On Jun 27, 2011, at 10:02 PM, Lao Meng wrote:
> Hi all,I have some questions about the covariants of regression.
>
> My target: To explore the trend of CD4 level through a period of time.
>
> Response variable: CD4 count
> Explanatory variable:time
>
> Also, the demology information is available,such as
> gender,occupation,income
> level...
>
> Q1,Are these variables of demology information called covariant?
> Q2,How can I correct the impact of "covariant" so that I can get
the
> "corrected result" of CD4's change through the time period?
> Q3,How to treat the covariants in regression?I've looked up to many
> papers
> of R on regression,which treat the covariant in the same
>
> way as the Explanatory variable,like following:
> lm(CD4 ~ time + gender + income)
Yes that seems pretty standard practice. It does, of course, force the
relationships to a) be linear and b) means that a single slope and
intercept are estimated for each variable, neither of a} or b}
assumptions may be true.>
>> From above expression of regression,it's obvious that the response
>> variables
> and covariants are treated the same way,
In what sense are you making that claim? True they are both numeric,
but what else are you saying?
--
David
> but acturally
>
> they are totally different.
>
>
>
> Thanks for your help.
>
> My best.
>
> [[alternative HTML version deleted]]
>
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David Winsemius, MD
West Hartford, CT