[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

Re: st: Graphs With Log Scale: A Bug?

From   "Vladimir V. Dashkeyev" <[email protected]>
To   [email protected]
Subject   Re: st: Graphs With Log Scale: A Bug?
Date   Thu, 29 May 2008 16:31:58 +0400


I understand that "make it work for me" approach is not acceptable.
But before asking I made several attempts and failed. I do appreciate
your help, I managed to get what I wanted thanks to your advice.

Thank you again,

On Wed, May 28, 2008 at 5:48 PM, Nick Cox <[email protected]> wrote:
> 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.
> *
> *   For searches and help try:
> *
> *
> *
*   For searches and help try:

© Copyright 1996–2024 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index