Obtain upper level model estimates

ec_estimates_MU(est, quantiles = c(0.05, 0.95))

Arguments

est

is an 'echoice2' draw object (list)

quantiles

quantile for CI

Value

tibble with MU (upper level) summaries

Examples

data(icecream)
#run MCMC sampler (use way more than 20 draws for actual use)
icecream_est <- icecream %>% dplyr::filter(id<20) %>% vd_est_vdm(R=20, cores=2)
#> Using 2 cores
#>  MCMC in progress 
#> MCMC complete
#>  Total Time Elapsed: 0.02 minutes
#Upper-level summary
icecream_est %>% ec_estimates_MU
#> # A tibble: 21 × 12
#>    attribute lvl        par       mean     sd `CI-5%` `CI-95%` sig   model error
#>    <chr>     <chr>      <chr>    <dbl>  <dbl>   <dbl>    <dbl> <lgl> <chr> <chr>
#>  1 NA        NA         int    0.00250 0.213  -0.133   0.138   FALSE VD-c… EV1  
#>  2 Brand     BlueBell   Bran…  0.294   0.321   0.0896  0.498   TRUE  VD-c… EV1  
#>  3 Brand     BlueBunny  Bran… -0.0384  0.0531 -0.0722 -0.00460 TRUE  VD-c… EV1  
#>  4 Brand     Breyers    Bran… -0.248   0.0411 -0.275  -0.222   TRUE  VD-c… EV1  
#>  5 Brand     Dryers     Bran… -0.147   0.214  -0.283  -0.0108  TRUE  VD-c… EV1  
#>  6 Brand     HaagenDa   Bran…  0.0730  0.545  -0.274   0.420   FALSE VD-c… EV1  
#>  7 Brand     Store      Bran…  0.120   0.162   0.0168  0.224   TRUE  VD-c… EV1  
#>  8 Flavor    ChocChip   Flav… -0.0479  0.0354 -0.0705 -0.0254  TRUE  VD-c… EV1  
#>  9 Flavor    ChocDough  Flav…  0.292   0.101   0.228   0.357   TRUE  VD-c… EV1  
#> 10 Flavor    CookieCre… Flav… -0.178   0.132  -0.262  -0.0937  TRUE  VD-c… EV1  
#> # … with 11 more rows, and 2 more variables: reference_lvl <chr>,
#> #   parameter <chr>