I wonder if someone could help me… I get the output below when I use the lmer function from the lme4 package, and I don’t seem to find an answer to what dam.1 and sire.1 stand for.

Best regards,

Elin Renborg


> lmer.tot <- lmer(metsucc ~ matrix + salt + (1 | sire) + (1 | dam) + (1 | sire/salt) + (1 | dam/salt), weights=baseS, data = gf)
> summary(lmer.tot)
Linear mixed model fit by REML ['lmerMod']
Formula: metsucc ~ matrix + salt + (1 | sire) + (1 | dam) + (1 | sire/salt) +      (1 | dam/salt)
   Data: gf

REML criterion at convergence: 240.7323

Random effects:
 Groups    Name        Variance  Std.Dev.
 salt.dam  (Intercept) 1.073e-03 3.275e-02
 salt.sire (Intercept) 5.051e-05 7.107e-03
 dam       (Intercept) 2.313e-19 4.810e-10
 sire      (Intercept) 1.943e-10 1.394e-05
 dam.1     (Intercept) 2.249e-18 1.500e-09
 sire.1    (Intercept) 7.323e-05 8.558e-03
 Residual              6.299e-03 7.936e-02
Number of obs: 265, groups: salt:dam, 90; salt:sire, 90; dam, 18; sire, 18

Fixed effects:
            Estimate Std. Error t value
(Intercept)  0.15144    0.01336   11.34
matrixF2     0.07083    0.01530    4.63
matrixF3    -0.03134    0.01525   -2.06
matrixF4     0.04096    0.01529    2.68
matrixF5     0.03625    0.01527    2.37
matrixF6     0.03222    0.01522    2.12
salt27.5     0.63279    0.01219   51.90
salt30.5     0.61029    0.01220   50.01
salt33.5     0.02474    0.01223    2.02
salt36.5    -0.17741    0.01228  -14.45

The experimental design is as follows (with one family missing):
6 matrices of 9 crosses (3 males x 3 females) yielding 53 families (one missing).
All families were exposed to 5 different salinities (salt) yielding 265 observations.
Male/sire and female/dam effects are treated as random and matrix and salt as fixed.

> str(gf)
'data.frame': 265 obs. of  16 variables:
 $ pop    : Factor w/ 1 level "Gullmarsfjorden": 1 1 1 1 1 1 1 1 1 1 ...
 $ date   : Factor w/ 3 levels "17/07/2011","18/07/2011",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ matrix : Factor w/ 6 levels "F1","F2","F3",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ animal : Factor w/ 53 levels "GF01","GF02",..: 1 1 1 1 1 2 2 2 2 2 ...
 $ sire   : Factor w/ 18 levels "GS01","GS02",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ dam    : Factor w/ 18 levels "GD01","GD02",..: 1 1 1 1 1 2 2 2 2 2 ...
 $ sal    : num  24.5 27.5 30.5 33.5 36.5 24.5 27.5 30.5 33.5 36.5 ...
 $ cleav  : int  28 45 24 22 0 42 47 33 27 0 ...
 $ fert   : int  14 4 3 16 22 14 4 13 14 5 ...
 $ tot    : int  67 71 57 54 38 88 72 78 66 9 ...
 $ met    : int  14 31 19 6 0 29 38 24 0 0 ...
 $ larv   : int  0 6 5 1 0 1 6 14 0 0 ...
 $ base   : int  42 49 27 38 22 56 51 46 41 5 ...
 $ metsucc: num  0.333 0.633 0.704 0.158 0 ...
 $ salt   : Factor w/ 5 levels "24.5","27.5",..: 1 2 3 4 5 1 2 3 4 5 ...
 $ baseS  : num  6.48 7 5.2 6.16 4.69 …

__________________________________

Elin Renborg, PhD Student
Dept of Biological & Environmental Sciences - Tjärnö
University of Gothenburg
SE-452 96 Strömstad, Sweden















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