Re: st: Marginsplot on backtransformed data

[Richard Williams <richardwilliams.ndu@gmail.com>]

Patrick Royston's -marginscontplot- (available from SSC) can be used 
when you've done a log or other transformation of an independent 
variable. See the help file example entitled "Example using a 
log-transformed covariate".

For a dependent variable, I think you can use the glm command, at 
least some of the time. You should get a 2nd opinion on this, e.g. 
Austin Nichols is much better with these sorts of things than I am. 
When the dependent variable has been transformed I believe it is 
often better to use glm anyway. In the following you don't get 
exactly the same results from regress and glm but I don't think you 
are supposed to (and the results are similar).

webuse nhanes2f, clear
gen sqweight = weight ^.5
reg sqweight i.race
margins race
marginsplot, name(regress)
glm weight i.race, link(power .5)
margins race
marginsplot, name(glm)

At 01:58 AM 12/19/2013, you wrote:
> Hi All,
>
> I am using the marginsplot function to plot graphs that take into
> account adjustments I have carried out following a regression
> analysis. Since my regression analysis contains data that has been
> normalised by square root transformation, the plots are not that
> easily interpretable. Is there a way to plot the same graphs but
> somehow tell Stata/marginsplot to use back-transformed results? And
> does the margins function store predictions that can be accessed?
>
> I am using Stata 13 and the following are examples of commands I am using:
>
> regress squareroot_transformed_variable i.categorical1 i.categorical2
>
> margins categorical1
>
> marginsplot
>
> Kind Regards
> Herbert
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Richard Williams, Notre Dame Dept of Sociology
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