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Topic: Empirical Bayes method

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	Empirical Bayes method - Wikipedia, the free encyclopedia
		In statistics, empirical Bayes methods are a class of methods which use empirical data to evaluate / approximate the conditional probability distributions that arise from Bayes' theorem.
		These methods allow one to estimate quantities (probabilities, averages, etc.) about an individual member of a population by combining information from empirical measurements on the invididual and on the entire population.
		For example, one common approach, called (parametric Empirical Bayes point estimation) is to approximate the marginal using the maximum likelihood estimate (MLE), or a Moments expansion, which allows one to express the hyperparameters η in terms of the empirical mean and variance.
	en.wikipedia.org /wiki/Empirical_Bayes_method (1391 words)

	International Journal of Health Geographics \| Full text \| Exploratory disease mapping: kriging the spatial risk ... (Site not responding. Last check: 2007-11-03)
		The empirical Bayes step has the advantage of shrinking the unstable and often extreme estimates to the global or local mean, and also has a stabilising effect on variance by borrowing strength, as well.
		Due to the constant mean assumption ordinary kriging is the appropriate spatial prediction method and without nugget effect this leads to direct interpolation of the data at the counties centres and to smoothed values shrunken towards the global mean for the rest of the study area.
		Figure 6 is a choropleth map of the empirical Bayes smoothed period prevalences from 43 regions in the study area.
	www.ij-healthgeographics.com /content/3/1/18 (5159 words)

	Cowbird Parasitism
		The empirical Bayes application is employed to estimate proportions using information obtained in a study of parasitism by the brown-headed cowbird.
		The first step to analysis in the empirical Bayes method is to estimate unknown parameters and obtain an estimate of the average parasitism rate on host species.
		His methods included placing artificial eggs in the host nest to determine the means used by the cedar waxwing to reject the egg.
	www.schools.lth5.k12.il.us /bths-east/cowbird.html (2977 words)

	[No title] (Site not responding. Last check: 2007-11-03)
		On the Measures of Uncertainty of Empirical Bayes Small-Area Estimators by Ferry Butar Butar March 16, 1999 Abstract: Small-area typically refers to a small geographic area or a demographic group for which very little information is obtained from the sample surveys.
		An empirical Bayes (EB) method uses sample survey data in conjunction with relevant supplementary data which are obtained from various administrative sources.
		In this talk, a method based on bootstrap samples is proposed to measure the accuracy of the proposed EB estimators of a small-area characteristic.
	www.math.fau.edu /HTMLFILE/EVENTS/co90316.txt (220 words)

	BioMed Central \| Full text \| Comparison and evaluation of methods for generating differentially expressed gene lists ... (Site not responding. Last check: 2007-11-03)
		That is, fold change methods were still the worst, followed by the t-statistic, but there was less of a difference in the performance between the methods in cluster 2 (dendrograms in figure 2).
		Using this method we have demonstrated that the empirical bayes statistic, the Area under the ROC curve method and rank products are accurate ways to identify differentially regulated genes in a microarray dataset and that these can produce robust classifiers.
		The Empiricial bayes statistic [24] is described as equivalent to shrinkage of the estimated sample variances towards a pooled estimate, resulting in far more stable inference when the number of arrays is small.
	www.biomedcentral.com /1471-2105/7/359 (7583 words)

	Amazon.com: Bayes and Empirical Bayes Methods for Data Analysis: Books: Bradley P. Carlin,Thomas A. Louis (Site not responding. Last check: 2007-11-03)
		Bayes and Empirical Bayes Methods for Data Analysis answers the need for a ready reference that can be read and appreciated by practicing statisticians as well as graduate students.
		Introduces Bayes and Empirical Bayes methods and demonstrates their usefulness in challenging applied settings and shows how they can be implemented using modern Markov chain Monte Carlo computational methods.
		Bayes and Empirical Bayes Methods for Data Analysis, Second Edition by Bradley.
	www.amazon.com /Bayes-Empirical-Methods-Data-Analysis/dp/0412056119 (1301 words)

