# Summary Methods for Various Objects Generate concise summary statistics for objects created by the `Qval` package. The output is a named list tailored to the class of the input: - **`CDM`**: contains the original call, dataset dimensions, model fit object, and attribute-pattern distribution. - **`validation`**: contains the original call, suggested Q-matrix, and original Q-matrix. - **`sim.data`**: contains the original call, dataset dimensions, and attribute-pattern distribution. - **`fit`**: contains the original call, relative fit indices and absolute fit indices. - **`is.Qident`**: contains the original call and results of whether the Q-matrix is identifiable. - **`att.hierarchy`**: contains the results of iterative attribute hierarchy exploration. ```r ## S3 method for class 'CDM' summary(object, ...) ## S3 method for class 'validation' summary(object, ...) ## S3 method for class 'sim.data' summary(object, ...) ## S3 method for class 'fit' summary(object, ...) ## S3 method for class 'is.Qident' summary(object, ...) ## S3 method for class 'att.hierarchy' summary(object, ...) ``` ## Arguments - `object`: An object of class `CDM`, `validation`, `sim.data`, `fit`, or `is.Qident`. - `...`: Currently unused. Additional arguments are ignored. ## Returns A named list with class `summary.` containing the components above. ## Methods (by class) * `summary(CDM)`: Summary method for `CDM` objects * `summary(validation)`: Summary method for `validation` objects * `summary(sim.data)`: Summary method for `sim.data` objects * `summary(fit)`: Summary method for `fit` objects * `summary(is.Qident)`: Summary method for `is.Qident` objects * `summary(att.hierarchy)`: Summary method for `att.hierarchy` objects ## Examples ```r set.seed(123) library(Qval) ################################################################ # Example 1: summary a CDM object # ################################################################ Q <- sim.Q(3, 20) IQ <- list(P0 = runif(20, 0, 0.2), P1 = runif(20, 0.8, 1)) data.obj <- sim.data(Q, N = 500, IQ = IQ, model = "GDINA", distribute = "horder") CDM.obj <- CDM(data.obj$dat, Q, model = "GDINA", method = "EM") summary(CDM.obj) ################################################################ # Example 2: summary a validation object # ################################################################ MQ <- sim.MQ(Q, 0.1) CDM.obj2 <- CDM(data.obj$dat, MQ) val.obj <- validation(data.obj$dat, MQ, CDM.obj2, method = "GDI") summary(val.obj) ################################################################ # Example 3: summary a sim.data object # ################################################################ data.obj2 <- sim.data(Q = sim.Q(3, 10), N = 1000) summary(data.obj2) ################################################################ # Example 4: summary a fit object # ################################################################ fit.obj <- fit(data.obj$dat, Q, model="GDINA") summary(fit.obj) ```

summary function