SPSS steps - Missing data analysis

Click 'Analyse'

Click 'Missing value analysis'

In 'Missing value analysis' window

Transfer ID (if you have one) to 'Case Labels'

Then, transfer all your variables to 'Quantitative variables'

Then, if applicable, transfer all variables that considered as categorical to 'Categorical variables' 

Then click 'Pattern'

In 'Missing value analysis: Patterns' window

In Display 

Tick 'Tabulated cases....'

Set to 5% in 'Omit patterns with less than .... % of cases'

Tick 'Sort variables by missing value patern'

Tick 'Cases with missing values, sorted by missing value patterns'

Tick 'Sort variables by missing value pattern

Tick 'All cases, optionally sorted by selected variable'

In Variables, select all and send to 'Additional Information for'

Click 'Continue'

In 'Missing value analysis' window

Click 'Descriptive'

Click "t Tests"

Click 'Include probabilities in table

Click 'Crosstabulations of categorical and indicator variables

Click 'Continue'

In 'Missing value analysis' window

In Estimation 

Click 'Listwise'

Click 'Pairwise'

Click 'EM'

Click 'Regression'

Then Click 'Variables' button

In Missing value analysis: Variable 

Make sure 'Use all quantitative variables' is ticked

Click 'Continue'

Click 'EM' button

In Missing value analysis: EM 

Distribution 'Normal'

Maximum iteration type '100'

Click 'Continue'

Click 'Regression' button

In Missing value analysis: Regression

Click 'Residuals'

Click 'Maximum number of predictors', then type '3'

Click 'Continue'

Finally click 'OK'