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[CTIS] Add note that current SEs are unweighted #908

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9 changes: 8 additions & 1 deletion docs/api/covidcast-signals/fb-survey.md
Original file line number Diff line number Diff line change
Expand Up @@ -726,6 +726,13 @@ of zero, and in simulations improves the quality of the standard error
estimates. See the [Appendix](#appendix) for further motivation for these
estimators.

<div style="background-color:#FCC; padding: 10px 30px;"><strong>Note:</strong>
Currently the standard errors are calculated as though all survey weights are
equal, that is \(w^\text{part}_i = 1\) for all respondents. The result is that
reported standard errors are artificially narrow for weighted estimates. This
will be corrected in a future update to the API.
</div>

The pseudo-observation is not used in $$\hat{p}$$ and $$\hat{q}$$ themselves, to
avoid potentially large amounts of estimation bias, as $$p$$ and $$q$$ are
expected to be small.
Expand All @@ -750,7 +757,7 @@ knowing someone in their community who is sick. In this subsection we will
describe how survey weights are used to construct weighted estimates for these
indicators, using community CLI as an example.

In a given aggregation unit (for example, daily-county), let $$U_i$$ the
In a given aggregation unit (for example, daily-county), let $$U_i$$ denote the
indicator that the survey respondent knows someone in their community with CLI,
including their household, for survey $$i$$, out of $$m$$ surveys collected.
Also let $$w_i$$ be the weight that accompanies survey $$i$$, normalized to sum
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2 changes: 1 addition & 1 deletion docs/symptom-survey/contingency-tables.md
Original file line number Diff line number Diff line change
Expand Up @@ -173,7 +173,7 @@ for download, and specifies the survey questions on which they are based. See
the <a href="coding.html">survey instrument codebook</a> for the full text of
all questions.</div>

The files contain [weighted estimates](../api/covidcast-signals/fb-survey.md#survey-weighting)
The files contain [weighted estimates](../api/covidcast-signals/fb-survey.md#survey-weighting-and-estimation)
of the percent of respondents who fulfill one or several criteria. Estimates are
broken out by state, age, gender, race, ethnicity, occupation, and health
conditions.
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