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Topic: Imputation (statistics)

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	Imputation (statistics) - Wikipedia, the free encyclopedia
		In statistics, imputation is the substitution of some value for a missing data point or a missing component of a data point.
		While many imputation methods are available, two of the most commonly used are hot-deck imputation and regression imputation.
		Imputation is not the only method available for handling missing data.
	en.wikipedia.org /wiki/Imputation_(statistics) (183 words)

	Statistics Finland - Quality guidelines - Statistical Editing and Imputation
		Statistical editing refers to activities by which the statistical data are checked and made as correct as possible with respect to both individual values and mutual compatibility between the values for different variables.
		Statistical editing is needed at each phase, starting from the planning of the data collection all the way to data file formation and data processing and analysis.
		Imputation implies that a missing value for a variable is replaced with an imputed value, which has to be as correct as possible with regard to the true but unknown value.
	www.stat.fi /tk/tt/laatuatilastoissa/lm020900/sp_en.html (263 words)

	[No title]
		Imputation procedures used by NACJD in aggregating data to the county level are described in Section IV.
		Imputation and "Zero-Population" Agencies In compiling its crime and arrest statistics, the FBI tries to ensure that both the numerators (number of crimes and arrests) and denominators (number of people) are based on accurate data and estimates.
		Imputation As this report details, imputation of crime and arrest data has been based on ad hoc procedures that were appropriate at the time they were made and for the uses to which they were originally put.
	www.ojp.usdoj.gov /bjs/pub/ascii/bgpcd.txt (17490 words)

	Statistics: Power from Data! Imputation
		Imputation resolves the problems of missing, invalid or incomplete responses identified during editing, as well as any editing errors that might have occurred.
		Deductive imputation is used when there is only one possible response to the question (e.g., all the values are given but the total or subtotal is missing).
		Done properly, imputation limits the biases caused by not having a complete and accurate record; contains an audit trail for evaluation purposes; and ensures that the imputed records are internally consistent.
	www.statcan.ca /english/edu/power/ch3/imputation/imputation.htm (907 words)

	Multiple Imputation for Missing Data
		Another strategy is single imputation, in which you substitute a value for each missing value.
		Single imputation does not reflect the uncertainty about the predictions of the unknown missing values, and the resulting estimated variances of the parameter estimates will be biased towards zero.
		The SAS multiple imputation procedures assume that the missing data are missing at random (MAR), that is, the probability that an observation is missing may depend on the observed values but not the missing values.
	support.sas.com /rnd/app/da/new/dami.html (1177 words)

	Imputation of Maori descent - Statistics New Zealand
		Imputation is the allocation of a response based on the responses of others with similar attributes.
		Imputation provides a sounder basis for electoral population calculations than the approach used in 1994, when all who did not specify a clear Yes or No answer in the 1991 Census were effectively allocated to not being of MÃ¤ori descent.
		The effect of the imputation was to increase the proportion of those allocated to MÄori descent from 16.0 percent to 17.4 percent of the total population.
	www.stats.govt.nz /developments/imputation-of-maori-descent.htm (293 words)

	Statistics projects
		Imputation by mean, median or random values: missing values replaced by mean, median or random values of non-missing values for the variable.
		Hot-deck imputation: missing values replaced by values from donor records within the same sample that are derived sequentially, hierarchically or via a distance function.
		Multiple imputation: Bayesian method that imputes missing values several times resulting in multiple datafiles that are combined to a single estimation.
	home.hccnet.nl /m.van.veller/statistics.html (1052 words)

	K-Base: The Knowledge Base on Statistical Data Editing (Site not responding. Last check: 2007-11-06)
		Based on the edit rules, the deterministic imputation identifies cases in which there is only one possible solution that would allow the record to satisfy the rules.
		The donor imputation replaces the values to be imputed using data from the closest valid record, also referred to as the nearest neighbour.
		For a given record, a subset of the fields which do not need imputation are automatically used as matching fields, and the maximum standardized difference among these individual fields is used as the distance function.
	amrads.jrc.cec.eu.int /k-base/evaluations/geis.htm (907 words)

	Software for multiple imputation
		Multiple imputation is a simulation-based approach to the statistical analysis of incomplete data.
		This ongoing work is carried out at The Pennsylvania State University, in the Department of Statistics and at the NIDA-supported Center for the Study of Prevention through Innovative Methodology.
		Imputation of missing covariates under a general linear mixed model.
	www.stat.psu.edu /~jls/misoftwa.html (601 words)

	Multiple imputation literature
		Multiple imputation compared with some informative dropout procedures in the estimation and comparison of rates of change in longitudinal clinical trials with dropouts.
		Imputation of missing values in the case of a multiple item instrument measuring alcohol consumption.
		Multiple imputation and maximum likelihood principal component analysis of incomplete multivariate data from a study of the ageing of port.
	web.inter.nl.net /users/S.van.Buuren/mi/hmtl/literature.htm (8593 words)