	RedOrbit - Science - Ancestral Gene Reconstruction and Synthesis of Ancient Rhodopsins in the Laboratory1 (Site not responding. Last check: 2007-11-03)
		With stochastic methods such as maximum likelihood and Bayesian analysis, it is important to explore different models of molecular evolution to determine how robust the ancestral reconstruction results are (Huelsenbeck and Bollback, 2001; Huelsenbeck et al., 2002).
		PCR is often the preferred method of choice, due to its ease and speed of use, but care must be taken to avoid propagating errors introduced in the chemical oligonucleotide synthesis, or the subsequent cloning and amplification.
		Empirical Bayes methods were used to estimate amino acids with the highest posterior probabilities for the archosaur node at each site in the protein, with the maximum likelihood estimates of branch lengths and model parameters as priors (Yang, 1997).
	www.redorbit.com /news/display?id=47798 (4897 words)

	TechBrief: The Safety Impacts of Differential Speed Limits on Rural Interstate Highways – HRT –04 –156
		While the data in figure 2 are based on crash rates and validates the results generated by the Empirical Bayes method, it should be noted that the Empirical Bayes method did not use crash rate in the modeling process but included annual average daily traffic (AADT) and section length as independent variables.
		Using the Empirical Bayes technique, the ratio θ of the "actual" after crashes to the "would have been" after crashes is calculated.
		The Empirical Bayes methodology suggested that crash risk during the study period increased for all four policy groups.
	www.tfhrc.gov /safety/pubs/04156/index.htm (2015 words)

	Mathematical Biosciences Institute
		Applying our method for the yeast S. cerevisiae, we find that on average 58% of the genes whose promoter region is bound by a transcription factor are true regulatory targets.
		A new set of accept/reject decisions are reached for each null hypothesis using the empirical Bayes adjusted p-values through a resampling based step-down p-value calculation that protects the analyst against the overall (familywise) type 1 error rate.
		We illustrate the proposed method in two examples, including a simulation study and a a microarray experiment to screen for genes with differential expression in colon cancer versus normal tissue.
	www.mbi.osu.edu /2004/ws1abstracts.html (2697 words)

	[No title]
		Using Bayes rule (see Hagen, p.18), the prior is combined with data collected in an experiment to yield an updated probability of the hypothesis (posterior).
		During initial applications of Bayes rule, priors may have a disproportionately large and potentially misleading effect on the inference process.
		Alternatively, an empirical Bayes method can be employed, in which priors are obtained from past or even current data (Casella, 1985).
	quantrm2.psy.ohio-state.edu /injae/injae/nhst.htm (991 words)

	OSU Statistics: Ming Yuan
		We propose an empirical Bayes method for variable selection and coefficient estimation in linear regression models.
		The method is based on a particular hierarchical Bayes formulation, and the estimator is shown to be closely related to the LASSO estimator.
		Unlike previous empirical Bayes variable selection methods, which in most practical situation can only be implemented through a greedy stepwise algorithm, our method gives a global solution efficiently.
	www.stat.ohio-state.edu /~seminar/2004/yuan.html (148 words)

	Statistical Applications in Genetics and Molecular Biology
		Stochastic dependence between gene expression levels in microarray data is of critical importance for the methods of statistical inference that resort to pooling test statistics across genes.
		The empirical Bayes methodology in the nonparametric and parametric formulations, as well as closely related methods employing a two-component mixture model, represent typical examples.
		It is frequently assumed that dependence between gene expressions (or associated test statistics) is sufficiently weak to justify the application of such methods for selecting differentially expressed genes.
	www.bepress.com /sagmb/vol4/iss1/art34 (278 words)

	Research Activities, January 1997: Research Briefs (Site not responding. Last check: 2007-11-03)
		The appropriateness method elicits ratings of the "appropriateness" of performing medical procedures from a group of expert clinicians for a comprehensive array of potential patient indications and does not force consensus.
		Results of the appropriateness method for TENS, discography, and traction showed no disagreement among panel members and no appropriate indications for their use in the patient scenarios considered.
		Neither informal consensus building nor the appropriateness method was clearly preferred by a majority of panelists.
	www.ahcpr.gov /research/jan97/ra4.htm (1342 words)

