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Is MI the only principled way to handle missing data? ... How do I combine the results across the multiply imputed sets of data? ... Why can't I just impute once?
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www.stat.psu.edu/~jls/mifaq.html
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Additions to PROC MI include the TRANSFORM statement to transform variables before performing the imputation, autocorrelation and iteration plots, a monotone-data MCMC method to impute just enough values to achieve a monotone missing pattern for the imputed data, and the EM statement to derive the MLE and related...
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www.sas.com/rnd/app/da/new/dami.html
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knnimpute - Impute missing data using nearest-neighbor method ... knnimpute(Data) replaces NaNs in Data with the corresponding value from the nearest-neighbor column. The nearest-neighbor column is the closest column in Euclidean distance. If the corresponding value from the nearest-neighbor column is also NaN,
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www.mathworks.com/access/helpdesk/help/toolbox/bioinfo/...
www.mathworks.com/access/helpdesk/help/toolbox/bioinfo/ref/knnimpute.html
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Downloadable! imputemok imputes missing item responses with the Mokken scaling as defined in Huisman and Molenaar (2001) [Huisman M. and Molenaar I. W., Imputation of missing scale data with item response models. ... This file is part of IDEAS, which uses RePEc data; [ Papers | Articles | Software | Books | Chapters |
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ideas.repec.org/c/boc/bocode/s456806.html
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Downloadable! imputerasch imputes missing binary data by a Rasch model. The parameters of the Rasch model are estimated on complete data, then the missing data are imputed from the estimated probability for each individual to response to each item. ... This file is part of IDEAS, which uses RePEc data...
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ideas.repec.org/c/boc/bocode/s456805.html
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Previous message: IMPUTE: Re: non-random missing data ... Next message: IMPUTE: Missing Data Mechanisms ... Of course you never know for sure which data are MAR and which are not, unless you know exactly what the process is that caused missingness (not something beyond your control like refusal). Also, I would suggest that...
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lists.utsouthwestern.edu/pipermail/impute/2001-June/000...
lists.utsouthwestern.edu/pipermail/impute/2001-June/000140.html
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Impute -- Imputations in Data Analysi ... The topic of this list is imputations in data analysis. Simply put, an imputation is an "intelligent guess" about the value of a missing piece of information. Several imputation methods have been developed, and statisticians are conducting research on existing methods as well...
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lists.utsouthwestern.edu/mailman/listinfo/impute
lists.utsouthwestern.edu/mailman/listinfo/impute
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"Data from the 1987 [U.S.] National Medical Expenditure Survey, Institutional Population Component were used to characterize partial and complete respondents with respect to outcome measures based on event history data....The results indicated that ... Title: An evaluation of a method used to impute residence data.
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www.popline.org/docs/1055/241319.html
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This function, when used with da.mix or dabipf.mix, can be used to create proper multiple imputations of missing data under the general location model with or without restrictions.
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www.stat.ucl.ac.be/ISdidactique/Rhelp/library/mix/html/...
www.stat.ucl.ac.be/ISdidactique/Rhelp/library/mix/html/imp.mix.html
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