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

From |
"Nick Cox" <n.j.cox@durham.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: Graphs With Log Scale: A Bug? |

Date |
Wed, 28 May 2008 13:21:46 +0100 |

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" <dashkeyev@iet.ru> 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: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Graphs With Log Scale: A Bug?***From:*"Vladimir V. Dashkeyev" <dashkeyev@iet.ru>

**References**:**st: Graphs With Log Scale: A Bug?***From:*"Vladimir V. Dashkeyev" <dashkeyev@iet.ru>

**Re: st: Graphs With Log Scale: A Bug?***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**Re: st: Graphs With Log Scale: A Bug?***From:*"Vladimir V. Dashkeyev" <dashkeyev@iet.ru>

- Prev by Date:
**Re: st: instrumental variable for quantile regression** - Next by Date:
**Re: st: Graphs With Log Scale: A Bug?** - Previous by thread:
**Re: st: Graphs With Log Scale: A Bug?** - Next by thread:
**Re: st: Graphs With Log Scale: A Bug?** - Index(es):

© Copyright 1996–2014 StataCorp LP | Terms of use | Privacy | Contact us | What's new | Site index |