1d:T7c0,# Result Summaries of Covariate Estimates from a fitted `logis_re` or `logis_cre` object Provide the summary statistics for the covariate estimates for a random/correlated random effect logistic model. ```r ## S3 method for class 'logis_cre' summary(object, parm, level = 0.95, null = 0, ...) ## S3 method for class 'logis_re' summary(object, parm, level = 0.95, null = 0, ...) ``` ## Arguments - `object`: a model fitted from `logis_re` or `logis_cre`. - `parm`: specifies a subset of covariates for which the result summaries should be output. By default, all covariates are included. - `level`: the confidence level during the hypothesis test, meaning a significance level of $1 - \text{level}$. The default value is 0.95. - `null`: a number defining the null hypothesis for the covariate estimates. The default value is `0`. - ``...``: additional arguments that can be passed to the function. ## Returns A data frame containing summary statistics for covariate estimates, with the following columns: - **Estimate**: the estimates of covariate coefficients. - **Std.Error**: the standard error of the estimate. - **Stat**: the test statistic. - **p value**: the p-value for the hypothesis test. - **CI.upper**: the lower bound of the confidence interval. - **CI.lower**: the upper bound of the confidence interval. ## Examples ```r data(ExampleDataBinary) outcome <- ExampleDataBinary$Y covar <- ExampleDataBinary$Z ProvID <- ExampleDataBinary$ProvID data <- data.frame(outcome, ProvID, covar) outcome.char <- colnames(data)[1] ProvID.char <- colnames(data)[2] wb.char <- c("z1", "z2") other.char <- c("z3", "z4", "z5") fit_cre <- logis_cre(data = data, Y.char = outcome.char, ProvID.char = ProvID.char, wb.char = wb.char, other.char = other.char) summary(fit_cre) data(ExampleDataBinary) outcome <- ExampleDataBinary$Y covar <- ExampleDataBinary$Z ProvID <- ExampleDataBinary$ProvID fit_re <- logis_re(Y = outcome, Z = covar, ProvID = ProvID) summary(fit_re) ```

summary.logis_re function