Error with objects of class stanreg about report

[strengejacke]

Should work now after updating parameters and performance from CRAN. Due to the "dependency chain", it might be you need to install insight from GitHub first, before installing parameters and performance (sorry for the inconvenience...).

[strengejacke]

library(report)
library(rstanarm)
z <- stan_glm(mpg ~ cyl, data = mtcars, refresh = 0)
report(z)

We fitted a Bayesian linear model (estimated using MCMC sampling with 4 chains of 2000 iterations and a warmup of 1000) to predict mpg with cyl (formula = mpg ~ cyl). Priors over parameters were set as normal (mean = 0.00, SD = 8.44) distributions. The Region of Practical Equivalence (ROPE) percentage was defined as the proportion of the posterior distribution within the [-0.60, 0.60] range. The 89% Credible Intervals (CIs) were based on Highest Density Intervals (HDI). Parameters were scaled by the mean and the SD of the response variable. Effect sizes were labelled following Funder's (2019) recommendations.The model's explanatory power is substantial (R2's median = 0.71, 89% CI [0.60, 0.82], adj. R2 = 0.68). The model's intercept, corresponding to mpg = 0 and cyl = 0, is at 37.81 (89% CI [34.51, 41.47], 0% in ROPE). Within this model:

• The effect of cyl has a probability of 100% of being negative and can be considered as large and significant (median = -2.87, 89% CI [-3.41, -2.33], 0% in ROPE, std. median = -0.85). The algorithm successfuly converged (Rhat = 1.000) and the estimates can be considered as stable (ESS = 3478).

^{Created on 2020-03-04 by the reprex package (v0.3.0)}