[R-sig-ME] Does corSymm() require balanced data?

Tip But |@w|@wt @end|ng |rom gm@||@com
Mon Mar 15 03:24:06 CET 2021

Dear Members,

In my longitudinal data below, the first couple of subjects were measured 4
times but the rest of the subjects were measured 3 times (see data below).

We intend to use an unstructured residual correlation matrix in
`nlme::lme()`. But our model fails to converge.

Question: Given our data is unbalanced with respect to our grouping
variable (i.e., `id`), can we use ` corSymm()`? And if we do, what would be
the dimensions of the resultant unstructured residual correlation matrix
for our data; a 3x3 or a 4x4 matrix?

Thank you for your expertise,

# Data and R Code
dat <- read.csv("https://raw.githubusercontent.com/hkil/m/master/un.csv")


fit <- lme(opp~time*ccog, random = ~1|id, correlation=corSymm(form = ~ 1 |

  nlminb problem, convergence error code = 1
  message = false convergence (8)

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