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Topic: Selection bias

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	Selection bias -- Facts, Info, and Encyclopedia article (Site not responding. Last check: 2007-10-22)
		Selection bias is the error of distorting a (Click link for more info and facts about statistical) statistical analysis by pre- or post-selecting the samples.
		Selection bias can be the result of (Click link for more info and facts about scientific fraud) scientific fraud which manipulate data directly, but more often is either unconscious or due to biases in the instruments used for observation.
		Self-selection bias, which is possible whenever the group of people being studied has any form of control over whether to participate.
	www.absoluteastronomy.com /encyclopedia/s/se/selection_bias.htm (625 words)

	Confirmation bias - Wikipedia, the free encyclopedia
		Confirmation bias is a type of statistical bias describing the tendency to search for or interpret information in a way that confirms one's preconceptions.
		In inductive inference, confirmation bias is a type of cognitive bias toward confirmation of the hypothesis under study.
		Confirmation bias is a phenomenon wherein decision makers have been shown to actively seek out and assign more weight to evidence that confirms their hypothesis, and ignore or underweigh evidence that could disconfirm their hypothesis.
	en.wikipedia.org /wiki/Confirmation_bias (577 words)

	Bias seléksi - Wikipédia
		Seleksi bias nyaeta distorsi kasalahan analisa statistik dina samemeh- atawa sanggeus-milih sampel.
		Selecting spacial regions, including grid size or zero points (see stratified sampling, cluster sampling).
		For example, to "prove" an association between cancer and a particular locality, you could adjust the size, orientation and alignment of grid cells until most of the local cancers fit in the same grid as the locality.
	su.wikipedia.org /wiki/Selection_bias (482 words)

	EBM Tool Kit - Clinical Epidemiology Glossary (Site not responding. Last check: 2007-10-22)
		Lead-time bias: If prognosis study patients are not all enrolled at similar, well-defined points in the course of their disease, differences in outcome over time may merely reflect differences in duration of illness.
		Referral filter bias: The sequence of referrals that may lead patients from primary to tertiary centres raises the proportion of more severe or unusual cases, thus increasing the likelihood of adverse or unfavorable outcomes.
		Selection Bias: a bias in assignment or a confounding variable that arises from study design rather than by chance.
	www.med.ualberta.ca /ebm/define.htm (1825 words)

	selection bias
		Selection bias comes in two flavors: (1) self-selection of individuals to participate in an activity or survey, or as a subject in an experimental study; (2) selection of samples or studies by researchers to support a particular hypothesis.
		Edzard Ernst, M.D., who was trained in various non-conventional medical therapies, provides an example of selection bias that occurred while he was studying the therapeutic effect of mistletoe injections on cancer patients.
		Selection bias partly explains why there are so many satisfied customers who go to psychics, tarot card readers, palmists, and faith healers.
	skepdic.com /selectionbias.html (1275 words)

	Outcomes from stroke rehabilitation in Veterans Affairs rehabilitation units: Detecting and correcting for selection ... (Site not responding. Last check: 2007-10-22)
		The term "selection bias" merely describes the nonrandom process that generates the data and is not a pejorative description of the quality of rehabilitative services or the ways in which rehabilitative services are distributed within the Veterans Affairs (VA).
		The type of selectivity is reflected by ρ, since it represents the correlation between the disturbance in the selectivity equation and the disturbance in the primary equation.
		In correcting for selection bias, we are not imputing values for functional gain for the overall stroke population.
	www.vard.org /jour/02/39/3/vogel.htm (3221 words)

	Methods for Addressing Selection Bias in Observational Studies (Text Version) (Site not responding. Last check: 2007-10-22)
		Recall that selection bias arises because the "treatment" was correlated with the error term in the outcome equation.
		Selection models with valid exclusion restrictions (variables that predict treatment but not the outcome) and IV models with valid instruments (same thing) are closely related.
		Selection models can be estimated without exclusion restrictions, but then you are relying heavily on (untestable) assumptions about the joint distribution of the error terms.
	www.ahcpr.gov /FUND/training/ettnertxt.htm (3023 words)

