Please accept more responsibility for solving problems.
It is just a matter of (a) reading the help and (b) applying textbook formulae.
Here is a sketch:
local level = <your_choice, e.g. 95>
regress <whatever>
tempvar pred se ul ll
predict `pred'
predict `se', stdp
local level = (100 - `level') / 200
gen `ul' = `pred' + invttail(e(df_r), `level') * `se'
gen `ll' = `pred' - invttail(e(df_r), `level') * `se'
Nick
[email protected]
Vladimir V. Dashkeyev
Nick,
Thanks for the answer. I did not use -predict- since this approach
does not provide a quick way for drawing confidence intervals. If I'm
wrong and there is a way to draw CI, please, let me know about it.
Thank you,
Vladimir
On Wed, May 28, 2008 at 4:21 PM, Nick Cox <[email protected]> wrote:
> My advice is to use -predict- after each model fitted to save the results in separate variables. Then draw one graph to get you want. I wouldn't approach this via -lfit- or
> -lfitci-. That will also oblige you to make explicit what you are doing.
>
> Nick
>
> Vladimir V. Dashkeyev
>
> Thanks for the reply. I should have emphasized in the first message,
> that I run -lfitci- of X on ln(Y) in both scenarios. The difference is
> in the scatter plot. In the first scenario I use ln(Y), and in the
> second -- Y with log scale option. I expected to get the same linear
> prediction line and the same scatter plot.
>
> But after I posted that question, I compared the graphs once again and
> realized that the real problem is with the Y axis scale. If I draw a
> scatter and prediction line on the same Y axis, everything is fine.
> Yet if I draw the same scatter with 2 Y axes I get different range of
> values on Y1 and Y2 axes. I need two Y axes for overlaid drawing of
> the scatter with -yscale (log)- option and linear prediction of
> X-ln(Y). Setting range on both axes to the same values did not help.
> They are very close but still shifted a bit. So the arrangement of
> observations and prediction line is not correct. So it's not a bug,
> but still a problem I have to solve.
>
> Is there any way to "tie" axis Y1 with axis Y2?
>
> Maarten buis
>
>> --- "Vladimir V. Dashkeyev" <[email protected]> wrote:
>>> I drew a two-way plot with a linear prediction line -lfitci- of X on
>>> natural logarithm of Y. Next, I drew the plot of X on Y with log
>>> scale option -yscale(log)-.
>>>
>>> To my surprise regression line changed its slope. The slope is
>>> greater with the -yscale(log)- option. I used the same X axis and
>>> the second Y-axis for the linear prediction graph .
>>> Is this a bug or am I doing something wrong?
>>
>> This is not a bug: in the first scenario you are thinking that there is
>> a linear relationship between ln(Y) and X and you are showing the
>> predictions, while in the second scenario you are thingking that there
>> is a linear relationship between Y and X and then transforme the
>> predictions to a log scale. So the results are different because the
>> models are different.
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