Multiple regression analysis
Description: Least-squares multiple regression is performed when you seek to test predictive relationships between multiple predictors and a single dependent measure. The dependent measure is assumed continuous, whereas the predictors can be either categorical (after appropriate dummy coding) or continuous. The model includes the assumption of a linear relationship between the independent and dependent variables, and the assumption that the residuals are independently and normally distributed and exhibit constant variance.
A priori power analysis for study planning study involving multiple regression: G*Power demo (May 2020): Powerpoint, video
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
SPSS demos
Multiple linear regression in SPSS (Sept 2021): Video , SPSS data , Powerpoint
-This presentation provides demonstrations for how to run a multiple regression model and how to interpret your results. Included in the Powerpoint is a discussion of effect size for the model, as well as assessment of relative importance of predictors using semi-partial and partial r's (and r-squares).
Multiple regression analysis (procedures and interpretation) using SPSS (July, 2019): video, Powerpoint, SPSS data file
-This presentation provides demonstrations for how to run a multiple regression model and how to interpret your results. Included in the Powerpoint are demonstrations for how to evaluate assumptions.
Polynomial regression with single predictor (April 2022): video , SPSS data , Powerpoint
Polynomial regression with covariates (May, 2022): video , SPSS data , Powerpoint
Fixed effects regression for repeated measures and longitudinal data in SPSS (Least-squares dummy variable approach:): video SPSS data example 1 (wide format) , SPSS data example 1 (long format with dummy variables) , Powerpoint
Identifying potential heteroskedasticity when performing linear regression in SPSS (March 2021): video , Powerpoint , SPSS data
Generating collinearity diagnostics for linear regression (and binary logistic regression) in SPSS (February, 2020): Video (multiple regression), Powerpoint, Video (logistic regression; in case you are interested).
Regression diagnostics: Identifying cases with high potential influence on your regression model (February, 2021): Powerpoint presentation, SPSS data example 1, SPSS data for example 2 , SPSS data for example 3 , Video (example 3)
Multiple regression with robust standard errors in SPSS (February 2021): video , SPSS data, link to article
-This presentation walks you through the concepts of distance/discrepancy, leverage, and influence. It covers SPSS procedures for how to generate results that will allow you to identify cases that are (a) outliers (high distance with respect to the residuals), (b) high in leverage (cases that are more extreme with respect to the independent/predictor variables), and/or (c) highly influential (where influence is the product of both discrepancy and leverage).
How to generate and interpret squared Mahalanobis distance in SPSS to identify possible multivariate outliers (Jan 2021): video , Powerpoint , SPSS data
Understanding zero-order, partial, and part correlations in your regression output (June 2020): video , Powerpoint, SPSS data
-This presentation provides a basic overview of these correlations and builds up to showing you what these indices represent when requested as part of the regression output. It also discusses the relationship between R-square and the squared part (i.e., semi-partial) correlations in your output.
Regression in SPSS: Identifying and managing heteroskedasticity (July, 2019): video, Powerpoint, SPSS data file
-This presentation provides demonstrations of ways of evaluating whether the assumption of heteroskedastic errors is violated. It also shows you how to run the regression analysis with heteroskedasticity-consistent standard errors via the General Linear Model menu.
Hierarchical multiple regression using SPSS (February, 2020): video, SPSS data file, Powerpoint
Running and interpreting multiple regression with dummy variables in SPSS (June, 2019): video, text file (referenced in video), SPSS data
Multiple regression using dummy coding of multi-categorical predictors in SPSS (August 2021) : Multiple regression using dummy coding of multi-categorical predictors in SPSS (August 2021) , SPSS data , Powerpoint
Multiple regression using effect-coded variables (December, 2019): video; Powerpoint, .sav file (video & Powerpoint); .sav file (Powerpoint only)
Running multiple regression in SPSS based on summary matrix data input (Jan 2021): video , text file containing syntax
Moderated multiple regression using Hayes' Process macro (July, 2019): video, Powerpoint, SPSS data file
(link to obtain Process macro, video on how to install Process macro)
Moderated multiple regression using Process macro version 3 5 for SPSS (Sept 2020) : video , SPSS data file , Powerpoint
Moderated multiple regression using Process macro Multicategorical option (Sept 2020): video , SPSS data , Powerpoint
Testing for simple, parallel, and sequential mediation using Hayes' Process macro (July, 2019): video, Powerpoint, SPSS data
Polynomial regression (July 2020): video , Powerpoint , SPSS data file
Variable selection procedures using SPSS (July 2020): video , Powerpoint, SPSS data
Median regression as an alternative to OLS regression: video , SPSS data , Excel file
Wild bootstrap for generating confidence intervals for regression coefficients (March 2021): Video , SPSS data, , Powerpoint
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
R demos
Basics for performing multiple regression (Jan, 2020): video, .RData file (data saved in a data frame named 'regdata'), text file containing commands
Hierarchical multiple regression (Jan, 2020): video, .RData file, text file with commands
Variable selection procedures (Jan, 2020): video, .RData file, text file containing commands, Powerpoint
Moderated multiple regression (Jan, 2020): video, Powerpoint, text file with commands, .RData file (part 1),.RData file (part 2)
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Stata demos
Multiple regression using dummy-coding of multicategorical predictors (June 2020): Video , dataset , Powerpoint
Running and interpreting moderated multiple regression (Jan, 2020): video, .dta file, text file with commands, Powerpoint
Obtaining percentile and bias-corrected confidence intervals for R-square in Stata (March 2021): video , main dataset , extra dataset , Link to text file with commands
Linear regression in Stata with heteroskedasticity-consistent standard errors (March, 2021): Video, .dta file
Using 'sem' commands to mimic Hayes' Process Model 4 in Stata (March 2021): video, .dta file , Do-file , Powerpoint ,text file
Regression analysis in Stata: Testing a probing interactions involving continuous predictors (August, 2019): video, text file, .dta file
Testing and plotting interaction effects: Multiple regression in Stata (February, 2021): video , .dta file , text file , Powerpoint
*Presentation covers continuous and binary moderators
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Older videos on multiple regression analysis
Overview of simple and multiple regression using SPSS (video), SPSS data file
Multiple regression in SPSS using ESPN football data (video), SPSS file
Multiple regression (Powerpoint demo), SPSS file
Multiple regression using Excel (video), Excel file
Evaluating linear regression assumptions (video 1, using Plots option), SPSS file
Evaluating linear regression assumptions (video 2; Breusch-Pagan test), SPSS file, Excel calculator