Sequences are ordered lists of elements. A typical example is the sequence of bases in DNA. Other examples are sequences of employment stages during a lifetime or individual party preferences over time. Sequence analysis include techniques to handle, describe, and, most importantly, compare sequences. Sequences are most commonly used by geneticists but not as commonly by social scientists. This disparity is surprising, as sequence data are readily available for the social sciences. In fact, all data from panel studies can be regarded as sequence data. Nevertheless, social scientists relatively seldom use panel data for sequence analysis. The first aim of the presentation therefore is to illustrate a typical research topic that can be dealt with sequence analysis. The second part will then describe a bundle of user-written Stata programs for sequence analysis, including a Mata algorithm for performing optimal matching with the so-called Needleman–Wunsch algorithm.