	FAQ: Endogeneity versus sample-selection bias
		In general, sample-selection bias refers to problems where the dependent variable is only observed for a restricted, nonrandom sample.
		Because the entire sample is utilized, there are no sample-selection issues (there may be a sample selection issue to the extent that wages are only observed for employed workers; typically this is only a cause for concern in estimating wage equations for females).
		This is accomplished via Heckman's selection correction model (utilizing either ML estimation, or two-step estimation where in the first stage a probit model is used to predict the probability of union status and in the second-stage, the inverse Mills' ratio (IMR) is included as a regressor).
	www.stata.com /support/faqs/stat/bias.html (1378 words)

	SSRN-Correcting for Self-selection Bias in Business Ethics Research by Harvey James Jr.
		Self-selection bias occurs when there is non-random sampling of membership within a group or category, such as employment status, that is hypothesized to affect a variable of interest, such as ethical attitudes or behaviors.
		Self-selection bias is germane to a variety of important business ethics questions, such as how the business environment affect personal ethics or whether business students are more or less ethical than non-business students.
		Correcting for self-selection bias shows that an observed negative correlation between employment and ethics is the result of self-selection rather than factors associated with employment, other things being equal.
	papers.ssrn.com /sol3/papers.cfm?abstract_id=596225 (320 words)

	Selection bias in gene extraction on the basis of microarray gene-expression data -- Ambroise and McLachlan 99 (10): ...
		Selection bias in gene extraction on the basis of microarray gene-expression data -- Ambroise and McLachlan 99 (10): 6562 -- Proceedings of the National Academy of Sciences
		Selection bias in gene extraction on the basis of microarray gene-expression data
		selection bias of the rule was estimated to be almost zero.
	www.pnas.org /cgi/content/full/99/10/6562 (4706 words)

	[No title]
		The result of information bias: Misclassification ¡65(¨BNondifferential misclassification Differential misclassification ¡CCª3ó¨%3.1 Nondifferential Misclassification¡&%(ª¨1Occurs when the degree of misclassification of exposure is independent of case-control status (vice-versa) Example: misclassification of HCV infection due to window period in a study looking at risk factors for HCV.
		Another example: In a cohort study of occupational exposures and asthma, the most susceptible individuals may be more likely to leave employment with early symptoms of asthma and the effect of the occupational exposure may be underestimated as a result.
		Selection bias can occur on the front end of a cohort study, by self- selection bias or by systematic error in recruitment.
	www.epibiostat.ucsf.edu /courses/schedule/epimethods/2001/Bias_atcr_2001.ppt (526 words)

	Biostatistics Seminar-December 5, 2000 (Site not responding. Last check: 2007-10-22)
		We propose a test for selection bias based on a minimally selected $p$-value, analyzed via a refined Bonferroni correction derived by Worsley (1982).
		Further, we propose estimators for the overall probability of selection and for the probability of selection given baseline predictors, and find that much of the selection bias can be explained by one baseline genetic feature.
		Lastly, we show that it is essential to adjust comparisons of treatment strategy for the selection bias; naive comparisons of response and of survival are significant, whereas properly adjusted comparisons are not.
	www.biostat.wisc.edu /generaladmin/seminars/dept120500.html (302 words)

	Book Excerpt: How to Identify Liberal Media Bias (Site not responding. Last check: 2007-10-22)
		Bias by omission can occur either within a story, or over the long term as a particular news outlet reports one set of events, but not another.
		Bias by story selection often occurs when a media outlet decides to do a story on a study released by a liberal group, but ignores studies on the same or similar topics released by conservative groups.
		The second kind of bias by labeling occurs when a reporter not only fails to identify a liberal as a liberal, but describes the person or group with positive labels, such as "an expert" or "independent consumer group." In so doing, the reporter imparts an air of authority that the source does not deserve.
	secure.mediaresearch.org /news/identifybias.html (9646 words)

