Biostatistical Genetics and Genetic Epidemiology

Dr. Robert C. Elston is a statistical geneticist and distinguished professor emeritus at Case Western Reserve University. He was born in London, England. He is one of the eponyms of the Elston-Stewart algorithm. Jane M. Olson is the editor of Biostatistical Genetics and Genetic Epidemiology, published by Wiley.

• Admixture in Human PopulationsAdmixture MappingAdoption StudiesAge-of-Onset EstimationAkaike's CriteriaAlternative HypothesisAnticipationAscertainmentAssociationAssociation, Measures ofAssortative MatingAttributable RiskBayes' TheoremBiasBias in Case- Control StudiesBioinformaticsBlood GroupsBonferroni Inequalities and IntervalsBootstrap MethodCandidate GeneCarcinogenesis ModelsCase-CohortCase-Control StudyCase-Only Gene MappingCausationCladistic AnalysisCohort StudiesCollinearityCommingling AnalysisComparative Genomic HybridizationComplex DiseasesConfidence Intervals and SetsConfounderConfoundingConsistent EstimatorControlsCorrelated Binary DataCorrelationCovariateCox Regression ModelCumulative IncidenceDiagnosticsDiscriminant Analysis, LinearDisease-Marker AssociationDNA SequencesDummy VariablesElston-Stewart AlgorithmEM AlgorithmEugenicsExclusion MappingExpectationExperiment-Wise Error RateFamilial CorrelationsFamily History ValidationFamily-Based Association for QuantitativeTraitsFamily-Based Case-Control StudiesFixed EffectsFounder EffectFrailtyFrequency MatchingGeneGene ConversionGene Expression AnalysisGene Frequency EstimationGene-Environment InteractionGeneral Linear ModelGeneralized Estimating EquationsGeneralized Linear ModelGeneralized Maximum LikelihoodGenetic Correlations and CovariancesGenetic CounselingGenetic DistanceGenetic EpidemiologyGenetic HeterogeneityGenome-Wide SignificanceGenotypeGenotyping and Error-CheckingGoodness of FitHaplotype AnalysisHardy-Weinberg EquilibriumHeritabilityHeterozygosityHidden Markov ModelsHierarchical ModelsHLA SystemHuman Genetics, OverviewHuman Genome ProjectIdentity CoefficientsImportance SamplingInbreedingIncidence RateIncidence-Prevalence RelationshipsIncident CaseInformationInformation MatrixInteractionIsolated PopulationsKin-Cohort StudiesKurtosisLambda Criterion, Wilks'Level of a Test Liability ModelLikelihoodLikelihood RatioLikelihood Ratio TestsLinear Regression, SimpleLinkage Analysis, Model-Based Linkage Analysis, Model-FreeLinkage DisequilibriumLinkage Information ContentLogistic Regression, ConditionalLoss of HeterozygosityMap FunctionsMarginal LikelihoodMarginal ModelsMarkersMarkov Chain Monte CarloMarkov ChainsMatched AnalysisMatchingMaximum LikelihoodMcNemar TestMendel's LawsMeta-analysisMixed Model in Segregation AnalysisMolecular EpidemiologyMonte Carlo MethodsMultilocus (Gene �Gene) InteractionMultiple ComparisonsMultiplicative ModelMultipoint Linkage AnalysisMultivariate Linkage AnalysisMultivariate Normal DistributionMultivariate Normality, Tests ofMutationNeural NetworksNull HypothesisOdds RatioOrnstein-Uhlenbeck ProcessOvermatchingP ValueParental EffectsParsimonyPartial LikelihoodPaternity TestingPath AnalysisPedigrees, Sequential SamplingPenetrancePharmacogeneticsPolygenic InheritancePolymorphismPolymorphism Information ContentPopulation GeneticsPopulation-Based StudyPower TransformationsPredictionPrevalencePrincipal Components AnalysisProfile LikelihoodProtecting Privacy in Genetic StudiesPseudo-LikelihoodRadiation Hybrid MappingRandom EffectsRegressionRegressive ModelsRelationship TestingRelative OddsRelative RiskResidualsResponse VariableRisk RatiosSegregation Analysis, ClassicalSegregation Analysis, ComplexSegregation RatiosSelection BiasSensitivitySequence AnalysisSequential Linkage AnalysisSex Ratio at BirthSimulated AnnealingSimulationSkewnessSoftware for Genetic EpidemiologySpecificityStatistical ForensicsStratificationTransformationsTransition ProbabilitiesTwin AnalysisTwin ConcordanceTwin RegistersTwo-Phase SamplingUnbiasednessUnivariate ResponseValidity and Generalizability in Epidemiologic StudiesVarianceVariance Component AnalysisX-linkageZygosity Determination

"...a highly useful tool for those already engaged in research in biostatistical genetics and genetic epidemiology." (American Journal of Physical Anthropology, August 2005) "...an excellent reference guide, especially useful as an introduction to topics where the researcher is not an expert..." (Statistical Methods in Medical Research, Vol.14, No.1, 2005) "...a very useful addition to the genetic epidemiologist's bookshelf." (Journal of the American Statistical Association, June 2004) "...articles were commendably brief and informative...I expect to use this book frequently in the future..." (Short Book Reviews, 2004) "This wonderfully compiled book will be a great reference book for the genetic statisticians and epidemiologists." (Journal of Statistical Computation and Simulation, July 2003) "...the third extraction...from the comprehensive Encyclopedia of Biostatistics...a good value for statisticians with an interest in genetics." (Technometrics, Vol. 44, No. 4, November 2002)