	SAHIE Methodology
		The method is a mixed effects linear regression, where the log proportion insured is modeled as a linear combination of several predictors, mostly administrative records.
		The effect of this is similar to that of the empirical Bayes method used in the SAIPE program's estimates.
		The final estimates for counties where there is no sample is the same as the regression estimate, while the estimates for counties with lots of sample or very high insured rates and, thus, low variance, tend to be closer to the direct estimates.
	www.census.gov /hhes/www/sahie/methods/methods.html (1731 words)

	Chapter 6 - Signalized Intersections: Informational Guide (FHWA-HRT-04-091)
		Disadvantages of using this method are that it still does not consider the severity of the collisions and assumes that traffic volume and collisions have a linear relationship.
		Advantages of using such a method are that the potential for safety improvement is more accurately calculated, and that it acknowledges that the relationship between collision frequency and volume is not a straightforward linear one.
		One method of screening proposed treatments is to develop a matrix where each treatment is given a score within different categories, based on the consensus among study team members.
	www.tfhrc.gov /safety/pubs/04091/06.htm (10116 words)

	Good Math, Bad Math : Yet Another Crappy Bayesian Argument
		On the other hand, there are people like me who say that Bayesian methods produce an estimate; for a given estimated probability, you can assign a degree of certainty based on the quality and completeness of your information.
		Because classical methods lack a unified framework, reasonable statisticians may disagree as to which ostensibly objective procedure should be used on any given problem.
		One case that exemplifies the flaws of the frequencist methods is the use of the t-tests with a null hypothesis.
	scienceblogs.com /goodmath/2006/07/yet_another_crappy_bayesian_ar.php (12936 words)

	RAND \| Research Memoranda \| Statistical estimation by the empirical Bayes method: some extensions and logistical ...
		Presentation of the empirical Bayes procedure for improving existing methods of estimating statistical decision parameters which occur in such logistical problems as reliability, maintenance, and supply.
		It consists essentially of estimating a parameter by using an approximate Bayes estimator that does not depend on any previous information, other than earlier observations.
		The author presents estimators for the univariate and multivariate exponential family of distributions, for distributions with nuisance parameters, and for the distribution of a family of random variables (Poisson process).
	www.rand.org /pubs/research_memoranda/RM4442 (269 words)

	Biostatistics - Reprint Index
		Methods for comparing the means of two independent log-normal samples.
		Empirical Bayes Combination Of Estimated Areas Under Roc Curves Using Estimating Equations.
		Methods For Comparing Means Of Two Independent Log-Normal Samples With Applications To Studies Of Hospital Cost In Health Services Research.
	www.biostat.iupui.edu /Faculty/reprint.html (2469 words)

	Improved Estimation of Ecological Effects Using and Empirical Bayes Method (Site not responding. Last check: 2007-11-03)
		Of particular interest are statistical methods of design and analysis to test for impairment of biological assemblages in stream ecosystems associated with water pollution.
		An empirical Bayes approach is proposed here as an alternative and applied for multi-site inference.
		The advantages of an empirical Bayes approach, in particular the substantive contribution of collateral information from nearby sites, are discussed in contrast to traditional methods that employ site-specific information only.
	awra.org /jawra/papers/J94171.html (181 words)

	H. Milton Stewart School of Industrial and Systems Engineering :: Events
		If you need additional information relating to an event, please communicate with the contact person for the event or email www@isye.gatech.edu.
		Abstract: We propose an empirical Bayes method for variable selection and
		a particular hierarchical Bayes formulation, and the estimator is shown to
	www.isye.gatech.edu /events/event.php?id=407 (171 words)

	Not So Different After All: A Comparison of Methods for Detecting Amino Acid Sites Under Selection -- Kosakovsky Pond ... (Site not responding. Last check: 2007-11-03)
		For the SLAC and FEL methods, the rates of Type I and Type II errors for a given P value were rather similar (fig.
		A new method for estimatingsynonymous and nonsynonymous rates of nucleotide substitution considering the relative likelihood of nucleotide and codon changes.
		The neighbor-joining method—a new method for reconstructing phylogenetic trees.
	mbe.oxfordjournals.org /cgi/content/full/22/5/1208 (7969 words)

