Deciding on a dissertation or thesis topic can be a difficult task in and of itself. Deciding on a dissertation or thesis topic and collecting data based on your topic can at times seem impossible. It may be tempting to find an archival data set that might be tailored to fit your research study. There are a few advantages to using archived data. For example, on the surface, archival data sets save you resources and time because you don’t have to collect your own data. However, though archival data sets may appear to be time-savers, there are many other issues that you should take into account before you choose to use an archival data set.

Another common issue with archived data is the sheer amount of data. Large archival data sets often contain data collected over many years. On the surface, it might sound like a benefit to have such a large amount of data; however, this does become problematic when the codebook is difficult to follow and the data collected have changed from year to year. Additionally, archival data can have misleading sample sizes. When large questionnaires are given, participants are only asked certain questions based on their previous answers. If you want to run analyses on a particular item from the questionnaire, chances are that not everyone who took the survey has answered that item. This becomes particularly problematic when you want to investigate relationships among multiple items that may not have been answered by all participants in the study.

Though archival data may seem like an easier way to collect dissertation data, there are additional factors that might actually cause you more work in the long run. If you do choose to use archived data for your dissertation or thesis, be mindful of the potential difficulties you might face.