model_performance.ivreg

model

Can be <code>"all"</code>, <code>"common"</code> or a character vector of
metrics to be computed (some of <code>c("AIC", "AICc", "BIC", "R2", "RMSE", "SIGMA", "Sargan", "Wu_Hausman")</code>). <code>"common"</code> will compute AIC, BIC,
R2 and RMSE.

metrics

verbose

Arguments passed to or from other methods.

Performance of instrumental variable regression models

Utilities for computing measures to assess model quality,
which are not directly provided by R's 'base' or 'stats' packages.
These include e.g. measures like r-squared, intraclass correlation
coefficient (Nakagawa, Johnson & Schielzeth (2017)
<doi:10.1098/rsif.2017.0213>), root mean squared error or functions to
check models for overdispersion, singularity or zero-inflation and
more. Functions apply to a large variety of regression models,
including generalized linear models, mixed effects models and Bayesian
models.

Daniel Lüdecke

performance

Assessment of Regression Models Performance

Daniel L<c3><bc>decke

Dominique Makowski

Mattan S. Ben-Shachar

Indrajeet Patil

Philip Waggoner

Brenton M. Wiernik

Vincent Arel-Bundock

Martin Jullum

gjo11 

model_performance.ivreg function

Performance of instrumental variable regression models — model_performance.ivreg

Performance of instrumental variable regression models

model_performance.ivreg: Performance of instrumental variable regression models

Description

Usage

Arguments