Re: [R] fitted values from lmer (lme4 0.98)

From: Peter Dalgaard <p.dalgaard_at_biostat.ku.dk>
Date: Wed 18 Jan 2006 - 08:00:38 EST

Douglas Bates <dmbates@gmail.com> writes:

> On 1/16/06, Daniel A. Powers <dpowers@mail.la.utexas.edu> wrote:
> >
> > -- R-List
> >
> > Can someone tell me how to get fitted values etc. after fitting lmer?
> > for example, from lme, I can fit mod.1 <- lme(....) and get fitted values, coefficients, etc. in this way
> >
> > mod.1$fitted[,1] or mod.1$fitted[,2] etc.
> >
> > It seems lmer uses "slots" that are unfamiliar to me.
>
> The preferred way is to use the extractor functions fitted, fixef,
> ranef and coef.
>
> Using the recently uploaded version 0.995-1 of the Matrix package we get

But, at least with 0.99-6 (sorry for falling way behind, but I'd rather not upgrade just now...), fitted(fm1) are effectively BLUPs. If you want to get the estimated mean values, you need something like

model.matrix(fm1@terms,sleepstudy) %*% fixef(fm1)

I realize that since lmer models are not necessarily hierarchical, it takes more than cloning the "level" argument from fitted.lme, but it could be useful to at least have a "level=0" equivalent.  

> > (fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy))
> Linear mixed-effects model fit by REML
> Formula: Reaction ~ Days + (Days | Subject)
> Data: sleepstudy
> AIC BIC logLik MLdeviance REMLdeviance
> 1753.628 1769.593 -871.8141 1751.986 1743.628
> Random effects:
> Groups Name Variance Std.Dev. Corr
> Subject (Intercept) 612.090 24.7405
> Days 35.072 5.9221 0.066
> Residual 654.941 25.5918
> # of obs: 180, groups: Subject, 18
>
> Fixed effects:
> Estimate Std. Error t value
> (Intercept) 251.4051 6.8246 36.838
> Days 10.4673 1.5458 6.771
>
> Correlation of Fixed Effects:
> (Intr)
> Days -0.138
> > fixef(fm1)
> (Intercept) Days
> 251.40510 10.46729
> > ranef(fm1)
> An object of class $-1˛Řlmer.ranef˛ř
> [[1]]
> (Intercept) Days
> 308 2.2585636 9.1989720
> 309 -40.3985870 -8.6197013
> 310 -38.9602563 -5.4488780
> 330 23.6905071 -4.8143326
> 331 22.2602104 -3.0698958
> 332 9.0395288 -0.2721711
> 333 16.8404364 -0.2236253
> 334 -7.2325817 1.0745765
> 335 -0.3336930 -10.7521594
> 337 34.8903592 8.6282824
> 349 -25.2101185 1.1734156
> 350 -13.0699625 6.6142058
> 351 4.5778374 -3.0152575
> 352 20.8635979 3.5360123
> 369 3.2754538 0.8722165
> 370 -25.6128786 4.8224661
> 371 0.8070403 -0.9881552
> 372 12.3145428 1.2840291
>
> > coef(fm1)
> $Subject
> (Intercept) Days
> 308 253.6637 19.6662580
> 309 211.0065 1.8475846
> 310 212.4448 5.0184079
> 330 275.0956 5.6529533
> 331 273.6653 7.3973901
> 332 260.4446 10.1951148
> 333 268.2455 10.2436606
> 334 244.1725 11.5418624
> 335 251.0714 -0.2848734
> 337 286.2955 19.0955683
> 349 226.1950 11.6407015
> 350 238.3351 17.0814918
> 351 255.9829 7.4520285
> 352 272.2687 14.0032983
> 369 254.6806 11.3395024
> 370 225.7922 15.2897520
> 371 252.2121 9.4791308
> 372 263.7196 11.7513151
>
> > fitted(fm1)
> [1] 253.6637 273.3299 292.9962 312.6624 332.3287 351.9950 371.6612 391.3275
> [9] 410.9937 430.6600 211.0065 212.8541 214.7017 216.5493 218.3969 220.2444
> [17] 222.0920 223.9396 225.7872 227.6348 212.4448 217.4633 222.4817 227.5001
> [25] 232.5185 237.5369 242.5553 247.5737 252.5921 257.6105 275.0956 280.7486
> [33] 286.4015 292.0545 297.7074 303.3604 309.0133 314.6663 320.3192 325.9722
> [41] 273.6653 281.0627 288.4601 295.8575 303.2549 310.6523 318.0497 325.4470
> [49] 332.8444 340.2418 260.4446 270.6397 280.8349 291.0300 301.2251 311.4202
> [57] 321.6153 331.8104 342.0056 352.2007 268.2455 278.4892 288.7329 298.9765
> [65] 309.2202 319.4638 329.7075 339.9512 350.1948 360.4385 244.1725 255.7144
> [73] 267.2562 278.7981 290.3400 301.8818 313.4237 324.9656 336.5074 348.0493
> [81] 251.0714 250.7865 250.5017 250.2168 249.9319 249.6470 249.3622 249.0773
> [89] 248.7924 248.5076 286.2955 305.3910 324.4866 343.5822 362.6777 381.7733
> [97] 400.8689 419.9644 439.0600 458.1556 226.1950 237.8357 249.4764 261.1171
> [105] 272.7578 284.3985 296.0392 307.6799 319.3206 330.9613 238.3351 255.4166
> [113] 272.4981 289.5796 306.6611 323.7426 340.8241 357.9056 374.9871 392.0686
> [121] 255.9829 263.4350 270.8870 278.3390 285.7911 293.2431 300.6951 308.1471
> [129] 315.5992 323.0512 272.2687 286.2720 300.2753 314.2786 328.2819 342.2852
> [137] 356.2885 370.2918 384.2951 398.2984 254.6806 266.0201 277.3596 288.6991
> [145] 300.0386 311.3781 322.7176 334.0571 345.3966 356.7361 225.7922 241.0820
> [153] 256.3717 271.6615 286.9512 302.2410 317.5307 332.8205 348.1102 363.4000
> [161] 252.2121 261.6913 271.1704 280.6495 290.1287 299.6078 309.0869 318.5661
> [169] 328.0452 337.5243 263.7196 275.4710 287.2223 298.9736 310.7249 322.4762
> [177] 334.2275 345.9789 357.7302 369.4815
>
> I hope this helps.
>
> Doug Bates
>
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-- 
   O__  ---- Peter Dalgaard             ěster Farimagsgade 5, Entr.B
  c/ /'_ --- Dept. of Biostatistics     PO Box 2099, 1014 Cph. K
 (*) \(*) -- University of Copenhagen   Denmark          Ph:  (+45) 35327918
~~~~~~~~~~ - (p.dalgaard@biostat.ku.dk)                  FAX: (+45) 35327907

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Received on Wed Jan 18 08:17:58 2006

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