Survey research and design in psychology/Tutorials/Multiple linear regression/General steps

General steps
The general recommended steps for conducting a multiple linear regression analysis are:


 * 1) Conceptualise the model (e.g., draw a path diagram or Venn diagram to indicate the IVs and the DV) and establish research questions and/or hypotheses.
 * 2) Check assumptions:
 * 3) Levels of measurement
 * 4) Sample size
 * 5) Normality
 * 6) Linearity
 * 7) Homoscedasticity
 * 8) Multicollinearity
 * 9) Multivariate outliers
 * 10) Normality of residuals
 * 11) Choose the type of MLR:
 * 12) Standard
 * 13) Hierarchical
 * 14) Stepwise / Forward / Backward
 * 15) Interpret statistical output and psychological meaning of results. Consider:
 * 16) Overall model
 * 17) R, R2, Adjusted R2, sig. of R
 * 18) Change in R2 and the sig. of this change (if a hierarchical MLR is conducted)
 * 19) Regression coefficients
 * 20) Y-intercept (labelled "Constant" in the SPSS MLR Coefficients table output)
 * 21) Unstandardised (B)
 * 22) Standardised (&#946; (beta))
 * 23) t and significance for each predictor
 * 24) Zero-order correlations (r) and semi-partial correlations squared (sr2) for each IV in each model
 * 25) Depict the relationships in a path diagram or Venn diagram (if useful/relevant)
 * 26) Regression equation: Present a prediction equation for Y (if useful/relevant)