Chapter 3: Instrumentation in quantitative studies

Previously, we looked at instrumentation in qualitative studies, this time we move to quantitative studies. Generally, students will be relying on previously published instruments for quantitative studies. I do not recommend developing new surveys for a doctoral study. I will explain more on this below.

You will begin this section by discussing each instrument you will be using, who developed it and when. Then indicate why you have chosen it, and why it is appropriate for your study. You will need permission to use the instrument from the developer- include it in your appendix. Then go into detail about the published validity and reliability values that are relevant for your study (those using similar populations). Finally, you will discuss when and with what populations it has been used and how validity and reliability were established for each study.

If you are developing your own instrument, first describe the basis for its development. Did it come through items indicated in the literature? Did you or plan to do a pilot study to refine the questions? You will need to provide evidence for its reliability and validity, this typically requires extensive testing (100s of participants). Finally, show how the instrument will answer your research questions. If you are developing your own instrument, it will require quite a bit of testing and additional work; again, I do not recommend this for a dissertation.

If you are doing an intervention involving manipulation of an independent variable,

there are issues that will come up with the IRB, address them early! As far as c. 3, identify any materials that will be used in the intervention. Indicate who developed the materials and where they have been used in the past (you also may need permission from the developer to use them). If you developed them, indicate how that was done. Provide evidence that another agency will sponsor the intervention.

Next, you need to operational each variable. So for example, if you are interested in resilience, define it and how you will be measuring it. Then talk about how each variable or score is calculated and what the scores represent. Give an example item from each scale/ subscale.

The final portion of this section is your data analysis plan. Mention what software you will use, how you will clean the data (how you will handle missing data, and make sure there are not any extreme outliers). Restate your research questions and hypotheses from c 1. Then, for each hypothesis describe the statistical tests that will be used. If you are doing many statistical tests, you need to account for that by using a correction statistic (Bonferroni's is common- it reduces your p value, based on the number of tests). If you are using covariates and/or have confounding variables, you need to discuss it. Finally, how will you interpret the results (key parameter estimates, confidence intervals and/or probability values, odds ratios, etc.). 

Next time we will continue our review - Chapter 3: Instrumentation in mixed methods studies. 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