Hello again everyone!
This will be a short post since I spent this week finishing the first draft of my final paper and sending it over to my advisor, so I didn’t make many new discoveries.
Since my sample size was only 16 states and I had so many independent variables(covid-19 restrictions, unemployment rate change, National Domestic Violence Hotline calls), my correlations in the multivariate regressions were usually not statistically significant(p>0.05). I had to drop variables from my regressions until I got statistically significant correlations. By doing this, I realized that the poverty rate and the unemployment rate had the strongest significant correlation(highest R^2 value to depression. It is interesting to note that when a bivariate regression was done comparing each independent variable with the dependent variable separately, the R^2 rates and p values were compared to the multivariate regression which shows an interdependency between the poverty rate and unemployment rate in terms of the increase in depression during the pandemic. This makes sense to me because by itself, the poverty level did not correlate to an increase in depression(most likely because it was not a trigger to cause an increase) but people who were already in poverty now had the added stressor of providing for their families while unemployed.
I will continue working on my paper and update you on my progress!