How to Exclude Random Missing point before performing PCA.

Question

Hi,

How to exclude missing values from the dataset before analysis. These are random missing values due to instrument malfunction. I don't want to impute my data. I have explored the 'Explore Missing Value' but that didn't help because that changes the interpretation of my PCA results.

Is there any other way to do so?

Thank you,

Beginner_9

spyros_megalou · Answer

Hi @Beginner_9 ,

To exclude missing cells you can use Missing Value Codes. This excludes the value from one cell, but the values for the other variables are still included. You can use this also for outliers or noise as well and not just for missing values. You can see how at the Exploratory Data Analysis (around 2:40 min) Course from STIPS. This comes from the 2.6 Data Preparation for Analysis chapter.

I hope that solves the problem,
Spyros

Victor_G · Answer

Hi @Beginner_9,

Not with this platform, it will only give you the possibility to exclude rows containing missing values.
I suggest you read the documentation about the different methods available in the PCA platform.

If you want to "exclude" cells with missing values from the analysis, switching the default method to row-wise will exclude any observation with missing data. The other methods will try to leverage the information contained in missing and non-missing cells.

Hope this answer will help you,

Beginner_9 · Answer

Hi @Victor_G,

Is there a way to exclude missing cells instead of the entire row or column?

Thank you,