print.exametrika: Print Method for Exametrika Objects

In exametrika: Test Theory Analysis and Biclustering

Print Method for Exametrika Objects

Description

S3 method for printing objects of class "exametrika". This function formats and displays appropriate summary information based on the specific subclass of the exametrika object. Different types of analysis results (IRT, LCA, network models, etc.) are presented with customized formatting to highlight the most relevant information.

Usage

## S3 method for class 'exametrika'
print(x, digits = 3, ...)

Arguments

x	An object of class "exametrika" with various possible subclasses
digits	Integer indicating the number of decimal places to display. Default is 3.
...	Additional arguments passed to print methods (not currently used)

Details

The function identifies the specific subclass of the exametrika object and tailors the output accordingly. For most analysis types, the function displays:

• Basic model description and parameters

• Estimation results (e.g., item parameters, latent class profiles)

• Model fit statistics and diagnostics

• Visual representations where appropriate (e.g., graphs for network models, scree plots for dimensionality analysis)

When printing network-based models (LDLRA, LDB, BINET), this function visualizes the network structure using graphs, which can help in interpreting complex relationships between items or latent variables.

Value

Prints a formatted summary of the exametrika object to the console, with content varying by object subclass:

TestStatistics

Basic descriptive statistics of the test

Dimensionality

Eigenvalue analysis results with scree plot

ItemStatistics

Item-level statistics and psychometric properties

QitemStatistics

Item statistics for polytomous items

exametrikaData

Data structure details including response patterns and weights

IIAnalysis

Item-item relationship measures (tetrachoric correlations, etc.)

CTT

Classical Test Theory reliability measures

IRT/GRM

Item parameters, ability estimates, and fit indices

LCA/LRA

Class/Rank profiles, distribution information, and model fit statistics

Biclustering/IRM

Cluster profiles, field distributions, and model diagnostics

LDLRA/LDB/BINET

Network visualizations, parameter estimates, and conditional probabilities

Examples

# Print IRT analysis results with 4 decimal places
result <- IRT(J15S500)
print(result, digits = 4)

# Print Latent Class Analysis results
result_lca <- LCA(J15S500, ncls = 3)
print(result_lca)

exametrika documentation built on Aug. 21, 2025, 5:27 p.m.