Monday, March 10, 2014

c.4: Demographics and Data Collection


The mixed methods and qualitative checklists have sections called Demographics, in which you should discuss the relevant demographic characteristics of your participants. Typical items include gender, race, and age, as well as any characteristics specific to your study. For example, if you interviewed homeless teen mothers, it would be important to know how long they have been on their own and the age of their children. 

For all methods, the next section is Data Collection. You need to describe when the study was done (for example, months and year). Describe how you recruited your participants, and how many participated in all phases of the study. If you had to change any of your data collection procedures from what was listed in c. 3, indicate how and why it was changed (and that you went through IRB to do so). 

For Qualitative and Mixed Methods Studies. Describe the location of your study, how often you met with participants and the length of time both for individual interviews/surveys and for the total study. Next, describe how you recorded your interviews and how they were transcribed. If you encountered any unusual circumstances during your data collection describe it and how it affected your data collection (e.g., equipment failure, a participant died between interviews, etc.). 

For Quantitative Studies. Describe your demographics as discussed above. Describe how representative your sample is to the population of interest or how proportional it is to the larger population if non-probability sampling is used (external validity). Provide results of basic univariate analyses that justify inclusion of covariates in your model, if applicable.    

For this section, keep in mind that your reader should have a good picture of how you did your study, and would be able to replicate it based upon your description. 

Next time we will talk about c.4: Data Analyses: Quantitative. Do you have an issue or a question that you would like me to discuss in a future post? Would you like to be a guest writer? Send me your ideas! leann.stadtlander@waldenu.edu

2 comments:

  1. Dr. St
    You mentioned “effect sizes, as appropriate (e.g., R2,; check with your committee as to what they prefer).” I have three questions.
    My first question is if my research is conducting a multiple regression analysis I do not need to calculate the sample size. Is this correct?
    The second question is when I perform sample size calculation, is the mean value for a population based on my pilot study? Could I use other researchers’ results?
    Final question is when we report R2, should we also report adjusted R2 or both ?
    Thanks
    molly

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  2. Thanks for your questions, Molly!

    1) You need to calculate sample size for all quantitative studies. Do a Google search for "power analysis calculator multiple regression" - the site should walk you through the calculations.

    2) If it requires an effect size you should use others' results. A pilot study typically has too small of a sample for reliable calculations.

    3) This is really a personal preference, ask your methodologist what they prefer.

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