	Demo Session Program
		Multiple Imputation was originally proposed by Rubin in the early 1970’s as a possible solution to the problem of survey nonresponse, to address the failings of standard analyses of incomplete datasets.
		In SOLAS, users have two Multiple Imputation approaches to choose from, namely: a predictive model-based approach, where the predictive information contained in a user-specified set of covariates is used to predict the missing values, or a propensity score-based approach, in which cases are grouped according to their probability of being missing (i.e.
		Although Statistics is used to provide a common language to convince others of a particular state of nature from the survey data, it can be confusing and difficult to use.
	www.eia.doe.gov /ices2/Software_demo_program.htm (5279 words)

	Glossary: Imputation - Statistics Canada (Site not responding. Last check: 2007-11-06)
		Imputation is the process used to identify problems of missing, invalid or inconsistent responses identified during editing.
		This is done by changing some of the resonses or missing values on the record being edited to ensure that a plausible, internally coherent record is created.
		Statistics Canada Quality Guidelines, 3rd edition, October 1998, page 38
	forum.europa.eu.int /irc/dsis/coded/info/data/coded/en/gl004955.htm (54 words)

	Evaluation of the Canadian Census Editing and Imputation System - Statistics New Zealand
		This research project aimed to evaluate Canadian Census Editing and Imputation System (CANCEIS), the editing and imputation system used by Statistics Canada for census, and to recommend whether Statistics New Zealand should consider implementing the Canadian system in the next New Zealand census in 2006.
		This is a more sophisticated editing and imputation system than Statistics New Zealand has the resources to produce.
		This report compares CANCEIS with the current Statistics New Zealand approach to census editing and imputation, and evaluates the performance of CANCEIS for some simple households and for a limited range of demographic variables.
	www.stats.govt.nz /research-reports/evaluation-canadian-census.htm (226 words)

	Weekly Calendar (Site not responding. Last check: 2007-11-06)
		Although it has a long history of application, theoretical properties of the nearest neighbor imputation method are unknown.
		In this paper we show that under some conditions, the nearest neighbor imputation method provides asymptotically unbiased and consistent estimators of functions of population means and totals, and population distributions and quantiles.
		We also derive the asymptotic variances for estimators based on nearest neighbor imputation and consistent estimators of these asymptotic variances.
	www-math.bgsu.edu /oldcalendars/1998-01-26.html (371 words)

	Profile
		Relative to the high dimension of the data the number of independent samples is often rather small, either because the techniques are too expensive, or because it is hard to obtain enough independent biological samples.
		Clearly, the development of new statistical techniques is required for the extraction of useful biological information from such data.
		Journal of the Royal Statistical Society, Series B. Kooperberg C, Stone CJ,Contribution to the discussion of ``Varying-coefficient models'', by T.
	myprofile.cos.com /kooperberg (1787 words)

	Missing Data (Site not responding. Last check: 2007-11-06)
		Heckman, J. (1976) The common structure of statistical models of truncation, sample selection and limited dependent variables and a simple estimator for such models.
		NOTE: Reviews definitions, noting that MAR means likelihood ratio statistics are OK but that the sampling distribution of y, hence expected information is not right if ignore (in effect condition on) R=r.
		Also reference to Szatrouski, Annals of Statistics, 8, 802-810 (1980) on necessary and sufficient conditions for explicit solutions in the multivariate normal estimation problem for pattered means and covariances.
	www.lshtm.ac.uk /msu/missingdata/biblio.html (5682 words)

	[No title]
		Journal of the Royal Statistical Society: Series D (The Statistician), 50, Chand, N. and Alexander, C.H. Imputing Income For An N-Person Consumer Unit.
		Interface Foundation of North America, Fairfax, VA. Liu, M., Taylor, J.M.G. and Belin, T.R. Multiple imputation and posterior simulation for multivariate missing data in longitudinal studies.
		Statistics in Medicine, 18, 681-694 van Buuren, S., Hopman-Rock, M. and Miedema, H.S. The development of a proposal for revision of the Severity of Disabilities Scale of the ICIDH.
	web.inter.nl.net /users/S.van.Buuren/mi/docs/mi_lit.doc (8965 words)

	K-Base: The Knowledge Base on Statistical Data Editing (Site not responding. Last check: 2007-11-06)
		The junction between external data and statistics data - Is it possible to optimize?
		Imputation of demographic variables from the 2001 Canadian census of population
		Data imputation based on regression models with variations of entropy
	amrads.jrc.cec.eu.int /k-base/papers/all.htm (2507 words)

	Pasi Piela's Curriculum Vitae (Site not responding. Last check: 2007-11-06)
		Main subject: statistics, other: mathematics (cl), computer sciences (a), psychology (a); excellent grades.
		Part-time Teacher, Department of Statistics, University of Jyväskylä.
		Master’s thesis in Statistics, unpublished paper, Jyväskylä, Finland: University of Jyväskylä.
	www.cc.jyu.fi /~papiela/cv.html (419 words)

	Joseph L. Schafer's homepage
		I have served on the faculty of Penn State's Department of Statistics since 1992.
		Since 1996, I have directed several research projects at The Methodology Center, an interdisciplinary unit located within Penn State's College of Health and Human Development.
		Funding for these projects is currently provided by the National Institute on Drug Abuse through a P50 Center grant.
	www.stat.psu.edu /~jls (58 words)

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