	An Empirical Study of Optimism and Selection Bias in Binary Classification with Microarray Data
		Also, we find that when the feature selection is not performed during each stage of the cross-validation process, selection bias is present, but again, it is generally small.
		Considering all datasets, classifiers, and gene subset sizes together, the average optimism, selection, and total (optimism plus selection) bias estimates are only 4%, 3%, and 7%, respectively.
		For five of the six datasets, the misclassification rates and bias estimates were very consistent, suggesting that these results should generalize well to other clinical microarray datasets.
	www.bepress.com /mdandersonbiostat/paper3 (382 words)

	Court Revisits Question of Jury Selection Bias
		ASHINGTON, Oct. 16 ó The issue of discrimination in jury selection returned to the Supreme Court today, 16 years after the justices specified procedures for detecting the unconstitutional practice of picking or excluding jurors on the basis of race.
		Kentucky, has been working imperfectly, defense lawyers say, because the court has not yet made clear how trial judges are to evaluate a prosecutor's assertion that the removal of a substantial number of fl prospective jurors was unrelated to race.
		Bunn's assertion that evidence of the prosecution's use of race in other jury selections, while not completely irrelevant, was little better than circumstantial met with objections from several justices.
	www.ric.edu /tschmeling/courses/jurybatsonmiller.html (999 words)

	Supreme Court Rules Against Jury Selection Bias
		The 6-3 decision overturned an appeals court ruling in the case of Thomas Miller-El, who was found guilty of the execution-style murder of a 25-year-old motel clerk during a robbery near Dallas in November 1985.
		The selection process was replete with evidence that prosecutors were selecting and rejecting potential jurors because of race.
		He said California's legal standard for claims of bias in jury selection was at odds with a 1986 Supreme Court ruling that bars the racially discriminatory use of peremptory challenges.
	www.washingtonpost.com /wp-dyn/content/article/2005/06/13/AR2005061300731.html (689 words)

	Selection Bias in Preterm Cohort Studies Overestimates Survival: A Systematic Review (Site not responding. Last check: 2007-10-22)
		Objectives: There is a potential for selection bias in preterm infant cohort studies that only report survival in infants admitted to neonatal units and in those that include livebirths but exclude stillbirth data.
		The objective of this systematic review was to determine if this potential selection bias leads to an overestimate of survival.
		Discussion: Professionals responsible for provision or perinatal services need to be aware of the effect of selection bias has in overestimating survival of infants 23-26 weeks gestation when appraising cohort studies.
	www.cochrane.org /colloquia/abstracts/rome/romePB19.htm (223 words)

	Certificate
		Understand how selection probabilities are used to identify selection bias.
		Describe how selection bias can be reduced or eliminated from epidemiological studies.
		Determine whether selection bias exists based on the 4 selection probabilities in a 2x2 table.
	www.sph.unc.edu /courses/eric/sbtutorial/certificate.htm (577 words)

	Journal of the American Statistical Association: The intrinsic distribution and selection bias of long-period cometary ... (Site not responding. Last check: 2007-10-22)
		A question that arises in the study of cometary orbits is whether or not the directed normals to the orbits are uniformly distributed on the celestial sphere.
		Here a plausible selection mechanism is proposed that gives rise to a one-parameter family of distributions on the sphere.
		A nonzero selection effect is detected, and its size is estimated.
	www.highbeam.com /library/doc0.asp?DOCID=1G1:111300275&refid=holomed_1 (209 words)

	Selection Bias in the Assessment of Gene-Environment Interaction in Case-Control Studies -- Morimoto et al. 158 (3): ...
		Selection Bias in the Assessment of Gene-Environment Interaction in Case-Control Studies -- Morimoto et al.
		Selection Bias in the Assessment of Gene-Environment Interaction in Case-Control Studies
		Selection bias is a common concern in epidemiologic studies,
	aje.oxfordjournals.org /cgi/content/abstract/158/3/259 (294 words)

