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Table 4 Treatment effect estimates and confidence intervals of Facebook advertising in study 2

From: Do Online Advertisements Increase Political Candidates’ Name Recognition or Favorability? Evidence from Randomized Field Experiments

Subgroup Estimation procedure DV = heard of candidate DV = positive impression of candidate DV = recall of campaign issue DV = recall seeing online ad
All subjects Difference-in-means and randomization inference, no covariates 0.011
[−0.036, 0.061]
0.015
[−0.033, 0.067]
0.022
[−0.024,0.069]
0.057***
[0.024, 0.088]
Difference-in-means and randomization inference, covariate adjustment 0.004
[−0.036, 0.046]
0.011
[−0.028, 0.052]
0.020
[−0.024,0.064]
0.053***
[0.021, 0.083]
OLS, clustered standard errors and block fixed effects 0.021
[−0.022, 0.065]
−0.000
[−0.047, 0.047]
0.020
[−0.021,0.062]
0.059***
[0.029, 0.089]
N 3,085 3,085 2,320 2,459
Self-reported Facebook users only Difference-in-means and randomization inference, no covariates −0.003
[−0.069, 0.067]
0.011
[−0.045, 0.072]
0.012
[−0.051,0.077]
0.082***
[0.036, 0.126]
Difference-in-means and randomization inference, covariate adjustment −0.008
[−0.067, 0.053]
0.011
[−0.045, 0.072]
0.009
[−0.050, 0.070]
0.081***
[0.035, 0.125]
OLS, clustered standard errors and block fixed effects −0.013
[−0.082, 0.056]
−0.017
[−0.084, 0.049]
0.001
[−0.059, 0.061]
0.084***
[0.036, 0.134]
N 1,337 1,337 1,221 1,328
  1. Each cell records the estimate of the effect of being treated with online advertising on the dependent variable at the top of the column. 95 % confidence intervals are shown in brackets below each estimate. The first two rows in each panel employ randomization inference to estimate the uncertainty associated with the main point estimates, with the first row applying the procedure to unadjusted difference in means and the second employing covariate adjusted values. Rosenbaum (2002) 95 % confidence intervals for these results are calculated taking into account the blocked, clustered randomization scheme. The final row shows estimates employing OLS with block fixed effects, with 95 % confidence intervals calculated based on clustered standard errors
  2. p < 0.05, ** p < 0.01, *** p < 0.001 (one-tailed)