[R] fitted values from lmer (lme4 0.98)

Tue Jan 17 22:00:38 CET 2006

Douglas Bates <dmbates at gmail.com> writes:

> On 1/16/06, Daniel A. Powers <dpowers at 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 at 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 $-1òülmer.ranefòý
> [[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             Øster Farimagsgade 5, Entr.B
  c/ /'_ --- Dept. of Biostatistics     PO Box 2099, 1014 Cph. K
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