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From |
"Vladimir V. Dashkeyev" <dashkeyev@iet.ru> |

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Wed, 28 May 2008 15:47:37 +0400 |

Maarten, Sorry for the misspelled name. Situation is a bit hectic here. Best, Vladimir On Wed, May 28, 2008 at 3:45 PM, Vladimir V. Dashkeyev <dashkeyev@iet.ru> wrote: > Martin, > > 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? > > Thanks, > Vladimir > > On Wed, May 28, 2008 at 2:24 PM, Maarten buis <maartenbuis@yahoo.co.uk> wrote: >> --- "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. >> >> -- Maarten >> >> >> ----------------------------------------- >> Maarten L. Buis >> Department of Social Research Methodology >> Vrije Universiteit Amsterdam >> Boelelaan 1081 >> 1081 HV Amsterdam >> The Netherlands >> >> visiting address: >> Buitenveldertselaan 3 (Metropolitan), room Z434 >> >> +31 20 5986715 >> >> http://home.fsw.vu.nl/m.buis/ >> ----------------------------------------- >> >> >> __________________________________________________________ >> Sent from Yahoo! Mail. >> A Smarter Email http://uk.docs.yahoo.com/nowyoucan.html >> * >> * 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/ >> > * * 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/

**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>

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