summary(model_m <- lm(unaccept_i ~ condition*fiscal, data=d1))
summary(model_y <- lm(redis_i ~ condition*fiscal + unaccept_i, data=d1))

mod_med <- mediation::mediate(model_m, model_y,
                   covariates = list(fiscal = 0),
                   treat="condition",
                   mediator="unaccept_i",
                   boot=T,
                   sims = 5000)

psy_med <- psych::mediate(redis_i ~ condition*fiscal + (unaccept_i),
data=d1, plot=F, n.iter=5000)

#conditional effect of X on Y through M: (a1 + a3*W)*b
a1 <- mod_med$model.m$coefficients[2]
a3 <- mod_med$model.m$coefficients[4]
b <- mod_med$model.y$coefficients[4]

cond_fx_pap <- tibble(fis_val = c(mean(d1$fiscal)-sd(d1$fiscal),
                                  mean(d1$fiscal),
                                  mean(d1$fiscal)+sd(d1$fiscal)),
                  cond_ind_fx = (a1 + a3*fis_val)*b)