Slides and R code that produced them are online: https://github.com/tjmahr/Psych710_BayesLecture
I gave a similar, more code-heavy version of this talk to the R Users Group: https://github.com/tjmahr/MadR_RStanARM
I learned stats and R in this course with Markus Brauer and John Curtin.
I still refer to the slides from this course on contrast codes.
But now I’m a “Bayesian”.
Open Science Collaboration (2015) tries to replicate 100 studies published in 3 psychology different journals in 2008.
Scatter plot of original vs replicated effect sizes
I don’t know how to turn off the figure labeling feature
Some reactionary:
Some constructive:
All those unintentional acts and rituals to appease the Statistical Significance gods.
The usual way of doing things is insecure.
I want to avoid these questionable practices.
I want to level up my stats and explore new techniques.
I want something less finicky than statistical significance.
Cover of Data Analysis USing Regression and Multilevel/Hierarchical Models
I started reading the Gelman and Hill book.
arm
package.It emphasizes estimation, uncertainty and simulation.
Midway through, the book pivots to Bayesian estimation. (Multilevel models are kinda Bayesian because they borrow information across different clusters.)
I’m down a rabbit hole, writing Stan (Bayesian) models to fit the models from the ARM book, and there is an influx of Bayesian tools for R.
I eat all this up. I become a convert.
The replication crisis sparked my curiosity, and a wave of new tools and resources made it really easy to get started with Bayesian stats.
My goal with this approach has been to make better, more honest scientific summaries of observed data.
# Some toy data
davis <- car::Davis %>% filter(100 < height) %>% as_data_frame()
davis
#> # A tibble: 199 × 5
#> sex weight height repwt repht
#> <fctr> <int> <int> <int> <int>
#> 1 M 77 182 77 180
#> 2 F 58 161 51 159
#> 3 F 53 161 54 158
#> 4 M 68 177 70 175
#> 5 F 59 157 59 155
#> 6 M 76 170 76 165
#> 7 M 76 167 77 165
#> 8 M 69 186 73 180
#> 9 M 71 178 71 175
#> 10 M 65 171 64 170
#> # ... with 189 more rows