Hello Thierry, Thank you for your quick response. Sorry, but I am not sure if I follow what you said. I get the following outputs from the two models: > coef(lmer(Reaction ~ Days + (1| Subject), sleepstudy)) Subject (Intercept) Days 308 292.1888 10.46729 309 173.5556 10.46729 310 188.2965 10.46729 330 255.8115 10.46729 331 261.6213 10.46729 332 259.6263 10.46729 333 267.9056 10.46729 334 248.4081 10.46729 335 206.1230 10.46729 337 323.5878 10.46729 349 230.2089 10.46729 350 265.5165 10.46729 351 243.5429 10.46729 352 287.7835 10.46729 369 258.4415 10.46729 370 245.0424 10.46729 371 248.1108 10.46729 372 269.5209 10.46729
> coef(lm(Reaction ~ Days + Subject, sleepstudy)) (Intercept) 295.03104 Days 10.46729 Subject309 -126.90085 Subject310 -111.13256 Subject330 -38.91241 Subject331 -32.69778 Subject332 -34.83176 Subject333 -25.97552 Subject334 -46.83178 Subject335 -92.06379 Subject337 33.58718 Subject349 -66.29936 Subject350 -28.53115 Subject351 -52.03608 Subject352 -4.71229 Subject369 -36.09919 Subject370 -50.43206 Subject371 -47.14979 Subject372 -24.24770 Now, what I expected is the following: - 'Intercept' of model-2 to match with Intercept of Subject-308 of model-1 - 'Intercept+Subject309' of model-2 to match with Intercept of Subject-309 of model-1 - and so on... What am I missing here? If it is difficult to explain this, can you alternately answer the following: "Is it possible to define the 'lm' and 'lmer' models above so they produce the same results (at least in terms of predictions)?" Thanks again. Utkarsh Singhal 91.96508.54333 On 12 July 2016 at 19:15, Thierry Onkelinx <thierry.onkel...@inbo.be> wrote: > The parametrisation is different. > > The intercept in model 1 is the effect of the "average" subject at days == > 0. > The intercept in model 2 is the effect of the first subject at days == 0. > > ir. Thierry Onkelinx > Instituut voor natuur- en bosonderzoek / Research Institute for Nature and > Forest > team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance > Kliniekstraat 25 > 1070 Anderlecht > Belgium > > To call in the statistician after the experiment is done may be no more > than asking him to perform a post-mortem examination: he may be able to say > what the experiment died of. ~ Sir Ronald Aylmer Fisher > The plural of anecdote is not data. ~ Roger Brinner > The combination of some data and an aching desire for an answer does not > ensure that a reasonable answer can be extracted from a given body of data. > ~ John Tukey > > 2016-07-12 15:35 GMT+02:00 Utkarsh Singhal <utkarsh....@gmail.com>: > >> Hi experts, >> >> While the slope is coming out to be identical in the two methods below, >> the >> intercepts are not. As far as I understand, both are formulations are >> identical in the sense that these are asking for a slope corresponding to >> 'Days' and a separate intercept term for each Subject. >> >> # Model-1 >> library(lmer) >> coef(lmer(Reaction ~ Days + (1| Subject), sleepstudy)) >> >> # Model-2 >> coef(lm(Reaction ~ Days + Subject, sleepstudy)) >> >> Can somebody tell me the reason? Are the above formulations actually >> different or is it due to different optimization method used? >> >> Thank you. >> >> Utkarsh Singhal >> 91.96508.54333 >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> 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 -- To UNSUBSCRIBE and more, see 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.