Dear All
Recently a researcher at Salisbury approached me for advice. A paper he had
submitted for publication in a journal had been rejected on statistical
grounds. The researcher had performed repeated paired t-tests and the
referee had suggested that a repeated measures ANOVA would be more
appropriate. I have little knowledge of mixed models and am not sure as to
how such an analysis could be applied to his data set. I would be grateful
for any comments you might have.
The researcher had conducted a retrospective study of stroke and MS patients
(n=111 and n=21 respectively) with a dropped foot who had been treated using
the Odstock Drop Foot Stimulator (ODFS). This device had been fitted to the
patients’ leg with Functional Electrical Stimulation (FES) being used to
stimulate the muscles as the patient walked. The patients were allowed to
take the ODFS devices home to use as desired. Patients were routinely
assessed at their initial visit, at 6 weeks, 4˝ months and every 6 months
thereafter whilst they continued to use the stimulator. At each assessment
the patients’ PCI (Physiological Cost Index) and walking speed were
measured. PCI (beats/m) = change in heart rate from rest to walking
(beats/min) / walking speed (m/min).
At each assessment patients were asked to walk briskly over a 10 metre
course six times with approx. 10 seconds rest between walks. During three
of the six walks the stimulator was activated. The order of the stimulated
(S) / non-stimulated (NS) walks was varied to compensate for fatigue. The
following order was set: NS S S NS NS S. The mean walking speed and
PCI for the NS and S runs were calculated. Some patients were not able to
complete all six runs and their mean readings were therefore based on fewer
runs. All data were obtained from patient notes. Data for each individual
run were recorded in the notes, but only the patient means have been
recorded on the database and there is no way of knowing the number of
observations on which each mean was based.
For the paper in question only the initial and 4˝ month assessments were
considered. The ability to walk at least 10 metres was defined as an
inclusion criterion, as was the availability of data at both time points.
The researcher had reported the results of repeated paired t-tests on the
mean values as follows
NS3 – NS1 (non-stimulated (3rd visit (at 4˝ months)) – non-stimulated (1st
visit))
S3 – S1
S1 – NS1
S3 – NS3
S3 – NS1
The results were reported separately for stroke and MS patients. No formal
comparisons were made between the two patient groups.
As you can see it’s a bit of a mess. I have reservations about performing
an analysis treating mean values as individual observations, especially when
the means in question are based on varying numbers of individual runs.
Also, the runs themselves cannot be considered independent. The systematic
way in which the order of runs was determined also raises concerns. Even if
it were acceptable to treat the means as individual observations, how could
a mixed model be applied? Note that S1, S3, NS1 and NS3 are all recorded on
the same patient.
All comments gratefully received - even if they’re to say that you don’t
think that there is any appropriate analysis for this data set without the
raw values.
Regards
Kate
P.S. Other studies have reported that, if the ODFS is used periodically, the
patients' ability to walk without the ODFS can also improve, hence the
non-stimulated readings at each follow up assessment.
*************************************************
Miss Kate Parry
Research and Development Support Unit
Trust Headquarters
Southmead Hospital
Westbury on Trym
BRISTOL BS10 5NB
Tel: 0117 959 5209/5054
Fax: 0117 959 0902
E-mail: [log in to unmask]
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