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tidy_es_cope_t

Source: R/tidy_es.R
tidy_es_cope_t.Rd

a modification of the tidy command that adds the effect size (confidence intervals for the contrast coefficient and adjusted R^2) for linear hypothesis testing contrasts (t-test) using glht

Usage

tidy_es_cope_t(
  model,
  ci = 0.95,
  mcc = c("single-step", "none", "uncorrected", "fdr", "FDR", "tukey", "tukey's HSD",
    "Tukey")
)

Arguments

model

contrast model from multcomp::glht()

ci

confidence interval (0, 1)

mcc

multiple comparison correction method. Options include "single-step" (default, which is what glht provides for Tukey's HSD), "none" (uncorrected), "fdr", "FDR", "tukey", "tukey's HSD", and "Tukey".

Value

data.frame

See also

Other model summary helpers: get_lm_multicollinearity(), models2coefs(), models2omni(), r_sq_to_adj_r_sq(), renamed_tidy(), tidy_es(), tidy_es_cope_F(), 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_F()

Examples

model_fit <- lm(salary ~ rank + discipline, data = carData::Salaries)
c <- gen_contrast_ss(model_fit, x = "rank")[-1, ]
model_fit_cope_t <- multcomp::glht(model_fit, c)
tidy_es_cope_t(model_fit_cope_t)
#>       lh op            rh        b       se  df         t            p
#> 1 salary  ~ rankAssocProf 13761.54 3960.661 393  3.474557 1.092134e-03
#> 2 salary  ~      rankProf 47843.84 3111.552 393 15.376197 1.776357e-15
#>     r_sq_adj   b_ci_ll  b_ci_ul r_sq_adj_ci_ll r_sq_adj_ci_ul
#> 1 0.02733473  5037.619 22485.47    0.007003391              1
#> 2 0.37403428 40990.199 54697.48    0.314935373              1