	Randomisation to protect against selection bias in healthcare trials (Cochrane Methodology Review) (Site not responding. Last check: 2007-10-22)
		The unpredictability of the process, if not subverted, should prevent systematic differences between comparison groups (selection bias), provided that a sufficient number of people are randomised.
		Selection criteria: Cohorts of trials, systematic reviews or meta-analyses of healthcare interventions that compared outcomes or prognostic factors for one of the following comparisons: randomised versus non-randomised trials, randomised trials with adequately versus inadequately concealed allocation, or high versus low quality trials where selection bias could not be separated from other sources of bias.
		However, it is not generally possible to predict the magnitude, or even the direction, of possible selection biases and consequent distortions of treatment effects.
	www.cochrane.org /Cochrane/revabstr/AM000012.htm (540 words)

	Currency Crises, Capital Account Liberalization, and Selection Bias
		Efforts to answer this question properly must control for “self selection” bias since countries with liberalized capital accounts may also have more sound economic policies and institutions that make them less likely to experience crises.
		Our results suggest that, after controlling for sample selection bias, countries with liberalized capital accounts experience a lower likelihood of currency crises.
		That is, when two countries have the same likelihood of allowing free movement of capital (based on historical evidence and a very similar set of economic and political characteristics)—and one country imposes controls and the other does not-- the country without controls has a lower likelihood of experiencing a currency crisis.
	repositories.cdlib.org /sccie/04-14 (242 words)

	Adjustment of an Estimated Proportion (Site not responding. Last check: 2007-10-22)
		Adjustment of a Prevalence Estimate for Selection Bias
		Subjects with the disease who are selected into the study sample as, 'a' and those selected who do not have the disease as 'b'.
		If the selection probabilities are known, then each observed value; 'a' and 'b' can be divided by these probabilities to estimate the number of diseased and non-diseased within the population.
	www.acs.ucalgary.ca /~patten/sbprev.html (183 words)

	[No title]
		In cohort studies, the rate of loss to follow-up indicates the potential for selection bias.
		Comparison of the characteristics of those lost to follow-up with those persons remaining under follow-up, may indicate the potential consequences of any selection bias.
		¡Z¬öó¨Detecting Selection bias¨íIn case-control studies, the approach to case and control selection signals the potential for selection bias.
	www.epibiostat.ucsf.edu /courses/schedule/epimethods/2000/bias_lecture.ppt (229 words)

	Adjustment of an Estimated Proportion (Site not responding. Last check: 2007-10-22)
		Denote the observed data from a case-control study in the form of a traditional epidemiological 2x2 table using: a,b,c,d.
		Denote the analogous population contingencies as: A,B,C,D. Here, there are four selection probabilities resulting from the four disease-exposure contingencies: a/A, b/B, c/C, d/D. A quick way to evaluate the impact of selection bias in a case-control study is to calculate a "selection odds ratio": [(a/A)(d/D)] / [(b/B)(c/C)].
		Multiplying an observed odds ratio by the inverse of this selection odds ratio will result in an adjusted estimate.
	www.acs.ucalgary.ca /~patten/sb_ccs.html (106 words)

	[No title] (Site not responding. Last check: 2007-10-22)
		Propensity to use care is in the error term of the utilization regression and is correlated with insuranceóTN¨Selection Bias: Example #3¡$¨;Earnings among persons with and without a college degree If persons with a college degree are more (unobservably) motivated or intelligent, then positive effects of college degree on earnings may be overstated.
		Bias arises when one endogenous variable is regressed on another.ª,ó¨Endogeneity Bias¡$ª¨kAlthough endogeneity bias is not identical to correlation of the regressor with the error term (Greene), it is similar and the easiest way to think about this.
		If random noise affecting the outcome in turn affects one of the regressors, then you have a bias that IV methods may help with.
	www.ahcpr.gov /fund/training/Ettner.ppt (709 words)

	EconPapers: Testing and Correcting for Sample Selection Bias in Discrete Choice Contingent Valuation Studies (Site not responding. Last check: 2007-10-22)
		We investigate the properties of tests for sample selection bias and the losses made by applying estimators assuming no sample selection.
		The effects of sample selection bias can be sizable but bivariate probit estimation give unbiased estimates.
		A computationally straightforward test for sample selection bias is found to perform well.
	econpapers.repec.org /paper/hhshastef/0171.htm (273 words)

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