#38220 | AsPredicted

As Predicted:COVID_SocialDistancing_Politics (#38220)

Created:       03/30/2020 10:04 AM (PT)

This is an anonymized version of the pre-registration.  It was created by the author(s) to use during peer-review.
A non-anonymized version (containing author names) should be made available by the authors when the work it supports is made public.

1) Have any data been collected for this study already?
It's complicated. We have already collected some data but explain in Question 8 why readers may consider this a valid pre-registration nevertheless.

2) What's the main question being asked or hypothesis being tested in this study?
**All the following hypothesis are for social distancing data after March 23rd. Data before that date was looked at in exploratory analyses and thus is not included in this pre-registration.**

We predict that as time goes by (after March 23rd and in April) and more COVID cases are announced across the United States that a link we observed in exploratory analyses - that conservative states and counties exhibit decreased social distancing (on March 23rd and earlier) - will begin to disappear. More specifically, we have found that the conservatism of states and counties predicts decreased social distancing (in terms of change in movement pre-Covid as tracked via phone GPS coordinates) on March 23rd and earlier (this link is not found for pre-COVID dates, e.g., February). Given these findings, we predict that after March 23rd, this link will continue but will begin to level off as time goes by and COVID spreads more and more across states and counties. Said another way, as the spread of COVID becomes more and more apparent, partisan differences in social distancing will likely disappear.

We also will examine whether the link between conservatism and social distancing on March 24th and after may be moderated by local orders to stay home and reduce social interactions (we have some preliminary evidence to suggest that this is the case before March 24th). We predict that local orders (e.g., stay at home orders; closing schools, etc) may reduce the link between conservatism and social distancing. That is, if stay at home orders are initiated, then conservatism should play less of a role in predicting social distancing then if such orders are not initiated. Indeed, local governments instituting such orders may explain, if true, why the link between conservatism and social distancing disappears (i.e., if this prediction pans out).

3) Describe the key dependent variable(s) specifying how they will be measured.
Link between social distancing (assessed via phone GPS coordinates) and conservatism (assessed via voting gap Trump vs. Clinton in 2016 election) at the State and County level for March 24th and onward. We will control for income, urbanacity, and # of COVID cases per capita. Other control variables may be added in further analyses to reduce the likelihood that the observed link is driven by a third-variable.

4) How many and which conditions will participants be assigned to?
No conditions.

5) Specify exactly which analyses you will conduct to examine the main question/hypothesis.
Regressions predicting social distancing with the above mentioned variables for March 24th and onward. Time series data will also be tested using mixed models (i.e., testing whether the link between conservatism and social distancing decreases over time).

6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations.
State: DC, Puerto Rico, and other non-states will not be included.
Counties: Approximately 100 counties will likely not be included because of data inconsistencies in terms of estimating number of COVID cases. If these 100 counties can be included they will be. Counties with a population under 5,000 will be excluded (supplemental analyses including these counties can be conducted to examine if findings replicate in this case).

7) How many observations will be collected or what will determine sample size?
No need to justify decision, but be precise about exactly how the number will be determined.

50 States. 3142 counties (before exclusions)

8) Anything else you would like to pre-register?
(e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?)

Data is technically accessible (as time goes by) in that the company that provides us with the social distancing data is sharing and will continue to share this data with us as it becomes accessible. We have not looked at any data after March 23rd, however (see point 1 above). Data for March 24th and 25th was shared with us March 30th but has not been analyzed yet. Data after March 25th has not been shared with us yet.