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Predict M/P ratio (Multiple regression analysis (Why: create a linear…
Predict M/P ratio
Multiple regression analysis
Why: create a linear regression model between one dependent variable and multiple independet variables. How: analyze; regression; linear
Check assumptions. all variables have an interval/ratio scale (categorical variables can be used as independent variable (dummies)), relationship is causal, model is linear, homogeneity of variances, normal distribution of residuals, no multicollinearity.
Check normal distribution. How: analyze; regression; linear; plots; normal probabilty plot
Residuals on/around diagonal
Normal distribution
Residuals not on/around diagonal
No normal distribution
Check for multicollinearity. How: see corelate, univariate analysis
Correlation with |r| >= 0,9
Multicollinearity
Discard one of the correlating variables
No correlation with |r|>=0,9
No multicollinearity
Check linearity/homogeneity of variances. How: analyze; regression; linear; plots; scatter with y=ZRESID and x=ZPRED.
Residuals not equal around baseline
No homogeneity
No obvious pattern of residuals
Linearity
Residuals equal around baseline
Homogeneity
Obvious pattern of residuals
No linearity
Satisfied
Choose between standard or stepwise method
Look at R-square determination coefficient, variance analysis, coefficients for the multiple regression equation and variables entered/removed (in case of stepwise method)
Translate categorical variables into dummies (dichotomous variable with value 0 and 1. How: translate; recode into different variables.
Not satisfied
Transform variables
Non-parametric/non-linear regression
For example R cubic spline function