Hi,
With 150 subjects, I wouldn’t worry too much about including a couple
extra covariates. The impact on your power will be minimal, and the
resulting analysis will appropriately control for age, gender, and disease.
cheers,
-MH
--
Michael Harms, Ph.D.
-----------------------------------------------------------
Conte Center for the Neuroscience of Mental Disorders
Washington University School of Medicine
Department of Psychiatry, Box 8134
660 South Euclid Ave.Tel: 314-747-6173
St. Louis, MO 63110Email: [log in to unmask]
On 5/23/16, 6:43 AM, "FSL - FMRIB's Software Library on behalf of Niek van
der Aa" <[log in to unmask] on behalf of [log in to unmask]> wrote:
Dear FSL users,
I’m currently working on a TBSS analysis using a sample size of
approximately 150 children. I have a number of clinical variables that may
be used as an explanatory variable. Normally, when I would perform a
linear regression analysis, I would start with univariate testing to
identify any possible explanatory variables. Any significant variables
would then be included in multivariate analyses.
Does it make sense to apply the same for TBSS? As age is a wel known
variable to affect FA in (young) children), so I would like to combine
each variable with age at scan. So for example, a first ‘univariate
analysis’ could be gender combined with age at scan, next presence of
disease (yes/no) and age at scan, etc. All variables that are significant
would then be included in a multivariate TBSS model.
If the above does make sense, what should I then do with variables that
show a significant association with FA in the ‘univariate’ analysis but
show no correlation in multivariate analyses. For example, if gender
affects FA when analyzed with age only (as mentioned above), but shows no
effect on FA when combined with presence of disease (yes/no), number of
medicine and age at scan. Would it then make sense to remove the gender
variable?
And finally, is there a maximum of variables that can be used in a TBSS
model?
Thanks for your help,
Niek
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