I met with Marianne, a post doc in the School of Nursing in UNC-CH,

to discuss some remaining problems in her publication. Those

problems caused me confused as well, but my supervisor Mark didn't

have time to participate in our meeting last Friday. Hence, I stop

by Mark's office again today (Monday). There are some useful

conclusion after meeting with Mark.

The first question is whether Likelihood Ratio Test(LRT) is

suitable in comparing two models have the same independent

variables but some of them have differnt attributes. For example,

one variable is continuous in a Model, but how about using a

categorical one in the same model? That's the key point of this

question. The only confused thing is that LRT is only used in

nested model, but I am not sure whether this kind of situation is

the same. Mark told me it is because we can regard the continuse

one is a reduced model and the categorical one is full model in

that there are more variables in categorical one. Based on this

assumption, we can use LRT as usual.

The second question is more complicated. Marianne had already

finish the part of model selection, but just need a LRT to confirm

her final models are the best one. By using LRT, the decision

should be non-significant with large p-value, then we can have no

rejection of the null hypothesis which is reduced (final) model.

However, it is totally conflicted because the result is

significant. After checking the original SAS code, there is no

problem as well. However, Mark said, based on Marianne study

design, she needs to keep two important variables in this model

whatever it is significant or non-significant. After including the

two variables in this model, the conflict was eliminated. But, I

was still wondering whether one of them is highly overlapped with

another one because they are all geographic variables and have

highly similarity. I dropped out a less important one and fit the

model again, the result looked better. From this problem, we can

understand that we need to know more about variables before model

fitting, then we will decrease confusion from that.

The two solutions had already been emailed to Marianne. Hope she

will feel useful.

- Feb 27 Mon 2006 05:03
## Consulting Case Study -- No.20060224

## 留言列表 (2)

若個別的p-value>.05，

但model卻是significant，

是因為variable之間有highly similarity嗎？

還是...？

What do you mean "model is significant"? There

is no criterion to say this model is

significant. I just know there are some

criteria to say "the model is better than

others".

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