	R: The MultiWilcoxonTest Class (via CobWeb/3.1 planetlab2.netlab.uky.edu) (Site not responding. Last check: 2007-11-03)
		Significance cutoffs are determined by the empirical Bayes method of Efron and Tibshirani
		Efron B, Tibshirani R: Empirical bayes methods and false discovery rates for microarrays.
		Estimating the occurrence of false positives and false negatives in microarray studies by approximating and partitioning the empirical distribution of p-values.
	bioinformatics.mdanderson.org.cob-web.org:8888 /Software/OOMPA/OnlineHelp/ClassComparison/multiWil.html (592 words)

	Product Details (Site not responding. Last check: 2007-11-03)
		This report describes the application of Bayesian statistical methods to several related problems arising in the estimation of mean daily traffic for roadway locations lacking permanent automatic traffic recorders.
		An evaluation of these methods confirmed results reported in other work, in which a sample consisting of two, 1-week counts was found to be adequate for overcoming prior uncertainty concerning the correct adjustments for a site.
		The empirical Bayes method produced sample-based estimates of mean daily traffic that on the average differed by 5%-6% from estimates based on daily counts for an entire year.
	www.lrrb.gen.mn.us /more.cfm?code=450 (139 words)

	Ovarian Cancer Tumor Marker Behavior in Asymptomatic Healthy Women: Implications for Screening -- Crump et al. 9 (10): ... (Site not responding. Last check: 2007-11-03)
		Empirical Bayes analysis was used to estimate individual-specific
		A hierarchical Bayes linear model (20) was used to characterize
		Morris C. Parametric empirical Bayes inference: theory and applications.
	cebp.aacrjournals.org /cgi/content/full/9/10/1107 (3072 words)

	Accuracy and Power of Statistical Methods for Detecting Adaptive Evolution in Protein Coding Sequences and for ... (Site not responding. Last check: 2007-11-03)
		of the method appear to be due to numerical problems in the
		It was argued that the parsimony-based method was robust
		framework, the empirical Bayes method described in N
	www.genetics.org /cgi/content/full/168/2/1041 (4916 words)

	Accuracy and Power of Bayes Prediction of Amino Acid Sites Under Positive Selection -- Anisimova et al. 19 (6): 950 -- ... (Site not responding. Last check: 2007-11-03)
		This is known as the empirical Bayes approach.
		Bayes method is not based on formal hypothesis testing.
		Because the empirical Bayes method uses parameter estimates
	mbe.oxfordjournals.org /cgi/content/full/19/6/950 (5020 words)

	Modified nonparametric approaches to detecting differentially expressed genes in replicated microarray experiments -- ... (Site not responding. Last check: 2007-11-03)
		of the performance or the underlying assumptions of the methods
		performance of the modified methods is demonstrated using simulated data.
		Empirical Bayes screening of many p-values with applications to microarray studies
	bioinformatics.oxfordjournals.org /cgi/content/abstract/19/9/1046 (455 words)

	UVA-2000-11
		A differential speed limit is defined as being one limit for automobiles and a different limit for commercial motor vehicles ("trucks") whereas a uniform speed limit is defined as a single limit for cars and trucks.
		Using the Empirical Bayes method for before-after safety analysis, this study developed a multivariate crash estimation model (CEM) using the before treatment years data and predicted what the safety would have been if there was no DSL enactment for the after treatment years.
		This study used data from seven states, which either kept the same speed limit strategy since 1990, or changed their strategy at least once.
	www.pti.psu.edu /mautc/docs/UVA-2000-11.html (419 words)

	R: Empirical Bayes Statistics for Differential Expression (via CobWeb/3.1 planetlab2.netlab.uky.edu) (Site not responding. Last check: 2007-11-03)
		Given a series of related parameter estimates and standard errors, compute moderated t-statistics, moderated F-statistic, and log-odds of differential expression by empirical Bayes shrinkage of the standard errors towards a common value.
		They use an empirical Bayes method to shrink the probe-wise sample variances towards a common value and to augmenting the degrees of freedom for the individual variances (Smyth, 2004).
		The empirical Bayes moderated t-statistics test each individual contrast equal to zero.
	rss.acs.unt.edu.cob-web.org:8888 /Rdoc/library/limma/html/ebayes.html (385 words)

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