I think there's a typo in the code in section 4.2.2. In 4.2.1. there's a model with a dummy dataset that takes 't' as the dependent variable. Then we run the model with the original dataset in 4.2.2 and the dependent variable is no longer 't', but rather 'rt'. So, the code is:
fit_press_trial <- brm(t ~ 1 + c_trial, data = df_spacebar, family = lognormal(), prior = c( prior(normal(6, 1.5), class = Intercept), prior(normal(0, 1), class = sigma), prior(normal(0, .01), class = b, coef = c_trial) ) )
But actually should be:
fit_press_trial <- brm(rt ~ 1 + c_trial, data = df_spacebar, family = lognormal(), prior = c( prior(normal(6, 1.5), class = Intercept), prior(normal(0, 1), class = sigma), prior(normal(0, .01), class = b, coef = c_trial) ) )
I think there's a typo in the code in section 4.2.2. In 4.2.1. there's a model with a dummy dataset that takes 't' as the dependent variable. Then we run the model with the original dataset in 4.2.2 and the dependent variable is no longer 't', but rather 'rt'. So, the code is:
fit_press_trial <- brm(t ~ 1 + c_trial, data = df_spacebar, family = lognormal(), prior = c( prior(normal(6, 1.5), class = Intercept), prior(normal(0, 1), class = sigma), prior(normal(0, .01), class = b, coef = c_trial) ) )
But actually should be:
fit_press_trial <- brm(rt ~ 1 + c_trial, data = df_spacebar, family = lognormal(), prior = c( prior(normal(6, 1.5), class = Intercept), prior(normal(0, 1), class = sigma), prior(normal(0, .01), class = b, coef = c_trial) ) )