Even the tiniest error messages can indicate an invalid statistical analysis

November 25, 2015
By

(This article was first published on Realizations in Biostatistics, and kindly contributed to R-bloggers)

The other day, I was reading in a data set in R, and the function indicated that there was a warning about a parsing error on one line. I went ahead with the analysis anyway, but that small parsing error kept bothering me. I thought it was just one line of goofed up data, or perhaps a quote in the wrong place. I finally opened up the CSV file in a text editor, and found that the reason for the parsing error was that the data set was duplicated within the CSV file. The parsing error resulted from the reading of the header twice. As a result, anything I did afterward was suspect.

Word to the wise: track down the reasons for even the most innocuous-seeming warnings. Every stage of a statistical analysis is important, and small errors anywhere along the way and have huge consequences downstream. Perhaps this is obvious, but you still have to slow down and take care of the details.

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