imputing missing values based on categories of other variables

[Romil Pandey]

level	typeofA	typeofB	typeofC	var
A	x	.	.	.
A	y	.	.	55
B	.	p	.	10.5
B	.	q	.	.
B	.	r	.	20
C	.	.	s	43.1
C	.	.	t	.

I have a dataset that looks something like this. There are levels, and for each level, there are different types. To impute missing values for “var”, I want to use the mean (or median) of “var” in the following way.

If there is a missing value in var:
if the observation belongs to level A

• If typeofA = x, then impute with mean(var) of x
• if typeofA = y, then impute with mean(var) of y
• and so on

and similarly for B and C......

There are a lot of types for each level, so i don't know if I can hardcode this. Maybe I have to use a loop for this, but I am really lost and don’t know where to begin.

[Andrew Musau]

You need to either provide a more elaborate example or explain better what you want to achieve.

If there is a missing value in var:
if the observation belongs to level A

• If typeofA = x, then impute with mean(var) of x

In your table, there is only one observation with "x", and it has a missing value on "var". What do you mean with "impute with mean(var) of x"?