Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.
[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]
Re: st: stepwise and manual drop of variables
From
Rodrigo Briceño <[email protected]>
To
[email protected]
Subject
Re: st: stepwise and manual drop of variables
Date
Thu, 10 Feb 2011 15:26:54 -0600
thanks Phil, that's the cause of the problem!
2011/2/10 Phil Clayton <[email protected]>:
> Also, if there are any missing values in the variables then those observations will be excluded from the stepwise regression. When you drop such variables manually your number of observations will rise, whereas stepwise keeps them out of the analysis. So check the "Number of obs" in the output of the two methods.
>
> Phil
>
> On 11/02/2011, at 7:40 AM, Richard Williams wrote:
>
>> At 04:00 PM 2/10/2011, Rodrigo Briceño wrote:
>>> Dear Stata users. I would like to know if there is a difference when
>>> applying the command Stepwise(SW) and doing the elimination of
>>> variables manually.
>>
>> When you did it manually, did you, in fact, do it one step at a time? When doing backwards selection, you should drop one variable, rerun the regression, drop another variable, etc. If you just drop all the insignificant variables at once that is not the same as stepwise. The fact that pprom made it in to your final model with a p-value of .0644 indicates you did something wrong; it should have been dropped (assuming this isn't just a typo).
>>
>> I'll leave it to others to point out the problems with stepwise, but you should be aware of them if you aren't already.
>>
>>> I recently run this two models:
>>>
>>> 1. regress logliq logsap l1liq l2liq l3liq l4liq l1sap l2sap l3sap
>>> l4sap liqmk pprom sem dv if isin2==169 & ano>=2009
>>> 2. sw regress logliq logsap l1liq l2liq l3liq l4liq l1sap l2sap l3sap
>>> l4sap liqmk pprom sem dv if isin2==169 & ano>=2009, pr(.05)
>>>
>>> When I drop the variables with p-value greater than 0.05 I got as
>>> final variables: sem (0.0315) and pprom (0.0644): p-values in
>>> parenthesis
>>> If I apply the second option my final variables are: sem (0.022), dv
>>> (0.027) and pprom (0.007).
>>>
>>> My final goal is to reduce the model with all the variables to a
>>> simple model with just significant variables (0.05 or lower p-value).
>>>
>>> Is there an explanation for the difference when applying both methods?
>>> in that case would be better to do the elimination of variables one by
>>> one?
>>>
>>> thanks for your help.
>>>
>>> --
>>> Rodrigo Briceño
>>> Economist
>>> [email protected]
>>> MSN: [email protected]
>>> SKYPE: rbriceno1087
>>>
>>> *
>>> * For searches and help try:
>>> * http://www.stata.com/help.cgi?search
>>> * http://www.stata.com/support/statalist/faq
>>> * http://www.ats.ucla.edu/stat/stata/
>>
>> -------------------------------------------
>> Richard Williams, Notre Dame Dept of Sociology
>> OFFICE: (574)631-6668, (574)631-6463
>> HOME: (574)289-5227
>> EMAIL: [email protected]
>> WWW: http://www.nd.edu/~rwilliam
>>
>>
>> *
>> * For searches and help try:
>> * http://www.stata.com/help.cgi?search
>> * http://www.stata.com/support/statalist/faq
>> * http://www.ats.ucla.edu/stat/stata/
>
>
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
--
Rodrigo Briceño
Economist
[email protected]
MSN: [email protected]
SKYPE: rbriceno1087
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/