Welcome!

Bayesian Regression Modeling with rstanarm

Jake Thompson

Psychometrician, ATLAS, University of Kansas

Overview

Introduction to Bayesian regression
Customizing Bayesian regression models
Evaluating Bayesian regression models
Presenting and using Bayesian regression models

A review of frequentist regression

Frequentist regression using ordinary least squares
The kidiq data

kidiq

# A tibble: 434 x 4
    kid_score mom_hs mom_iq mom_age
        <int>  <int>  <dbl>   <int>
  1        65      1  121.       27
  2        98      1   89.4      25
  3        85      1  115.       27
  4        83      1   99.4      25
  5       115      1   92.7      27
 # ... with 430 more rows

Predict child's IQ score from the mother's IQ score

lm_model <- lm(kid_score ~ mom_iq, data = kidiq)

summary(lm_model)

 Call:
 lm(formula = kid_score ~ mom_iq, data = kidiq)
 Residuals:
     Min      1Q  Median      3Q     Max 
 -56.753 -12.074   2.217  11.710  47.691 
 Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
 (Intercept) 25.79978    5.91741    4.36 1.63e-05 ***
 mom_iq       0.60997    0.05852   10.42  < 2e-16 ***
 ---
 Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
 Residual standard error: 18.27 on 432 degrees of freedom
 Multiple R-squared:  0.201,  Adjusted R-squared:  0.1991 
 F-statistic: 108.6 on 1 and 432 DF,  p-value: < 2.2e-16

Examing model coefficients

Use the broom package to focus just on the coefficients

library(broom)

tidy(lm_model)

            term   estimate  std.error statistic      p.value
   1 (Intercept) 25.7997778 5.91741208  4.359977 1.627847e-05
   2      mom_iq  0.6099746 0.05852092 10.423188 7.661950e-23

Be cautious about what the p-value actually represents

Comparing Frequentist and Bayesian probabilities

What's the probability a woman has cancer, given positive mammogram?
- P(+M | C) = 0.9
- P(C) = 0.004
- P(+M) = (0.9 x 0.004) + (0.1 x 0.996) = 0.1
What is P(C | M+)?
- 0.036

Spotify data

songs

 # A tibble: 215 x 7
    track_name    artist_name song_age valence tempo popularity duration_ms
    <chr>         <chr>          <int>   <dbl> <dbl>      <int>       <int>
  1 Crazy In Love Beyoncé         5351   70.1   99.3         72      235933
  2 Naughty Girl  Beyoncé         5351   64.3  100.0         59      208600
  3 Baby Boy      Beyoncé         5351   77.4   91.0         57      244867
  4 Hip Hop Star  Beyoncé         5351   96.8  167.          39      222533
  5 Be With You   Beyoncé         5351   75.6   74.9         42      260160
  6 Me, Myself a… Beyoncé         5351   55.5   83.6         54      301173
  7 Yes           Beyoncé         5351   56.2  112.          43      259093
  8 Signs         Beyoncé         5351   39.8   74.3         41      298533
  9 Speechless    Beyoncé         5351    9.92 113.          41      360440
 # ... with 206 more rows

Let's practice!

Bayesian Regression Modeling with rstanarm