Missing value analysis

Imputation or Removing Data

Before jumping to the methods of data imputation, we have to understand the reason why data goes missing.

1)Missing at Random (MAR): Missing at random means that the propensity for a data point to be missing is not related to the missing data, but it is related to some of the observed data

2)Missing Completely at Random (MCAR): The fact that a certain value is missing has nothing to do with its hypothetical value and with the values of other variables.

3)Missing not at Random (MNAR): Two possible reasons are that the missing value depends on the hypothetical value (e.g. People with high salaries generally do not want to reveal their incomes in surveys) or missing value is dependent on some other variable’s value (e.g. Let’s assume that females generally don’t want to reveal their ages! Here the missing value in age variable is impacted by gender variable)

In the first two cases, it is safe to remove the data with missing values depending upon their occurrences, while in the third case removing observations with missing values can produce a bias in the model. So we have to be really careful before removing observations. Note that imputation does not necessarily give better results.

Reference: https://towardsdatascience.com/how-to-handle-missing-data-8646b18db0d4

I face this problem quite a lot!! Thanks for the information!

You can use the syntax in the syntax window.

For opening a new syntax window, please click
• File > New> Syntax to open a new syntax window
• Type (or copy and paste) the syntax in the syntax window.
• Click “RUN” on the toolbar

I am new to SPSS. Where can I use the syntax?

Yes, the syntax is:
RECODE var 1 TO var 100 (SYSMIS=999) (ELSE=COPY).

Thanks a lot. Apart from click those tabs, may I know the relevant syntax?

Sure. The following are the steps:
• Transform
• Recode into same variable (choose all 100 variables)
• Old and new values: When you click, a new window where you can specify how to transform the values will appear. You can choose to transform ‘system missing’ into 999.

May I know the steps in details and how to convert blank spaces for 100 variables at the same time?

You are welcome May!

Thanks a lot!!

you can transform “system missing” into 999

How can I transform blank spaces in SPSS data into one missing value?

Thanks a lot.

The “Exclude cases listwise” option consists of cases in the analysis only if they have full data on all of the variables.

The “Exclude cases pairwise” option only excludes the cases if they are missing the data required for the specific analysis.

For some statistical procedures, the “Replace with mean” option is available. It calculates the mean value for the variable and gives every missing case this value.