. 
Published: July 2005

Abstract
Admixture between populations leads to linkage disequilibrium between loci if the allele frequencies are different between populations. One can test whether the linkage disequilibrium is due to linkage or admixture. One can condition the analysis on parental genotype or parental admixture. In the former case, what is scored is whether a haplotype in a parent is transmitted or not to an affected offspring.
Adoption Studies
Authors: Neale M. C. 
Published: July 2005

Abstract
The adoption study is a “natural experiment” but has methodological difficulties, such as confidentiality, sampling (ascertainment), and selective placement. When performed in nuclear families or combined with twin analysis (of special note are monozygotic twins reared apart), adoption studies have the potential to allow estimation of broad sense heritability and genotype environment interaction. A common method of analysis for continuous traits uses path analysis together with maximum likelihood. In the case of binary traits, logistic regression may be used, or in the framework of structural equation modeling, integration of the multivariate normal distribution is necessary.
Assortative Mating
Authors: Wilson Susan R. 
Published: July 2005

Abstract
Assortative mating occurs when the phenotypes of biological parents are more (or less) similar than would occur under random mating. In contrast to inbreeding, mechanisms for assortative mating are poorly defined. The classical model for assortative mating makes strong assumptions, such as independent genetic and environmental contributions to a trait and no interaction between genotype and environment. More complex models have been developed, especially for human behavioral traits. Assortative mating affects the estimations and interpretation of heritability and lowers the power of linkage studies.
Genetic Markers
Authors: Elston Robert C. 
Published: July 2005

Abstract
Genetic markers are genetic polymorphisms, used for the study of population structure, linkage and association analysis, paternity testing, and forensics, that segregate in a simple Mendelian fashion. They include blood cell antigens, restriction fragment length polymorphisms, minisatellites (variable number of tandem repeat), microsatellites (short tandem repeat), and single nucleotide polymorphisms.
Blood Groups
Authors: Reisner E. 
Published: July 2005

Abstract

The term
blood groups
encompasses the products of genes expressed as molecules on the surface of red cells in humans. They were first investigated for their clinical importance in the transfusion of blood products and then became useful as genetic markers for population genetic studies. Included in the blood groups are the ABO, Rhesus (Rh), MNSs, P, Kell, Duffy, Kidd, Lutheran, and Lewis blood.
Case‐Only Gene Mapping
Authors: Weir B. S. , Nielsen D. M. 
Published: July 2005

Abstract
When individuals can be characterized as being affected or unaffected by a disease, marker‐trait association can be addressed by comparing marker frequencies between these two categories. It is also possible to infer linkage or association on the basis of marker data from affected individuals only. When there is linkage disequilibrium a test for Hardy‐Weinberg proportions among marker genotypes in the affected population is a test about marker allele and genotype associations with the disease locus. However, rejection Hardy‐Weinberg at the marker locus in the affected population may simply reflect nonrandom mating in the whole population.
Cladistic Analysis
Authors: Zhu Xiaofeng , Cooper Richard S. , Elston Robert C. 
Published: July 2005

AbstractHaplotype based association analysis is playing an important role in dissecting the genetic factors underlying complex diseases. Cladistic analysis, which incorporates the evolutionary information among haplotypes, can improve the power to detect genetic factors by limiting the number of hypothesis tests that need to be performed. In this article, we describe the cladistic analysis method and its application to mapping quantitative trait loci.
Commingling Analysis
Authors: Mendell Nancy Role , Finch Stephen J. 
Published: July 2005

AbstractCommingling distributions have been proposed as a logical extension to the genetic model for genetic traits that are either polygenic or multifactorial. Mixture models can be used to describe unobserved heterogeneity in many situations. For normal component distributions with equal variance, the EM algorithm can be used to find the maximum likelihood estimates of the parameters. The asymptotic distribution of the likelihood ratio test of the null hypothesis of a single normal distribution is unknown but can be approximated by the parametric bootstrap. A Bayesian approach to this problem can also be taken.
Comparative Genomic Hybridization
Authors: Moore Dan H. 
Published: July 2005

