# Number of observations in groups - linear mixed effects model

I would like to fit linear mixed effects model to my dataset, but I was wondering if quantity of observations in groups matter? I have some groups with about 60 observations in each, but there are also some with only 1, so Im curious if there will be any influence on my linear mixed effects model because of that.

No, it will not be a strong influence. Using the standard LME model where $y \sim N(X\beta, ZDZ^T + \sigma^2 I)$ if one assumes a degenerate case for an LME where you have an equal number of observations and groups (let's say under a "simple" clustering, no crossed or nested effects etc.) then all your sample variance would moved in the $D$ matrix, and $\sigma^2$ should be zero. The problem will be that you will have as many parameters as data in a liner model. You have an over-parametrized model; therefore regression will a bit nonsensical. Issues of identifiability will also arise.