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Re: st: Very high t- statistics and very small standard errors
From
Laurie Molina <[email protected]>
To
[email protected]
Subject
Re: st: Very high t- statistics and very small standard errors
Date
Wed, 2 May 2012 09:08:24 -0500
Regarding DW, as in Chen (2003) I created and index variable for each
observation, as if it where the "time" variable.
Ok, I will look for clusters.
Thanks again!
Chen, X., Ender, P., Mitchell, M. and Wells, C. (2003). Regression with Stata,
On Wed, May 2, 2012 at 8:34 AM, Nick Cox <[email protected]> wrote:
> If your data are not time series, it is hard to see that Durbin-Watson
> tests make any sense. (It is also puzzling how you managed to
> calculate them.)
>
> Alan Feiveson's point was I think to wonder about any cluster or
> clumping structure: for example, millions of people would often show
> some similarities within families or communities.
>
> Nick
>
> On Wed, May 2, 2012 at 2:09 PM, Laurie Molina <[email protected]> wrote:
>> Thank you all.
>> I will try adding more variables to the model, and think on the
>> economic vs statistical significance of the results (I will look for
>> the appropiate null hypothesis, as opossed to the default zero).
>> Regarding the independe of the observations I ran Durbin Watson
>> (although my data is non time series), and the error term do not seem
>> to be correlated among observations.
>> Regards and thanks again,
>> LM
>>
>> On Tue, May 1, 2012 at 7:36 PM, David Hoaglin <[email protected]> wrote:
>>> Laurie,
>>>
>>> It's unusual to see such a large number of observations and so few
>>> explanatory variables. Often, as the amount of data increases, the
>>> complexity of the model grows. Do those 4 million observations
>>> actually have no structure other than that described by the 6
>>> explanatory variables?
>>>
>>> David Hoaglin
>>>
>>> On Mon, Apr 30, 2012 at 8:54 PM, Laurie Molina <[email protected]> wrote:
>>>> Hi everybody,
>>>> I'm running some OLS with around 4 million observations and 6
>>>> explanatory variables.
>
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