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:
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#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))
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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.
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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)
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Does the output given is valid? Could someone please advice on this message.
Thank you
Fir