Abstract
Comparative genomic hybridization is a method for directly identifying regions of gains and losses of genomic material in chromosomes. The results are measured as a series of test‐to‐reference signals from fluorescent dyes for a large number of distinct chromosomal regions and statistical methods are used to identify regions where the signal ratios are significantly different from 1.0. It is applied to microarrays to define abnormality in tumours.
Complex Diseases
Authors: Palmer Lyle J. 
Published: July 2005

Abstract
The principal distinction between “simple” monogenic diseases and “complex” diseases is that the latter do not exhibit classic patterns of Mendelian inheritance. Complex diseases tend to involve greater difficulties in phenotype definition and present challenges for genetic epidemiology. There is, typically, incomplete penetrance and genetic heterogeneity and they are often closely associated with “intermediate” phenotypes that are themselves highly heritable. The use of isolated populations, inbred animal models, and linkage and association analysis with haplotypes are often used in the study of complex diseases.
Family‐based Association for Quantitative Traits
Authors: Horvath Steve , Laird Nan M. 
Published: July 2005

Abstract
Tests of allelic association are designed to demonstrate relationships between genetic and phenotypic information. The class of tests using transmission information from parents to offspring (TDT and its generalizations) are very popular with dichotomous phenotypes because of their lack of sensitivity to population heterogeneity. Here we discuss the generalization of this approach to quantitative phenotypes.
Genetic Heterogeneity
Authors: Olson Jane M. 
Published: July 2005

AbstractThe term genetic heterogeneity refers to the underlying diversity in genetic architecture of different individuals in the population with a common phenotype. Two types of genetic heterogeneity are commonly distinguished: locus heterogeneity in which variants at different loci can predispose to the same phenotype, and allelic heterogeneity in which different variants at the same loci can predispose to the same phenotype. Although allelic heterogeneity is certainly of interest, once a susceptibility locus is identified, the presence of locus heterogeneity so dramatically reduces the power of gene mapping for complex traits that it remains a major statistical challenge. In this article, we primarily discuss models of linkage analysis that allow for locus heterogeneity, including more recent models that allow for heterogeneity‐related covariates.
Linkage Disequilibrium
Authors: Chakravarti Aravinda 
Published: July 2005

AbstractThe nonrandom association between alleles at different loci is termed linkage disequilibrium. This note discusses the origin of this concept, its theoretical genetic basis, its estimation and tests of significance, and applications. Linkage disequilibrium studies are critical in human disease gene mapping and is now a major area of research with the availability of variation of the human genome sequence.
Linkage Information Content
Authors: Guo Xiuqing 
Published: July 2005

Abstract
The probability of knowing IBD sharing status of relative pairs at polymorphic genetic markers is an important factor for a model‐free linkage study. Here, Linkage Information Content (LIC) value is introduced, which measures the informativeness of a marker for identity‐by‐descent (IBD) sharing status of relative pairs. LIC value is independent of the mode of inheritance of the disease, but is specific to the type of relative pairs used.
Mendel's Laws
Authors: Wijsman Ellen M. 
Published: July 2005

AbstractGregor Mendel's experiments with peas lead to the development of two laws that describe, in quantitative terms, trait distributions in the offspring of a mating. The first, which still forms the fundamental basis behind much of genetics, is the law of segregation. In modern terms, this law states that each individual, as a parent, transmits to an offspring, exactly one randomly chosen allele of the two present at each locus in the individual. The second law, or law of independence, describes the joint behavior of more than one gene. This law states that alleles at one locus segregate independently of alleles at other loci. This proposition is now known to be false for genes on the same chromosome, but still, usually adequately describes the inheritance patterns of multiple genes, other than those on the same chromosome.
Linkage Analysis, Multipoint
Authors: Speed Terry P. 
Published: July 2005

Abstract
Multipoint linkage analysis is the analysis of linkage data involving three or more linked loci. Such analyses are carried out to order or map a set of loci, to position a new locus in relation to a mapped set of loci, or to exclude a locus from a region containing two or more loci. Multipoint linkage analysis can be viewed as an attempt to make more efficient use of recombination data in furthering the aims of linkage analysis. It is more complicated than two‐point linkage analysis in several ways: the order of loci needs to be specified; a joint distribution for all recombination patterns needs to be specified; and the calculations can become prohibitive rather quickly. Likelihood methods are used in multipoint linkage analysis; there are two principal approaches to calculating likelihoods in the literature: the Elston–Stewart algorithm, which works on a relatively few loci and many individuals in a pedigree, and the Lander–Green algorithm, which is effective for many loci and relatively few individuals in human pedigrees.
Parental Effects
Authors: Fallin Dani , Palmer Lyle J. 
Published: July 2005

