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Each column reports the results for the original dataset and the politically balanced dataset, respectively.
Each column reports the results from the original dataset and the balanced dataset.
Each column reports the same estimate including a different set of control variables.
Each column reports the OLS estimates of the regression equation for the main outcomes: employment, farm work, off-farm work, wage employment, and self-employment.
In the second and third rows, instead, each column reports results from a specification that distinguishes between contractor-only and business assistance living wage laws (by interacting the living wage variable with dummy variables for these types of laws, constructed to be mutually exclusive).
Each column reports separate model specification.
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Each week this column reports on a single strong buy.
The first column reports each factor as univariate HR's whereas the second and third column reports each factor and TRMT2A respectively as bivariate HR's.
The second column reports the results for self-reported BMI.
The next column reports the results for each regression method when using, as input descriptors, only the set of molecular descriptors.
The relative ranking portion of this analysis (Fig. 3, far right column) reports the overall vulnerability ranking for each community.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com