# Is using percentile data for linear regression a valid approach?

With this article from the CDC, I'm creating a log-log plot of all percentiles for the weight of men aged 25-34 (page 32) against all percentiles for the height of men aged 25-34 (page 33).

So the data looks something like...

percentile | log(height) | log(weight)

99 | 4.3307 | 5.5134

95 | 4.301 | 5.407

90 | 4.286 | 5.338

80 | 4.268 | 5.273

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My linear regression equation ended up with a slope of 4.0527, but I know the slope should be somewhere close to 2 from previous analyses for other datasets.

Is the misconception with this approach that the xth percentile observation in height is NOT necessarily the xth percentile observation in weight. Therefore, the ordered pairs on the log-log plot are incorrect?

I found a similar question here, but the author is only plotting percentiles for the predictor variable and not the response variable.

• I don't see that this is a useful regression. There isn't a pairing that makes sense for prediction or understanding between percentiles on different variables. Jun 21 at 6:21