mice
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amices
Multivariate Imputation by Chained Equations
The change requested in #426 and implemented in #432 has the side-effect of having `mice` return the exactly same set of imputed values on each instantiation of the function. The...
lower.tail=FALSE instead of the complement increases numerical precision for very small p-values. See #487
New imputation method for individual patient data (IPD) and cluster data that follow a MNAR mechanism according to the Heckman selection model.
[I posted this question to stackoverflow](https://stackoverflow.com/questions/72758276/pooled-average-marginal-effects-from-survey-weighted-and-multiple-imputed-data), which contains a reproducible example. If this conversation isn't appropriate to Github issues, please let me know. I thought it would be interesting to...
Hi, I have performed an imputation several weeks ago that I am now wanting to reproduce, but I keep getting different results and I do not understand why. I am...
Added error messages for the number of imputations and the number of iterations in the `mids` object (should be > 1 and > 2, respectively). And added an interpretation paragraph...
I am following suggestions of the book of van Buuren (2018), p. 114f, to first impute (a few) single missing values that destroy monotone missingness pattern by a simple random...
Hello, I believe there is a minor coding issue on line 49 of the function code 'ampute'. The line of code is supposed to match the length of frequencies/frequency vector...
Does the automatic pool() function count a random effect (e.g., a random intercept) as a parameter in calculating the degrees of freedom for a mixed model? I ask because I...
Hi there, thanks for the excellent package! I was pooling some data and noticed some (highly significant) p-values were coming out as 0 which then messes with multiple comparisons correction....