# Round numbers in reporting statistics

Dear professor and colleagues,

Is it good practice to round numbers during statistical analysis? For example, AUROC curve can be 0.789; can we round it to 0.79? If yes, can we apply same rule on confidence interval?

this is a good question because it can be dictated by convention, eg i think jounals will indicate how many decimals they want to see for the p-value. At some point you can round without any loss of info. For your auc example i think 2 decimal places is right but maybe 3 is the convention

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Depends indeed on context. Here is a relevant discussion.

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I love the question â€¦ I come from a physics background where our first lesson was in measurement error/uncertainty and some of those lessons still apply. For something like the AUC the number of decimal points depends on the accuracy (where the CI is the â€śuncertaintyâ€ť). If the CI is small, then more decimal points OK. Here are some examples

0.789 (0.781 to 0.799) - this is good because the uncertainty is in the thousandths.
0.789 (0.754 to 0.848) - this is not good - should be 0.79 (0.75 to 0.85)
0.789 (0.610 to 0.967) - this is not good - should be 0.8 (0.6 to 1)

Hope this helps

John

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Some nice guidelines on presenting statistical results here (including precision, although AUCs not directly mentioned). Guidelines for reporting of statistics for clinical research in urology - PMC

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