generics::tidy() and generics::glance() methods for
"lsastrat_estimate" objects, returning the broom-style tidy data frame of
coefficients and a one-row model summary. This lets lsastrat results flow
into the broom/tidyverse ecosystem (tables, plots, dplyr).
Usage
tidy(x, ...)
glance(x, ...)
# S3 method for class 'lsastrat_estimate'
tidy(x, ...)
# S3 method for class 'lsastrat_estimate'
glance(x, ...)Value
tidy() a data frame with columns term, estimate, std.error,
statistic, df, p.value, conf.low, conf.high; glance() a
one-row data frame of estimator metadata.
Examples
data(pisa_mini)
g <- social_gradient(pisa_mini, paste0("PV", 1:10, "MATH"), "ESCS",
"W_FSTUWT", repweights = paste0("W_FSTURWT", 1:64))
generics::tidy(g)
#> term estimate std.error statistic df p.value conf.low
#> 1 slope 41.357302 1.830573 22.5925470 399.3701 2.112631e-73 37.758539
#> 2 strength 20.188700 1.799350 11.2199971 389.1354 1.679262e-25 16.651036
#> 3 curvature 1.025083 1.596808 0.6419579 406.6947 5.212622e-01 -2.113944
#> conf.high
#> 1 44.956065
#> 2 23.726363
#> 3 4.164111
generics::glance(g)
#> estimator n_pv nobs design_based
#> 1 social_gradient 10 2048 TRUE