Above we estimated the effects of d_treatment_source on the outcomes y_share_report_email_num and y_share_report_fb_num. Do the same for the outcomes y_share_report_twitter_num and y_share_report_whatsapp_num.
Start by conducting two t-test for both outcomes. What do they indicate for sharing on Twitter and Whatsapp?
Use the code below and adapt it (step by step) to directly produce a table that includes the t-test results for the two outcomes.
Also estimate the treatment effects using a linear model and again produce a table with the output (below some code). We’ll need lm() to estimate the models and stargazer() to produce a nice tables (see example above).
Above we provided balance statistics for two covariates. There are two more covariates x_income_* and x_education_*. How would you proceed if you want to explore and show that treatment and control groups are balanced on them as well? (Tip: table())
What is your conclusion? Is there also a source effect for sharing per Twitter and Whatsapp analogue to sharing on Facebook (cf. Table 5.4)?