Experimenting with [joint dependent distributions](https://mathematica.stackexchange.com/q/41000/57) via the `TransformedDistribution` function, I used the following to derive a distribution where the second variate is distributed dependent on the value of the first variate (very simplified & contrived example follows).

 distA = TransformedDistribution[{b, 
 If[b == 1, d1, d2]}, {b \[Distributed] 
 DiscreteUniformDistribution[{1, 2}],
 d1 \[Distributed] UniformDistribution[{1, 2}],
 d2 \[Distributed] UniformDistribution[{2, 3}]}]
 

 distB = TransformedDistribution[{b, 
 Piecewise[{{d1, b == 1}, {d2, b == 2}}]}, {b \[Distributed] 
 DiscreteUniformDistribution[{1, 2}],
 d1 \[Distributed] UniformDistribution[{1, 2}],
 d2 \[Distributed] UniformDistribution[{2, 3}]}]
 
 distC = TransformedDistribution[{b, 
 Switch[b, 1, d1, 2, d2]}, {b \[Distributed] 
 DiscreteUniformDistribution[{1, 2}],
 d1 \[Distributed] UniformDistribution[{1, 2}],
 d2 \[Distributed] UniformDistribution[{2, 3}]}]
 
 distD = TransformedDistribution[{b, 
 Which[b == 1, d1, b == 2, d2]}, {b \[Distributed] 
 DiscreteUniformDistribution[{1, 2}],
 d1 \[Distributed] UniformDistribution[{1, 2}],
 d2 \[Distributed] UniformDistribution[{2, 3}]}]

The first two behave as I'd expect: `Mean, Var, RandomVariate` all do what they're supposed to. The latter two, while behaving as expected for the *simple* probability functions (e.g. `Mean`), puke on any attempt to sample with `RandomVariate`, with the message 

>TransformedDistribution::nnbprm: The valid numeric parameters of distribution TransformedDistribution[{\FormalX]1,Switch[\FormalX]1,1,\FormalX]2,2,\FormalX]3]},\FormalX]1,\FormalX]2,\FormalX]3}\Distributed]ProductDistribution[DiscreteUniformDistribution[{1,2}],UniformDistribution[{1,2}],UniformDistribution[{2,3}]]] are expected. Use DistributionParameterAssumptions to obtain the parameter assumptions. >>

I'm a bit puzzled by this, seems the forms in this case should result in equivalent behavior. Any insights?