Thank you. What could be a "User Error"? where could I be making a mistake?
I cannot use a lm because my data is not normal, is categorical (count data). So my first option was Poisson, but had severe overdispersion problems so I used Binomial Negative as an option. Thank you for taking the time to answer my questions. Lucas. 2012/3/7 peter dalgaard <pda...@gmail.com> > > On Mar 7, 2012, at 15:02 , Lucas wrote: > > > Hi Pascal. > > > > I applied my analysis in time. I have 25 fire seasons, each season starts > > on November and ends up on April (our summer) > > Hey, why are you worrying about regression coefficients. _Everything_ is > upside-down at your place... ;-) > > > , so I have used them as > > independent observations. I know that assumption it could be wrong, but > is > > the only way I can use the information available. > > > > As a general matter, there are three possibilities > > 1) User error > 2) Method artifact > 3) Counterintuitive (but true) relation > > and you really need to keep the possibility of 3) in mind rather than > poking around hoping that the counterintuitive signs would go away by > themselves. > > To investigate, I think I would make some stabs that try to get closer to > the raw data. If you produce a plot showing that the average number of > fires is increasing with temperature and a model fit with temperature as > the only predictor apparently shows the opposite, then I'd suspect a user > error causing coefficients not to mean what you think they mean. > > > > > Thank you. > > > > 2012/3/7 Pascal Oettli <kri...@ymail.com> > > > >> Hi Lucas, > >> > >> Do you apply your analysis in time or in space? > >> > >> Regards, > >> Pascal > >> > >> > >> > >> ----- Mail original ----- > >> De : Lucas <lpchaparro...@gmail.com> > >> à : r-help@r-project.org > >> Cc : > >> Envoyé le : Mercredi 7 mars 2012 22h34 > >> Objet : [R] Problems with generalized linear model (glm) coefficients. > >> > >> Hello to everyone. > >> > >> I´m writing you because I´m feeling a bit frustrated with my work. > >> > >> My work consists in finding the relation between the amount of fires > and > >> the weather, so, my response variable is the amount of fires in a fire > >> season and the explanatory variables are the temperature, the amount of > >> precipitation and the some othersâ. my problem is this; I keep getting > the > >> wrong sign in the coefficients estimated, I get a negative sign for > >> temperature and a positive sign for precipitation, which is > unreasonable, > >> the greater the temperature I would expect more fire, on the contrary, > the > >> greater the precipitation I would expect less fires. So far I have deal > >> with overdispersion, multicollinearity and the amount of zeroes through > >> passing from Poisson to Negative Binomial and Hurdle. I believe I have > >> used all my options and still have the wrong signs on my coefficients. > >> > >> Do I have more options? What does it mean that I keep getting those > signs? > >> > >> If anyone could help me I would really appreciate it. > >> > >> Thank you. > >> > >> > >> Lucas. > >> > >> [[alternative HTML version deleted]] > >> > >> > >> ______________________________________________ > >> R-help@r-project.org mailing list > >> https://stat.ethz.ch/mailman/listinfo/r-help > >> PLEASE do read the posting guide > >> http://www.R-project.org/posting-guide.html > >> and provide commented, minimal, self-contained, reproducible code. > >> > >> > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help@r-project.org mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > -- > Peter Dalgaard, Professor > Center for Statistics, Copenhagen Business School > Solbjerg Plads 3, 2000 Frederiksberg, Denmark > Phone: (+45)38153501 > Email: pd....@cbs.dk Priv: pda...@gmail.com > > [[alternative HTML version deleted]]
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