An R6 class that stores results for a contrast of the form
L θ - m estimated using a specified object inheriting from
FamModelFit
. Wald tests and confidence intervals for individual
rows of the contrast matrix as well as an overall Wald chi-square test of
the null hypothesis L θ - m = 0 are provided.
new()
Constructs a new instance of this class.
Contrast$new(model_fit, L_mat, m)
model_fit
An object inheriting from FamModelFit
.
L_mat
A contrast vector (1 df) or matrix
(>1 df) containing
one contrast in each row. The contrast vector must have a number of
elements equal to the number of model parameters. The contrast matrix
must be of full row rank and have a number of columns equal the number
of model parameters.
m
An optional vector containing the null value for each contrast.
Will be set to the zero vector of length nrow(L_mat)
if not
specified.
get_model_fit()
Returns model_fit
object.
Contrast$get_model_fit()
get_L_mat()
Returns L_mat
.
Contrast$get_L_mat()
get_m()
Returns m
.
Contrast$get_m()
get_L_theta_hat_m()
Returns L \hat{θ} - m.
Contrast$get_L_theta_hat_m()
get_V_L_theta_hat()
Returns L \hat{V}(\hat{θ}) L^{'}.
Contrast$get_V_L_theta_hat()
get_X2()
Returns Wald chi-square statistic for null hypothesis L θ - m = 0, which is (L \hat{θ} - m)^{'} [L \hat{V}(\hat{θ}) L^{'}]^{-1} (L \hat{θ} - m).
Contrast$get_X2()
get_df_X2()
Returns degrees of freedom of Wald chi-square statistic, which is the rank of L.
Contrast$get_df_X2()
get_p_X2()
Returns p-value for Wald chi-square statistic.
Contrast$get_p_X2()
print()
Formatted printing of the Contrast
object.
Contrast$print(...)
...
Arguments passed on to print_ests()
.
clone()
The objects of this class are cloneable with this method.
Contrast$clone(deep = FALSE)
deep
Whether to make a deep clone.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.