se_r_Pois2

ICC standard error for Poisson model. Concordance setting

internal

Estimates the intraclass correlation coefficient (ICC) for count data to assess repeatability (intra-methods concordance) and concordance (between-method concordance). In the concordance setting, the ICC is equivalent to the concordance correlation coefficient estimated by variance components. The ICC is estimated using the estimates from generalized linear mixed models. The within-subjects distributions considered are: Poisson; Negative Binomial with additive and proportional extradispersion; Zero-Inflated Poisson; and Zero-Inflated Negative Binomial with additive and proportional extradispersion. The statistical methodology used to estimate the ICC with count data can be found in Carrasco (2010) <doi:10.1111/j.1541-0420.2009.01335.x>.

Josep Carrasco

iccCounts

Intraclass Correlation Coefficient for Count Data

se_r_Pois2 function

<dl><dt>b1</dt>
<dd>Intercept of GLMM</dd>
<dt>b2</dt>
<dd>Parameter related to between-subjects variance in the GLMM model</dd>
<dt>sb</dt>
<dd>Between-methods variability</dd>
<dt>CovB</dt>
<dd>Variance covariance matrix of b1 and b2</dd>
<dt>var.sb</dt>
<dd>Standard error of sb (in variance scale).</dd></dl>

Arguments

ICC standard error for Poisson model. Concordance setting — se_r_Pois2

<dl>

<dt>b1</dt>
<dd>Intercept of GLMM</dd>


<dt>b2</dt>
<dd>Parameter related to between-subjects variance in the GLMM model</dd>


<dt>sb</dt>
<dd>Between-methods variability</dd>


<dt>CovB</dt>
<dd>Variance covariance matrix of b1 and b2</dd>


<dt>var.sb</dt>
<dd>Standard error of sb (in variance scale).</dd>

</dl>

se_r_Pois2: ICC standard error for Poisson model. Concordance setting

Description

Usage

Value

Arguments