leiden85


Subset of data from the Leiden 85+ study


datasets

Multiple imputation using Fully Conditional Specification (FCS)
implemented by the MICE algorithm. Each variable has its own imputation
model. Built-in imputation models are provided for continuous data
(predictive mean matching, normal), binary data (logistic regression),
unordered categorical data (polytomous logistic regression) and ordered
categorical data (proportional odds). MICE can also impute continuous
two-level data (normal model, pan, second-level variables). Passive
imputation can be used to maintain consistency between variables. Various
diagnostic plots are available to inspect the quality of the imputations.

Stef van Buuren

mice

Multivariate Imputation by Chained Equations

leiden85 function

<code>leiden85</code> is a data frame with 956 rows and 336 columns.

Format

Lagaay, A. M., van der Meij, J. C., Hijmans, W. (1992). Validation of
medical history taking as part of a population based survey in subjects aged
85 and over. Brit. Med. J., 304(6834), 1091-1092. Izaks, G. J., van Houwelingen, H. C., Schreuder, G. M., Ligthart, G. J.
(1997). The association between human leucocyte antigens (HLA) and mortality
in community residents aged 85 and older. Journal of the American
Geriatrics Society, 45(1), 56-60. Boshuizen, H. C., Izaks, G. J., van Buuren, S., Ligthart, G. J. (1998).
Blood pressure and mortality in elderly people aged 85 and older: Community
based study. Brit. Med. J., 316(7147), 1780-1784. Van Buuren, S., Boshuizen, H.C., Knook, D.L. (1999) Multiple imputation of
missing blood pressure covariates in survival analysis. Statistics in
Medicine, 18, 681--694. van Buuren, S. (2012). Flexible Imputation of Missing Data. Boca
Raton, FL: Chapman & Hall/CRC Press.

leiden85: Leiden 85+ study

Description

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