multiple imputation

I have missing values from a few subjects due to instrumentation
not working. My data set is N=283 data points. For some subjects
i have 60 data points missing max. 

I tried to use Amelia 2  to impute the missing values but i am
getting a negative number and i am sure this is wrong because
its biologically implausible to have a negative number for what
i am measuring.

Does anyone have any suggestions on how to proceed?
Thanks.
--

Amelia assumes that the data are multivariate Normal.
This intrinsically allows negative values. One possible
way to avoid negative values for a variable which must
be positive is to use the logarithm of that variable
in your analysis, and proceed as though that had the
multivariate Normal distribution.

Then you can back-transform after imputation.

However, whether that is advisable, or whether you should
adopt some other approach, can depend on many considerations
which can only be inferred from background information about
the context in which the data were obtained.

I note that you seem to call the variable with missing
values "max". If that is, say, the maximum observed value
of a variable over a period of time, then it may be more
appropriate to treat it as having an "extreme value" type
of distribution, and transform it accordingly.

Better targeted advice might be given if you can supply
more detail about what is being observed, what is measured
and how, etc.

Ted.

--------------------------------------------------------------------
E-Mail: (Ted Harding) <ted.harding at wlandres.net>
Fax-to-email: +44 (0)870 094 0861
Date: 21-Apr-11                                       Time: 19:44:49
------------------------------ XFMail ------------------------------