fit_model_rep

Estimates the GLMM model for concordance setting

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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

fit_model_rep function

<dl><dt>data</dt>
<dd>A data frame containing at least two columns: outcome (named as y) and subject identifier (named as id).</dd>
<dt>fam</dt>
<dd>Character string. The within-subjects pdf to use. Valid options are: "poisson" (default) for Poisson pdf; "nbinom1" for Negative Binomial pdf with additive extradispersion; "nbinom2" for Negative Binomial pdf with proportional extradispersion; "zip" for zero-inflated Poisson pdf; "zinb1" for zero-inflated nbinom1 pdf; "zinb2" for zero-inflated nbinom2 pdf;</dd></dl>

Arguments

Estimates GLMM. Repeatability setting. — fit_model_rep

<dl>

<dt>data</dt>
<dd>A data frame containing at least two columns: outcome (named as y) and subject identifier (named as id).</dd>


<dt>fam</dt>
<dd>Character string. The within-subjects pdf to use. Valid options are: "poisson" (default) for Poisson pdf; "nbinom1" for Negative Binomial pdf with additive extradispersion; "nbinom2" for Negative Binomial pdf with proportional extradispersion; "zip" for zero-inflated Poisson pdf; "zinb1" for zero-inflated nbinom1 pdf; "zinb2" for zero-inflated nbinom2 pdf;</dd>

</dl>

fit_model_rep: Estimates GLMM. Repeatability setting.

Description

Usage

Value

Arguments