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

From: Douglas Bates <dmbates_at_gmail.com>
Date: Wed 18 Jan 2006 - 06:17:57 EST

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

> (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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