WaldTest

Computes a Wald Test for a parameter \(\bold{\theta}\)
with respect to a linear hypothesis
\( \bold{R} \bold{\theta}=\bold{c}\).

Functions for cognitive diagnosis modeling and multidimensional item response modeling
for dichotomous and polytomous item responses. This package enables the estimation of
the DINA and DINO model (Junker & Sijtsma, 2001, <doi:10.1177/01466210122032064>),
the multiple group (polytomous) GDINA model (de la Torre, 2011,
<doi:10.1007/s11336-011-9207-7>), the multiple choice DINA model (de la Torre, 2009,
<doi:10.1177/0146621608320523>), the general diagnostic model (GDM; von Davier, 2008,
<doi:10.1348/000711007X193957>), the structured latent class model (SLCA; Formann, 1992,
<doi:10.1080/01621459.1992.10475229>) and regularized latent class analysis
(Chen, Li, Liu, & Ying, 2017, <doi:10.1007/s11336-016-9545-6>).
See George, Robitzsch, Kiefer, Gross, and Uenlue (2017) <doi:10.18637/jss.v074.i02>
or Robitzsch and George (2019, <doi:10.1007/978-3-030-05584-4_26>)
for further details on estimation and the package structure.
For tutorials on how to use the CDM package see
George and Robitzsch (2015, <doi:10.20982/tqmp.11.3.p189>) as well as
Ravand and Robitzsch (2015).

Alexander Robitzsch

Cognitive Diagnosis Modeling

WaldTest function

<dl> <dt>delta</dt>
<dd>Estimated parameter</dd><dt>vcov</dt>
<dd>Estimated covariance matrix</dd><dt>R</dt>
<dd>Hypothesis matrix</dd><dt>nobs</dt>
<dd>Number of observations</dd><dt>cvec</dt>
<dd>Hypothesis vector</dd><dt>eps</dt>
<dd>Numerical value is added as ridge parameter of
the covariance matrix</dd></dl>

Arguments

Wald Test for a Linear Hypothesis — WaldTest

<dl>

 <dt>delta</dt>
<dd>Estimated parameter</dd>

<dt>vcov</dt>
<dd>Estimated covariance matrix</dd>

<dt>R</dt>
<dd>Hypothesis matrix</dd>

<dt>nobs</dt>
<dd>Number of observations</dd>

<dt>cvec</dt>
<dd>Hypothesis vector</dd>

<dt>eps</dt>
<dd>Numerical value is added as ridge parameter of
the covariance matrix</dd>

</dl>

WaldTest: Wald Test for a Linear Hypothesis

Description

Usage

Value

Arguments