  The s-ID problem seeks to compute a causal effect in a specific
sub-population from the observational data pertaining to the same sub
population (Abouei et al., 2023). This problem has been addressed when all the
variables in the system are observable. In this paper, we consider an extension
of the s-ID problem that allows for the presence of latent variables. To tackle
the challenges induced by the presence of latent variables in a sub-population,
we first extend the classical relevant graphical definitions, such as
c-components and Hedges, initially defined for the so-called ID problem (Pearl,
1995; Tian & Pearl, 2002), to their new counterparts. Subsequently, we propose
a sound algorithm for the s-ID problem with latent variables.
