Warning message with lmer function
The random effects variances are close to zero, which will cause lots of problems. This is possibly a numerical problem, as the values of the fixed effect estimates are small. Maybe you could try scaling the covariate before creating the polynomial terms. Ken
On 16/09/2009, at 8:17 PM, FMH wrote:
Dear All,
I have a set of data which consist of 1575 groups with 11
temperature values in each group. This temperature is recorded
across 11 different depths of the sea. The R script are shown below:
############################################################
#Temp : Temperature
#dp1, dp2, dp3 : covariate with respect to linear, quadratic and
cubic terms
#group : 1575 groups in which there are 11 observations in each group
#sub3 : Data set 1
#set3 : Data set 2
dp1 <- rep(rev(seq(1,51, by = 5)),1575)
dp2 <- dp1^2
dp3 <- dp1^3
group <- rep(1:1575, each = 11)
set3 <- data.frame(sub3, dp1, dp2, dp3)
(lm.lme3 <- lmer(Temp ~ dp1 + dp2 + dp3 + (dp1 + dp2 + dp3|group),
data = set3))
############################################################
I tried to fit a linear mixed model via lmer function, with all the
fixed and random effects are included, but there is a 'Warning'
message given after the output, as shown below.
##############################################
Linear mixed model fit by REML
Formula: Temp ~ dp1 + dp2 + dp3 + (dp1 + dp2 + dp3 | group)
Data: set3
AIC BIC logLik deviance REMLdev
65627 65743 -32799 65539 65597
Random effects:
Groups Name Variance Std.Dev. Corr
group (Intercept) 4.8336e-01 6.9524e-01
dp1 5.2199e-04 2.2847e-02 0.000
dp2 3.0528e-07 5.5252e-04 0.000 0.000
dp3 7.8888e-11 8.8819e-06 -0.966 0.000 0.000
Residual 1.9939e+00 1.4120e+00
Number of obs: 17325, groups: group, 1575
Fixed effects:
Estimate Std. Error t value
(Intercept) 1.363e+01 4.043e-02 337.1
dp1 -2.930e-01 6.328e-03 -46.3
dp2 3.924e-03 2.870e-04 13.7
dp3 -1.900e-05 3.628e-06 -5.2
Correlation of Fixed Effects:
(Intr) dp1 dp2
dp1 -0.739
dp2 0.616 -0.959
dp3 -0.563 0.904 -0.982
Warning message:
In mer_finalize(ans) : false convergence (8)
#############################################
Does the output given is valid? Could someone please advice on this
message.
Thank you
Fir
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