Post-workshop revisions

- Added Bayesian tSpectacles
- Added assumptions same as frequentist
- Added JASP priors plot

docs/guide.Rmd

@@ -372,6 +372,7 @@ We have very strong evidence for the model with no interaction.
 * *Psychonomic Bulletin & Review* special issue on [Bayesian methods for advancing psychological science](https://link.springer.com/journal/13423/25/1/page/1)
 * [`BayesFactor`](https://richarddmorey.github.io/BayesFactor/) package
 * [JASP](https://jasp-stats.org/) statistical software
+* [Bayesian Spectacles](https://www.bayesianspectacles.org/) blog
 * [Understanding Bayes](https://alexanderetz.com/understanding-bayes/) blog
 
 ***

docs/presentation.Rmd

@@ -255,8 +255,17 @@ $\frac{P(D|H_0)}{P(D|H_1)}$
 ## Potential issues
 
 \pause
-* Results can be sensitive to priors
+* Rely on same assumptions as frequentist statistics
 \pause
+* Results can be sensitive to priors
+
+\centering \includegraphics[height=1.5in]{../figures/jasp_priors_plot.png} 
+
+
+## Potential issues
+
+* Rely on same assumptions as frequentist statistics
+* Results can be sensitive to priors
 * Still use cutoffs
 \pause
 * Not accepted in the field
@@ -387,6 +396,7 @@ $BF_{interaction} = \frac{16}{14} = 1.14$
 * *Psychonomic Bulletin & Review* special issue on [Bayesian methods for advancing psychological science](https://link.springer.com/journal/13423/25/1/page/1)
 * [`BayesFactor`](https://richarddmorey.github.io/BayesFactor/) package
 * [JASP](https://jasp-stats.org/) statistical software
+* [Bayesian Spectacles](https://www.bayesianspectacles.org/) blog
 * [Understanding Bayes](https://alexanderetz.com/understanding-bayes/) blog
 * Anderson, D. R. (2008). [Model Based Inference in the Life Sciences]( http://www.springer.com/life+sci/ecology/book/978-0-387-74073-7). New York: Springer.
 * Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). [Bayesian Data Analysis](http://www.stat.columbia.edu/~gelman/book/) (Third Edition). Boca Raton, FL: CRC Press.

src/bf_analysis.R

@@ -151,21 +151,17 @@ ggplot(datafile, aes(x = rt, y = choice)) +
   geom_point() +  # plot individual points in grey
   geom_smooth(method = "lm") +  # plot regression line and CI
   labs(x = "Reaction time", y = "Choice proportion")
-ggplot(datafile, aes(x = pre, y = choice)) +
+ggplot(datafile, aes(x = age, y = choice)) +
   geom_point() +  # plot individual points in grey
   geom_smooth(method = "lm") +  # plot regression line and CI
-  labs(x = "Pre ratings", y = "Choice proportion")
-ggplot(datafile, aes(x = post, y = choice)) +
-  geom_point() +  # plot individual points in grey
-  geom_smooth(method = "lm") +  # plot regression line and CI
-  labs(x = "Post ratings", y = "Choice proportion")
+  labs(x = "Age", y = "Choice proportion")
 
 ## Frequentist
-summary(lm(choice ~ rt + pre + post, data = datafile))  # conduct frequentist linear regression
+summary(lm(choice ~ rt + age, data = datafile))  # conduct frequentist linear regression
 
 ## Bayesian
-regressionBF(choice ~ rt + pre + post, data = datafile)  # conduct Bayesian linear regression
-head(regressionBF(choice ~ rt + pre + post, data = datafile))  # order results by BF
+regressionBF(choice ~ rt + age, data = datafile)  # conduct Bayesian linear regression
+head(regressionBF(choice ~ rt + age, data = datafile))  # order results by BF