Previously, we looked at instrumentation in qualitative
studies, this time we move to quantitative studies. Generally, students will be
relying on previously published survey 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 survey 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 operationalize 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
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