Let $M$ be a n x k matrix which is the outcome of a subjective test, where $n$ is the number of samples and $k$ is the number of raters. Values in $M$ can range from 0 to 1 with a step of 0.1. Since the number of samples is high and the evaluation procedure is long, each rater evaluated only a subset of samples. Samples are provided randomly. Therefore, $M$ looks like this:
$$ M = \begin{bmatrix} 0.1 & NaN & 0.2 & \cdots \\ NaN & NaN & 0.15 & \cdots \\ 0.8 & 0.75 & NaN & \cdots \\ \vdots & \vdots & \vdots & \ddots \\ \end{bmatrix} $$
with $NaN$ representing missing data.
What are the available agreement measures for such a test, where some data are missing? The average number of rating for each sample is 5. $n$ is 50 and $k$ is 24. I am interested both in general agreement between raters and agreement on a specific sample. Also, is it possible to find out which of the raters was the less reliable?