a modification of the tidy command that adds the effect size (confidence intervals for the adjusted R^2) for linear hypothesis testing contrasts (joint F-test) using glht
Arguments
- model
contrast model from
multcomp::glht()- label
label for the contrast term (default: joined contrast names)
- ci
confidence interval (0, 1)
See also
Other model summary helpers:
get_lm_multicollinearity(),
models2coefs(),
models2omni(),
r_sq_to_adj_r_sq(),
renamed_tidy(),
tidy_es(),
tidy_es_cope_t(),
tidy_es_lm(),
tidy_es_lmer()
Other contrast or COPE helpers:
check_contrast_orthogonality(),
gen_contrast_blank(),
gen_contrast_ss(),
gen_data_jn(),
plot.jn_df(),
tidy_es_cope_t()
Examples
model_fit <- lm(salary ~ rank + discipline, data = carData::Salaries)
c <- gen_contrast_ss(model_fit, x = "rank")[-1, ]
model_fit_cope_F <- multcomp::glht(model_fit, c)
tidy_es_cope_F(model_fit_cope_F, label = "rank")
#> lh op rh ss df ms F p r_sq_adj
#> 1 salary ~ rank 152810893487 2 76405446744 148.9164 7.267053e-49 0.4282263
#> r_sq_adj_ci_ll r_sq_adj_ci_ul
#> 1 0.3698418 1