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WSRt using SPSS, manual for tests in the third block of the second year of psychology at the uva

Here is a short explanation how to do tests in SPSS. These are the tests needed for the third block of WSRt and psychology at the second year of the uva.

Correlation analysis (two continuous variables)

  1. Open the data
  2. Go to analyse, correlate, bivariate
  3. Place the variables of which you want to know the correlation under ‘variables’
  4. Click on ‘paste’ and run the syntax

Partial correlation (three continuous variables and you want to know the correlation between two variables, corrected for a third variable)

  1. Open the data
  2. Go to analyse, correlate, partial
  3. Place the variable of which you want to know the correlation under ‘variables’
  4. Place the variable for which you want to control under ‘controlling for’
  5. Click on ‘options’
    Select ‘zero-order correlations’ (this is the correlation without controlling for one variable)
  6. Click on ‘continue’
  7. Click on ‘paste’ and run the syntax

Multiple regression analysis

  1. Open the data
  2. Go to analyse, regression, linear
  3. Place the dependent variable under ‘dependent’
  4. Place the independent variables under ‘independent’
    If you want to run more models, you can put the first variable under ‘independent’, click on ‘next’ and put the next variable under ‘independent’ (this way you can compare the models)
  5. Click on ‘statistics’ and select:
    Model fit
    R squared change (if you have multiple models)
    Descriptives
    Part and partial correlations
    Collinearity diagnostics
  6. Click on ‘plots’
    Put ZPRED under Y
    Put ZRESID under X
    (This is for testing homoscedasticity)
  7. Click on ‘save’ and select:
    Unstandardised
    (for expected values)
    Mahalanobis
    Cook’s
    Leverage values
    (for outliers)
  8. Click on paste and run the syntax

Principal component analysis

  1. Open the data
  2. Go to analyse, dimension-reduction, Factor
  3. Put the items which you want to analyse under ‘variables’
  4. Click on ‘descriptives’ and select:
    Univariate descriptives
    Initial solution
    Coefficients
    Significance levels
    Anti-image (for assumptions)
    KMO and Bartlett’s test of sphericity (also for assumptions)
  5. Click on Extraction
    Chose Principal component analysis
    Select:
    Scree plot
    Chose for an eigenvalue bigger than 1
  6. Click on rotation and select:
    Varimax
  7. Click on options and select:
    Suppress small coefficients. Set the value on 0,4
  8. Click on paste and run the syntax

Reliability analysis

  1. Open the data
  2. Go to analyse, scale, reliability analysis
  3. put the items which you want to test under ‘items’
  4. Select alpha under model
  5. Click on ‘statistics’ and select:
    Item
    Scale if item deleted
    Correlations
  6. Click on paste and run the syntax

Mediation analysis (using PROCESS)

  1. open the data
  2. Go to analyse, regression, Process
  3. Place the dependent variable under ‘Y’
  4. Place the independent variable under ‘X’
  5. Place the mediator variable under ‘M’
  6. Chose model number 4
  7. Click on options and select:
    Effect size
    Sobel test
    Total effect model
    Compare indirect effects
  8. Click op paste and run the syntax (here, you can also chose ok, the syntax is long and difficult to select)

Moderation analysis (using PROCESS)

  1. Open the data
  2. Go to analysis, regression, Process
  3. Place the dependent variable in ‘Y variable’
  4. Plate the independent variable in ‘X variable’
  5. Set the moderation in ‘Moderator variable W’
  6. Choose model number 1
  7. Click on ‘options’ and select:
    Generate code for visualizing interactions
    Mean centring for construction of products
    Johnson-Neyman output
  8. Click on ‘continue’
  9. Click on ‘ok’
    This will generalize a code for SPSS to visualize. If you copy this code in the output and let it run in the syntax, it visualizes the results.

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Summary of Discovering statistics using IBM SPSS statistics by Field - 5th edition

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