Here is the question. Instead of generating a value equal to the mean
for each missing value, how can we make a random generation of values
that have the same mean but normally distributes within the range of
two SD.
As a concrete example. One continuous variable can be from 1 to 100.
The mean is 33. The SD is 12. There are 4000 cases and 20 % missing
values.
So insteand of attributing the value of 33 for all missing values, I
would like that the new created values for the 20 % missing have a
mean of 33 but would be randomly assigned and would range from 21 to
45.
Anyone is capable of doing so?
If you have v17 or later, why not use MULTIPLE IMPUTATION?
--
Bruce Weaver
bwe...@lakeheadu.ca
http://sites.google.com/a/lakeheadu.ca/bweaver/Home
"When all else fails, RTFM."
This sounds like a very bad idea.
Here is how to do it.
First, replace the Missing's with the mean, and create
an indicator variable (0/1 for No/Yes Missing) - just like
you would use if you wanted to include the variable and
its indicator in an ordinary regression.
Then generate your truncated normal deviation-scores--
mean= 33; SD= 12; tests to truncate or drop extremes;
add the Deviation-score to the variable.
--
Rich Ulrich