Dealing with missing values for correlations calculation

r correlation na missing-data
Delphine picture Delphine · Sep 16, 2011 · Viewed 84.5k times · Source

I have huge matrix with a lot of missing values. I want to get the correlation between variables.

1. Is the solution 

cor(na.omit(matrix))

better than below?

cor(matrix, use = "pairwise.complete.obs")

I already have selected only variables having more than 20% of missing values.

2. Which is the best method to make sense ?

Answer

IRTFM picture IRTFM · Sep 16, 2011

I would vote for the second option. Sounds like you have a fair amount of missing data and so you would be looking for a sensible multiple imputation strategy to fill in the spaces. See Harrell's text "Regression Modeling Strategies" for a wealth of guidance on 'how's to do this properly.

Related questions

Complete.obs of cor() function

I am establishing a correlation matrix for my data, which looks like this df <- structure(list(V1 = c(56, 123, 546, 26, 62, 6, NA, NA, NA, 15 ), V2 = c(21, 231, 5, 5, 32, NA, 1, 231, 5, 200), V3 = c(NA, NA, 24, 51, 53, 231, NA, 153, 6, 700), V4 = c(2, 10, NA, 20, 56, 1, 1, 53, 40, 5000)), .Names = c("V1", "V2", "V3", "V4"), …

Read More
How can I create a correlation matrix in R?

I have 92 set of data of same type. I want to make a correlation matrix for any two combination possible. i.e. I want a matrix of 92 x92. such that element (ci,cj) should be correlation between ci and cj. …

Read More
Calculate correlation with cor(), only for numerical columns

I have a dataframe and would like to calculate the correlation (with Spearman, data is categorical and ranked) but only for a subset of columns. I tried with all, but R's cor() function only accepts numerical data (x must be …

Read More