Dear Don,
I think taht all developed countreis shared the proplem of missing data on
collecting data on religion.
On the last Israeli census (1995) we omited the question of religion, and we
used other sources to impute (complete) the data like the Cnetral Population
Register (CPR).
So I think if you can use other sources to complete your data (maybe not
all) your missing data will be a random.
You can also use some details to impute your data. Details like names and
origion (country of birth) or using other members of the household or the
family.
To check your Impute, you can omit the data you collect, and add the data
from other sources. After that you can compair your new data with old data
(for people that answered).
Ahmad Hleihel
Director, Demography sector
Central Bureau Of Statistics
Israel
----- Original Message -----
From: "Donald Baken" <[EMAIL PROTECTED]>
To: <[EMAIL PROTECTED]>
Sent: 20 June, 2001 12:21 AM
Subject: IMPUTE: non-random missing data
> I am a new subscriber to this group so I hope that this question is not
too
> simple. I have looked at the archives but it does not seem to be covered.
>
> I am using SPSS for my analysis.
>
> I have both MCAR and non-random missing data. The non-random missing data
> comes from questions about religion where some people have just refused to
> answer any of the questions.
>
> I am planning to use EM to impute the missing data for the items with MCAR
> data. The non-random missing data is a bit trickier. I don't want to dump
> the items with non-random missing data because they are important. I can't
> dump the people who didn't answer the items because that would introduce
> bias. Although the SPSS manual suggests that EM is not suitable for data
> which is not missing at random I see that as my best option.
>
> What do people normally do in this sought of situation?
>
> Thanks
>
>
> Don Baken
> Don Baken
> Graduate Assisstant
> School of Psychology
> Massey University
> New Zealand
>
