Many health technologies exhibit some form of learning effect, and this represents a barrier to rigorous assessment by randomised controlled trials. There is reluctance to evaluate while the technique is being learnt, yet unwillingness to admit uncertainty once it has been learnt. In principle, statistical description of a learning curve and subsequent adjustment of an evaluation to take account of learning effects should solve this problem. Exactly how the analyses should be performed has been unclear. This thesis has three components: Systematic review of health technology assessment literature: a systematic description of studies that directly assessed the learning curve effect of health technologies. Systematic search of non-health technology assessment literature: a systematic identification of 'novel' statistical techniques applied to learning curve data in other fields, such as psychology and manufacturing. Testing of statistical methods: testing of these statistical techniques in sets of data describing a variety of health technologies where learning curve effects are known to exist.