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Re: st: RE: How to generate binary y?
From
Nick Cox <[email protected]>
To
[email protected]
Subject
Re: st: RE: How to generate binary y?
Date
Fri, 4 May 2012 07:06:18 +0100
I think most people round to the nearest integer, so
-round(predicted,1)- rounds 0.5 up to 1 and lower values to 0. There
is no need to round unless you want to impute or predict at individual
level.
Nick
On Thu, May 3, 2012 at 11:04 PM, Sumedha Gupta
<[email protected]> wrote:
> Thank you so much for your response. After I predict out of sample how
> do I allocate 0/1 to the continuous predicted value i.e. what is the
> cut off? Probably this is a very basic question but I will really
> appreciate your help.
On Thu, May 3, 2012 at 3:49 PM, Nick Cox <[email protected]> wrote:
>> Sounds as if you just need to use -predict- after -probit-. -predict- will happily predict out-of-sample so long as all predictors in the model are non-missing.
Sumedha Gupta
>> I have 2 samples one in which both x and y are observed and the other
>> in which only the x's are observed. Y is binary and some of the x's
>> are binary as well. I ran a probit of y on x for sample 1 and got all
>> the betas. Now using these beta's would it be possible to generate y
>> in sample 2 as well? This would be easy to do in the linear case...
>> but for a probit is there a command to do that?
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