Pinpointing Your Data Collection Procedures

Quantitative Methodology

One of the most important steps in developing a dissertation is identifying a gap in the literature.  New studies need to have a problem statement, purpose statement, background literature, and research questions.  Once these essential elements are set in stone, I suggest focusing on components of the methodology chapter.  Why focus on methodology specifics so early on in the dissertation process?  Because you need to make sure that your data collection procedures and data analysis plan are feasible.  If it is not possible to draw a sizeable sample, then you might be forced to revise your topic and research questions.

Once you have written your research questions and determined the statistical analyses you will be running, an a priori power analysis is usually conducted to identify the minimum sample size target for the study. G*Power is a common tool used to run power analyses (download for free here.  So early on in the process, you should have a ballpark estimate of how many participants you will need to sample.

Now you can start thinking about your data collection procedures.  You will need to determine if you are administering a self-report survey or if you are collecting archival data.  If administering a self-report survey, try to use an instrument that has already been validated.  While it is possible to develop your own quantitative survey, it adds considerable work to the dissertation journey.  Depending on the school you attend, developing your own survey tool potentially involves providing the survey to a panel of experts, running a pilot study with a subset of your sample, and establishing construct validity with an Exploratory Factor Analysis (EFA) or Confirmatory Factor Analysis (CFA).  If possible, save the development of your own survey instrument for a journal publication.  You can do google searches with keywords for your topic and type in “reliability and validity” at the end.  For example, if you’re looking for a job satisfaction survey, type into Google “Job Satisfaction Survey Reliability and Validity”.  Try to select the most recent survey instrument that has established validity and reliability statistics.  If the instrument is not listed publicly, send an e-mail to the author/creator of the instrument to ask for permission to use it in your study. Also request scoring guidelines from the author so you can correctly calculate the variables of interest.

If using archival data, allow yourself plenty of time to identify and gain access to an appropriate data set. Verify with your committee and IRB whether you can collect the archival data early so you can ensure the variables of interest are in the data set.  Sometimes there is extensive paperwork to complete when utilizing a secondary data source (such as hospital records). Keep track of all e-mail permissions and paperwork in case they are requested from the IRB.

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