Today we will take a look at the results section for
quantitative studies. Start out by reporting descriptive statistics "that
appropriately characterize the sample." What does this mean? Look at
frequencies for your demographics, such as gender, marital status, etc. For
continuous variables (not in categories) you will need to compute the means and
standard deviations or standard errors (check with your committee as to which
they prefer). An example of such a variable is age, the convention is to give
these stats like this (M = 43 yr., SD
= 5.2). You will also discuss any total scores or subscores that you may have
calculated and their distribution.
The next step is to discuss and evaluate statistical
assumptions as appropriate to the study. All statistical tests have specific
assumptions that must be considered (see Pallant, 2013, for an in-depth
discussion of them). Let's take as an
example, the assumptions for parametric tests (e.g., t-tests, analysis of variance):
using an interval or ratio scale of measurement, random sampling, independence
of observations (no measurement is influenced by another), a normal
distribution, and homogeneity of variance (samples have similar variances).
There are techniques to check these assumptions, and you would discuss in this
section which ones you used and the results.
Next, you report your findings, organized by research
questions and/or hypotheses. Include the exact statistics and associated
probability values (some examples: t(32)=3.1,
p < .01; r(N=45)= .16, p >
.05). A reminder- if the probability is < .05 (less than), it is considered
significant; if it is > than.05 (greater than) it is not significant. You
should include confidence intervals around the statistics, as appropriate
(check with your committee). Include effect sizes, as appropriate (e.g., R2,;
check with your committee as to what they prefer).
If you had multiple conditions, you may need to do post-hoc
tests. Report the type and results of post-hoc analyses. You may have additional statistical tests of
hypotheses that emerged from the analysis of main hypotheses and you will need
to report those.
Finally, you may wish to clarify your results with tables
and figures, include those as specified in the APA manual. There is very specific
formatting for these- so check it out in the manual.
Next time we will talk about c.4: Data Analyses: Qualitative.
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
Pallant, J. (2013). The
SPSS Survival Manual, 5th edition. Open University Press.
Dr. Stadtlander
ReplyDeleteYou 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, does the mean value indicate the value of dependent variable? Does the mean value of a population is based on a pilot study or other researchers' results? how to know the mean value for my population of CPAP adherence?
Final question is when we report R2, should we also report adjusted R2 or both ?
Thanks
Molly