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Data Censoring

When researchers only have partial information about the values of some data points (knowing that they are at least as large as some value or no larger than some other value), the correlation between those variables is distorted. For example, when exact opposites divide dimension into two parts, each variable is 0 when the other is positive and so they do not correlate -1.

We have created a method of estimating the correlation between the two variables when each of their measures may have some degree of left or right censoring. This method was described in our 2020 presentation:

Barchard, K. A., & Russell, J. A. (2020, June 1 – September 1).  I’m less and less happy until finally I’m sad: Estimating correlations when variables divide a construct into parts.  Poster presented at the Association for Psychological Science poster showcase, Chicago, IL.      Poster      Handout

To implement this method, use one of the following Excel sheets.

Small file, fast download: Barchard, K. A. (2020, July). CensorCorr: Examining the effect of censoring on correlations (n = 10,000). [Excel file]. http://barchard.faculty.unlv.edu/research/examining-opposites/

More accurate results: Barchard, K. A. (2020, July). CensorCorr: Estimating the effect of censoring on correlations (n = 500,000). [Excel file]. http://barchard.faculty.unlv.edu/research/examining-opposites/