Analyses
Squire
REGRESSION, SECONDARY, REGRESSIONS
A zero-inflated negative binomial regression for count data was conducted to investigate differences between the control and intervention groups’ URE within COVID-related social media posts from March 1, 2020, to June 30, 2021. The distribution of relevant social media posts was skewed positive and met the assumption of overdispersion for negative binomial regressions. Subsequent to detecting a main effect, similar secondary analyses were conducted to examine the ways that legislators used research language in social media posts. Given the distribution pattern of the outcome variable, a low interclass correlation between legislators within states, and optimal model fit indices across potential modeling options, a zero-inflated negative binomial model was selected. The rate of having no social media posts containing both URE and COVID-19 markers in this sample was 69.95%. Excessive zeros contributing to overdispersion of the data may indicate that a portion of state legislators’ social media posts were not captured or that the state legislators do not post to a public social media account. Therefore, we adjusted for the zero-inflation using two indicators that would be likely to predict whether a state legislator created a social media post with URE at all or not—the Squire Rank Index and the intervention. The Squire Index, a measure of state legislative professionalism, indicates the institutional capacity of legislatures for engagement. The Rank version orders the states based on their raw index score [An additional set of analyses were conducted comparing health-related social media posts with URE markers during the baseline time period in order to examine differences between groups prior to the intervention.