Summary statistics for model of nonprobsvy class.

Usage

# S3 method for nonprobsvy
summary(object, test = c("t", "z"), correlation = FALSE, cov = NULL, ...)

object: object of nonprobsvy class
test: Type of test for significance of parameters "t" for t-test and "z" for normal approximation of students t distribution, by default "z" is used if there are more than 30 degrees of freedom and "t" is used in other cases.
correlation: correlation Logical value indicating whether correlation matrix should be computed from covariance matrix by default FALSE.
cov: Covariance matrix corresponding to regression parameters
...: Additional optional arguments

An object of summary_nonprobsvy class containing:

call -- A call which created object.
pop_total -- A list containing information about the estimated population mean, its standard error and confidence interval.
sample_size -- The size of the samples used in the model.
population_size -- The estimated size of the population from which the nonoprobability sample was drawn.
test -- Type of statistical test performed.
control -- A List of control parameters used in fitting the model.
model -- A descriptive name of the model used, e.g., "Doubly-Robust", "Inverse probability weighted", or "Mass Imputation".
aic -- Akaike's information criterion.
bic -- Bayesian (Schwarz's) information criterion.
residuals -- Residuals from the model, providing information on the difference between observed and predicted values.
likelihood -- Logarithm of likelihood function evaluated at coefficients.
df_residual -- Residual degrees of freedom.
weights -- Distribution of estimated weights obtained from the model.
coef -- Regression coefficients estimated by the model.
std_err -- Standard errors of the regression coefficients.
w_val -- Wald statistic values for the significance testing of coefficients.
p_values -- P-values corresponding to the Wald statistic values, assessing the significance of coefficients.
crr -- The correlation matrix of the model coefficients, if requested.
confidence_interval_coef -- Confidence intervals for the model coefficients.
names -- Names of the fitted models.