WG1 – Linear Regression
Pearson correlation
Analyze Correlate Bivariate
Linear regression analysis
Analyze Regression Linear Dependent: afhankelijke variabele Independents: alle
onafhankelijke variabelen
Statistics: Part & partial correlations (VAF per variabele)
Statistics: Collinearity diagnostics (multicollineariteit)
o VIF < 10 (geen multicollineariteit)
o Tolerance > .10 (geen multicollineariteit)
Save: Cook’s distance & Leverage values (outliers)
o Cook’s distance < 1 (geen outliers)
o Leverage value < 3(k+1)/N (geen outliers)
Plots: scatterplot van standardized predicted values (Y) vs. standardized residuals (X)
o Vraag normal probability plot
Hierarchical regression analysis
Analyze Regression Linear Dependent: afhankelijke variabele Independents: variabelen
op bepaalde volgorde in de losse blokken
Statistics: R2change
Zie Linear Regression Analysis
Remove outliers
(Ask for Cook’s distances and Leverage when performing linear regression) Data Select cases
If condition is satisfied If Cook’s Distance < 1
Mogelijke vragen?
What predictor explains the most unique variance? part correlations
How much variance of [Y] is explained by [X]? (part correlations)2
Assumpties checken
o Non-linearity: scatterplot
o Heteroscedasticity: scatterplot
o Non-normality of the residuals: normal probability plot
o Multicollineariteit: collinearity diagnostics
How much variance of [Y] is explained by the predictors? Model summary: R2
, WG2 – ANOVA
Crosstabs (group sizes)
Analyze Descriptive statistics Crosstabs
ANOVA
Analyze General linear models Univariate
Plots: variabele met meeste groepen in horizontal axis, andere groep in separate lines
(interaction effect interpreteren) (“profile plot”)
EM means: estimated marginal means (losse variabelen & interactie effect)
Save: standardized residuals (+histogram voor assumpties (zie hieronder))
Options: descriptive statistics & homogeneity tests
Post hoc: Tukey
Distribution standardized residuals (voor assumpties)
ANOVA Save: standardized residuals OK Graphs Histogram of standardized residuals
Mogelijke vragen?
Assumpties checken
o Normaliteit: histogram per groep (distribution standardized residuals) of
Kolomogorov-Smirnov
o Equality group variances (homogeneity): Levene’s test > .05 goed
Is there a significant relationship between Y and X 1 and/or X2? Tests of Between-Subjects
Effects: Corrected model
Can the null hypothesis of equal group variances be rejected? Levene’s test
Calculate the eta squared measure formuleblad
WG3 – ANCOVA
Drie stappen:
1. ANOVA om te checken of x effectief is als significant:
2. ANCOVA met interactie effect om parallelisme assumptie te checken
a. ANCOVA Univariate Model Build model
i. Als significant: niet voldaan aan assumptie parallelle regressielijnen
ii. Als niet-significant: stap 3
3. ANCOVA zonder interactie
“Determine the correlation between Covariate and Dependent Variable”
ANOVA Dependent: Covariate Independent: Dependent variable Output: Corrected model
Pearson correlation
Analyze Correlate Bivariate
Linear regression analysis
Analyze Regression Linear Dependent: afhankelijke variabele Independents: alle
onafhankelijke variabelen
Statistics: Part & partial correlations (VAF per variabele)
Statistics: Collinearity diagnostics (multicollineariteit)
o VIF < 10 (geen multicollineariteit)
o Tolerance > .10 (geen multicollineariteit)
Save: Cook’s distance & Leverage values (outliers)
o Cook’s distance < 1 (geen outliers)
o Leverage value < 3(k+1)/N (geen outliers)
Plots: scatterplot van standardized predicted values (Y) vs. standardized residuals (X)
o Vraag normal probability plot
Hierarchical regression analysis
Analyze Regression Linear Dependent: afhankelijke variabele Independents: variabelen
op bepaalde volgorde in de losse blokken
Statistics: R2change
Zie Linear Regression Analysis
Remove outliers
(Ask for Cook’s distances and Leverage when performing linear regression) Data Select cases
If condition is satisfied If Cook’s Distance < 1
Mogelijke vragen?
What predictor explains the most unique variance? part correlations
How much variance of [Y] is explained by [X]? (part correlations)2
Assumpties checken
o Non-linearity: scatterplot
o Heteroscedasticity: scatterplot
o Non-normality of the residuals: normal probability plot
o Multicollineariteit: collinearity diagnostics
How much variance of [Y] is explained by the predictors? Model summary: R2
, WG2 – ANOVA
Crosstabs (group sizes)
Analyze Descriptive statistics Crosstabs
ANOVA
Analyze General linear models Univariate
Plots: variabele met meeste groepen in horizontal axis, andere groep in separate lines
(interaction effect interpreteren) (“profile plot”)
EM means: estimated marginal means (losse variabelen & interactie effect)
Save: standardized residuals (+histogram voor assumpties (zie hieronder))
Options: descriptive statistics & homogeneity tests
Post hoc: Tukey
Distribution standardized residuals (voor assumpties)
ANOVA Save: standardized residuals OK Graphs Histogram of standardized residuals
Mogelijke vragen?
Assumpties checken
o Normaliteit: histogram per groep (distribution standardized residuals) of
Kolomogorov-Smirnov
o Equality group variances (homogeneity): Levene’s test > .05 goed
Is there a significant relationship between Y and X 1 and/or X2? Tests of Between-Subjects
Effects: Corrected model
Can the null hypothesis of equal group variances be rejected? Levene’s test
Calculate the eta squared measure formuleblad
WG3 – ANCOVA
Drie stappen:
1. ANOVA om te checken of x effectief is als significant:
2. ANCOVA met interactie effect om parallelisme assumptie te checken
a. ANCOVA Univariate Model Build model
i. Als significant: niet voldaan aan assumptie parallelle regressielijnen
ii. Als niet-significant: stap 3
3. ANCOVA zonder interactie
“Determine the correlation between Covariate and Dependent Variable”
ANOVA Dependent: Covariate Independent: Dependent variable Output: Corrected model
