print.RRglmGOF

Generalized Linear Mixed Model (GLMM) for Binary Randomized Response Data.
Includes Cauchit, Compl. Log-Log, Logistic, and Probit link functions for Bernoulli Distributed RR data.
RR Designs: Warner, Forced Response, Unrelated Question, Kuk, Crosswise, and Triangular.
Reference: Fox, J-P, Veen, D. and Klotzke, K. (2018). Generalized Linear Mixed Models for Randomized Responses. Methodology. <doi:10.1027/1614-2241/a000153>.

Jean-Paul Fox

GLMMRR

Generalized Linear Mixed Model (GLMM) for Binary Randomized
Response Data

Konrad Klotzke

Duco Veen

print.RRglmGOF function

<dl><dt>x</dt>
<dd>an object of class RRglmGOF.</dd>
<dt>digits</dt>
<dd>minimal number of significant digits (default: 3).</dd>
<dt>...</dt>
<dd>further arguments passed to or from other methods.</dd></dl>

Arguments

Print RRglmGOF values — print.RRglmGOF

<dl>

<dt>x</dt>
<dd>an object of class RRglmGOF.</dd>


<dt>digits</dt>
<dd>minimal number of significant digits (default: 3).</dd>


<dt>...</dt>
<dd>further arguments passed to or from other methods.</dd>

</dl>

print.RRglmGOF: Print RRglmGOF values

Description

Usage

Arguments