Lorraine Andrews, Agnes Higgins, Michael Waring Andrews, and Joan G. Lalor Abstract This paper draws on the experiences of two researchers and discusses how they conducted a secondary data analysis using classic grounded theory. The aim of the primary study was to explore first-time parents’ postnatal educational needs. A subset of the data from the primary study (eight transcripts from interviews with fathers) was used for the secondary data analysis. The objectives of the secondary data analysis were to identify the challenges of using classic grounded theory with secondary data and to explore whether the re-analysis of primary data using a different methodology would yield a different outcome. Through the process of re-analysis a tentative theory emerged on ‘developing competency as a father’. Challenges encountered during this re-analysis included the small dataset, the pre-framed data, and limited ability for theoretical sampling. This re-analysis proved to be a very useful learning tool for author 1(LA), who was a novice with classic grounded theory. Introduction The concept of secondary data analysis appears to have first entered the literature nearly 50 years ago, when Glaser discussed the potential of re-analysing data ‘which were originally collected for other purposes’ (1963, p. 11). Despite the 50-year gap, there still remains a paucity of literature which specifically addresses the processes and challenges of applying secondary data analysis to primary qualitative data and exploring the implications and outcomes of using a different methodology. This paper draws on the experiences of two people who attempted to use a classic grounded theory approach to analyse previously collected primary qualitative data. Prior to discussing the approach to secondary data analysis used for this study, the differences between primary data, secondary data and primary and secondary data analysis and metasynthesis are briefly outlined. Primary data originates from a study in which a researcher collects information him/herself to answer a particular research question. Secondary data, on the other hand, is data that already exists (Glaser, 1963). Consequently, the secondary data analyst is not involved in the recruitment of participants or in the collection of the data. Heaton (2004) defines secondary data analysis as ‘a research strategy which makes use of pre-existing quantitative data or pre-existing qualitative data for the purposes of investigating new questions or verifying previous studies’ (p. 16). In other words, secondary data analysis is the use of previously collected data, for some other purpose. It is not a method of data analysis, therefore methods such as grounded theory or statistical analysis, for example, can be applied to the process of secondary data analysis. Metasynthesis, on the other hand, differs from secondary data analysis in that it analyses qualitative findings from a group of studies, and does not re-use the primary data set, e.g. interviews, diaries, photographs, stories and field notes. Rather, it is ‘the aggregating of a group of studies for the purpose of discovering the essential elements and translating the results into the end product that transforms the original results into a new conceptualisation’ (Schreiber, Crooks & Stern, 1997, p. 314). A review of the literature highlights a number of reasons for conducting a secondary data analysis including: applying a new research question (Heaton, 2004); using old data to generate new ideas (Fielding, 2004); ‘verification, refutation and refinement of existing research’ (Heaton, 2004, p. 9), and exploring data from a different perspective (Hinds, Vogel & Clarke-Steffen, 1997). Despite the fact that secondary data analysis has been in use as a research tool for quite some time it...