Abstract

An individual's risk for a genetic disease or phenotype, conditional on their own genotype, may depend on parental effects such as imprinting, or the genotype or phenotype of a particular parent. For example, under imprinting, a risk‐conferring allele may only be expressed in an individual if it is inherited from a particular parent. Alternatively, a mother's genotype, even if not transmitted to her offspring, may influence
in utero
conditions and increase risk and/or interact with genetic predisposition for particular diseases among those offspring. The existence of such parental effects may lead to incorrect interpretations of the (marginal) effects of particular genes when performing human genetic studies at the individual level, unless such effects are accounted for in the analysis. We discuss potential scenarios of such parental effects, and present an overview of current methods for accommodating these effects when performing segregation analysis, linkage analysis, or genetic association studies.
Relationship Testing
Authors: Epstein Michael P. , Boehnke Michael 
Published: July 2005

Abstract
Linkage analyses of genetic diseases are accomplished using data from related individuals in families. These analyses assume that one correctly specifies the relationships among all pairs of relatives within these different families. Relationship misclassification may lead to inappropriately reduced or increased evidence for linkage. Sometimes, one can identify misspecified relationships by detecting Mendelian inconsistencies. However, for smaller family subsets such as sibling pairs, it may not be possible to identify misspecified relationships with certainty. Still, with an adequate amount of marker data, one may be able to identify misspecified relationships probabilistically. This section describes a variety of different statistical methods that one can apply to identify misspecified relationships of relative pairs. Generally, these methods are accurate and computationally fast.
Bioavailability and Bioequivalence
Authors: Chow Shein‐Chung , Liu Jen‐Pei 
Published: July 2005

AbstractA brief history of regulatory development using bioavailability and bioequivalence studies for approving generic drug products is provided. Concepts of drug exchangeability and switchability are illustrated and their relationship with average bioequivalence, population bioequivalence, and individual bioequivalence is elucidated. The commonly used crossover designs for bioavailability and bioequivalence studies are presented. They include the standard two‐sequence two‐period crossover design, some higher‐order crossover designs for comparing two treatments, and Williams design. Statistical methods for evaluation of average bioequivalence, including the confidence interval and two one‐sided tests approaches, are illustrated with reference to sample size determination. Current issues and future challenges for bioavailability and bioequivalence studies are also given.
Biological Standardization
Authors: Gaines Das Rose E. 
Published: July 2005

Abstract
The potency of a biological product usually needs to be assessed in terms of its biological activity rather than in terms of its chemical or physical properties. Biological variability means that this assessment depends on statistical techniques, such as bioassay and on the availability of biological standards, which have known properties. Standards can be local, as might be used within a company for the assessment of a new assay or international standards, which are required for the primary calibration of biological products.
Dilution Method for Bacterial Density Estimation
Authors: Gaines Das Rose E. 
Published: July 2005

Abstract
There are many methods for the measurement of bacterial mass and concentration. Different measures reflect different characteristics of the bacterial mass, and not all measures reflect the number of viable bacteria. If direct counting and characterization of individual bacterial cells is not possible or feasible, indirect methods must be used. Determination of the “most probable number” and serial dilution assays are indirect methods intended to reflect the number of viable bacteria.
Dose–Response Models in Risk Analysis
Authors: Gaylor David W. 
Published: July 2005

Abstract
Various biological insults, such as exposure to hazardous chemicals, pose a risk to human health. For various purposes, including attempting to set safe limits of exposure, it is useful to quantify the risk. Direct evidence from human exposure is seldom available and most substances are assessed through bioassays on animals. The form of the dose–response relation obtained from these studies is important, as extrapolation to doses lower than those used in the experiments is necessary to try to estimate risks at the doses encountered in human exposure. Various dose–response models are presented, including multistage and multimutation carcinogenesis models. Models for continuous data are also mentioned. Models for litters are discussed as these are important in reproduction and developmental studies.