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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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