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07-11-2017 09:51 AM

Hi everyone,

I am doing simulations to test **multiple imputation** procedures implemented in **PROC MI**.

For one of my datasets, I had the following **error message** :

ERROR: The set of classification levels for centre, generated for the imputed variable y_4, does

not include the level c3 for observations that have missing y_4 values.

It occured when I was imputing with the **MONOTONE REGRESSION** technique (on a monotone dataset, of course).

The **code below** (on SAS V9.4) reproduces such error:

```
DATA myData;
INPUT centre $ y_1 y_2 y_3 y_4;
DATALINES;
c3 11 27 22 .
c3 10 14 21 .
c3 2 21 15 .
c3 1 10 12 .
c2 24 57 21 12
c2 3 21 14 7
c2 2 45 65 12
c2 1 2 3 4
c1 4 5 12 1
c1 12 32 54 12
c1 15 12 32 14
c1 14 21 10 12
;
RUN;
PROC MI DATA=myData OUT=imputed;
CLASS centre;
VAR centre y_1 y_2 y_3 y_4;
MONOTONE REG;
RUN;
```

But with **FCS REGRESSION**, no problem !

```
PROC MI DATA=myData OUT=imputed;
CLASS centre;
VAR centre y_1 y_2 y_3 y_4;
FCS REG;
RUN;
```

Yet, the **SAS user guide **for PROC MI (pdf version available here) seems to assert that for monotone datasets, **FCS REGRESSION** fill-in phase acts like a **MONOTONE REGRESSION** (page 5894 to 5895 and 5902 to 5903).

How to explain that the error occurs only for **MONOTONE REGRESSION **?

Thanks in advance

Accepted Solutions

Solution

2 weeks ago

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3 weeks ago

You are exactly right. With FCS, the problem should also surface.

I suspect that this is an oversight in the development that does not catch the missing level and you should report it to Technical Support.

http://support.sas.com/ctx/supportform/createForm

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Solution

2 weeks ago

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3 weeks ago

You are exactly right. With FCS, the problem should also surface.

I suspect that this is an oversight in the development that does not catch the missing level and you should report it to Technical Support.

http://support.sas.com/ctx/supportform/createForm