How to know if computational calculations are correct I've recently been modelling some transition states of a reaction I've been doing (read: struggling to do).

Whilst I have a lot of technical support in doing this (both step by step help and also academics who research in the field of computational chemistry), one thing that bugs me is the difficulty in knowing whether the calculation is meaningful. 

In synthetic chemistry, I can do an experiment, then take an NMR/crystal structure, and be confident that i've got what I was intending to do. Whilst different bases may promote different reactions, its always possible to work out whats happened. 

In computational chemistry, I do a calculation and get an answer, however depending on the methods used the answer might change. 

This can be minimal: isomer A is favoured over isomer B, but the extent changes depending on the basis set/experiment. Or can be significant: isomer A and B change their order. 

I was wondering if there is any way of telling whether a calculation is relevant. Obviously experiment can do this, but the reason I'm doing the calculation to begin with is to try and rationalise the difficulties in reaction .

Is there a concrete way to quantify the 'meaningfulness' of a computational result, or is it always a case of just fitting the computational data to experiment and then working backwards.
The only guaranteed way to achieve absolute correctness is to use asymptotically better methods and see the asymptotic behavior yourself. This, however, ofter requires prohibitively complex approaches.

Outside of that, one needs an experiment to check your data against. A good way (with limits) is to perform vibration frequency calculations and see if that fit the experiment. (making correction of unharmonic behavior). Another way is to run through similar well-studied cases and fit computational results. Most probably, a systematic error would be found, that can be easily eliminated. Luckily, most probably you are not the first to work with your particular kind of systems, so using google scholar it is usually possible to find a review or an establishing work that would list what work and what does not. Most practical methods have known 'glitches', and the ways to deal with them were considered. In particular, DFT cannot catch dispersion interactions, requiring empirical correction schemes.