I want to apply regression analysis using SPSS. Kindly help as to how to apply the regression model in the study where i have recorded Weight, BMI, Total body fat mass, insulin resistance and nerve conduction velocity in type 2 diabetics.
Also check https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4855031/
Hello Anwar,
The glib answer is to try OLS (ordinary least squares) regression, using weight, BMI, fat mass, and insulin resistance as IVs (independent variables, or "predictors"), with nerve conduction velocity as the DV (dependent variable).
There may be a few things to watch out for. First, among the IVs, weight and BMI will be positively correlated (fat mass and BMI and weight are also likely to correlate). So, the issue of collinearity may be one to check with your data. Second, the model residuals may not be normally distributed (this is easy to check, fortunately, with most software packages offering regression analysis).
If that seems too daunting, it might be a good idea to talk over your study aims, variables, and data collection with a statistical consultant from (or near to) your institution.
Good luck with your work.
Multivariable logistic regression analysis can be carried out to predict outcomes. Kindly check https://europepmc.org/article/med/27200189
Also check https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4855031/
Multiple linear regression (unless you categorise subjects based on some conduction velocity cut-offs). Make sure all the assumptions are satisfied such as homoscedasticity, absence of multicollinearity, and linear relation between the DV and IVs.
Thank you everyone for your suggestions.I think now i can easily proceed with my statistical analysis.
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