In this paper, we study the stability of Networked Control Systems (NCSs) that are subject to time-varying transmission intervals, time-varying transmission delays, packet dropouts and communication constraints. The transmission intervals and transmission delays are described by a sequence of continuous random variables. The complexity that the continuous character of these random variables introduces is overcome using a novel convex overapproximation technique that preserves the available probabilistic information. By focusing on linear plants and controllers, we present a modelling framework for NCSs based on discrete-time linear switched and parameter-varying systems. Stability (in the mean-square) of these systems is analysed using a new stochastic computational technique, resulting in a finite number of linear matrix inequalities. We illustrate the developed theory on the benchmark example of a batch reactor.