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I´m doing a multiple imputation for a dataframe named "mydata" with this code:

library(mice)

imp<-mice(mydata,pred=pred,method="pmm", m=10)

Because the default argument for this is function is "seed=NA", the seed-number is chosen randomly. I would like to keep it like this, because i don´t know which number i should choose as a seed. But for replication i would like to know which seed this function chose for me. Is there a possibility to inspect the mids-object "imp" for the seed-value? Or should i just use a random number generator and set the seed to a generated value?

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SEMson
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    If it is not mentioned in documentation you can always use `str` with resulting object to check what is inside its guts. – Tim Dec 04 '14 at 12:43

1 Answers1

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If you look at the documentation, there is no such thing as a set.seed argument for mice function. There is, however a seed argument which takes an integer. If left alone, the integer is generated randomly.

An integer that is used as argument by the `set.seed()` for offsetting the random
number generator. Default is to leave the random number generator alone

You can choose your own integer. If you're stuck at what to choose, try your lucky number, or some random integer, with sky or architecture of your system being the limit.

The function sets seed in the following manner, which translates to "set seed only if specified, otherwise leave alone" as mentioned in the documentation.

   if (!is.na(seed))
        set.seed(seed)  ## FEH 1apr02
Roman Luštrik
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  • Thank you for your explanation! So, the randomly generated integer cannot be known afterwards. I´ll try my lucky number then ;) PS: I edited my post concerning set.seed=NA towards seed=NA. – SEMson Dec 04 '14 at 12:14
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    @user2982730 I think you want http://stackoverflow.com/questions/19614314/can-i-get-seed-somehow – Roman Luštrik Dec 04 '14 at 14:28