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Performing Non-Compartmental Analysis with Julia and Pumas AI

Domino Data Lab

TIME – time points of measured pain score and plasma concentration (in hrs). As each dose is administered at TIME=0 (the other entries are times of concentration and pain measurement), we create an AMT column as follows: pain_df[:"AMT"] = ifelse.(pain_df.TIME.== and 3 to 8 hours. pain_df.TIME.== 0, pain_df.DOSE, missing).

Metrics 59
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Variance and significance in large-scale online services

The Unofficial Google Data Science Blog

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. Because individual observations have so little information, statistical significance remains important to assess.

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

For example, imagine a fantasy football site is considering displaying advanced player statistics. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. One reason to do ramp-up is to mitigate the risk of never before seen arms.

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LSOS experiments: how I learned to stop worrying and love the variability

The Unofficial Google Data Science Blog

In this post we explore why some standard statistical techniques to reduce variance are often ineffective in this “data-rich, information-poor” realm. Despite a very large number of experimental units, the experiments conducted by LSOS cannot presume statistical significance of all effects they deem practically significant.