Hi everyone,
I am in a tricky situation with regards to data screening because I
have grouped data and ungrouped data.
For the 1st hypothesis the data set is looked at a whole ie everybody
all patients with chronic pain in the data set thus have identified
the outliers (15 seen)
For the 2nd hypothesis the data is grouped as I'm looking at
differences according to pain type.I have 3 pain groups classified. I
have explored the data for outliers.(25 found).
I have different univariate outliers identified by each scenario, but
multivariate outliers were the same for both situations. However
Textbooks say that the data needs to be either grouped or ungrouped.
In order to deal with these I feel I would now need 2 versions of the
data for when outliers have been dealt with so when I analyse each
hypothesis I use the appropriately transformed data. It would not work
having all the data outliers ammended for everyone all together.
What is the correct method, what are the hard and fast rules? I dont
see a clear solution according textbooks ( tabachink & fidell, andy
field) rather the advise is to deal eith outliers and normality of
data with ungrouped initial data first then with grouped differences
and run data analyses with different versions.
Also when doing score alterations for the grouped data I take it when
you look at the extreme scores, you choose to make the outlier smaller
or larger + 1 unit, when comparing to next extreme score ONLY FROM THE
SAME PAIN GROUP?? For eg if a back pain case has outlier on a variable
such as disability, for score alteration I would look at the next
extreme disability score from ONLY back pain and not within ALL pain
groups?? Ie:ignore disability scores from 2 remaining pain groups?
Also, would I report the results of data screening seperately? When
examining data for normality would this be also done seperately for
ungrouped and grouped data along with any transformations etc?
Also what is the best solution for multivariate outliers? Only have 3
in the data set want to retain, textbook says these scores can be
replaced
Please let me have your thoughts or suggestions asap
Sarah
Sent from my iPhone
|