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Compute intraclass correlation coefficient

Source: R/icc_specs.r
icc_specs.Rd

[Deprecated] This function is deprecated because the new version of specr uses a new analytic framework. In this framework, you can decompose the variance simply by using the generic plot() function and adding the argument type = "variance", which also prints the variance components. This function extracts intraclass correlation coefficients (ICC) from a multilevel model. It can be used to decompose the variance in the outcome variable of a specification curve analysis (e.g., the regression coefficients). This approach summarises the relative importance of analytical choices by estimating the share of variance in the outcome (e.g., the regression coefficient) that different analytical choices or combinations therefor account for. To use this approach, one needs to estimate a multilevel model that includes all analytical choices as grouping variables (see examples).

Usage

icc_specs(model, percent = TRUE)

Arguments

model

a multilevel (i.e., mixed effects) model that captures the variances of the specification curve.

percent

a logical value indicating whether the ICC should also be printed as percentage. Defaults to TRUE.

Value

a data frame including the grouping variable, the random effect variances, the raw intraclass correlation coefficient (ICC), and the ICC in percent.

References

  • Hox, J. J. (2010). Multilevel analysis: techniques and applications. New York: Routledge.

See also

plot_variance() to plot the variance decomposition.

Examples

# Step 1: Run spec curve analysis
results <- run_specs(df = example_data,
                     y = c("y1", "y2"),
                     x = c("x1", "x2"),
                     model = c("lm"))
#> Warning: `run_specs()` was deprecated in specr 1.0.0.
#> ℹ Please use `specr()` instead.
#> ℹ Set up the specifications with `setup()` first.

# Step 2: Estimate a multilevel model without predictors
model <- lme4::lmer(estimate ~ 1 + (1|x)  + (1|y), data = results)

# Step 3: Estimate intra-class correlation
icc_specs(model)
#> Warning: `icc_specs()` was deprecated in specr 1.0.0.
#> ℹ Please use `plot(<specr.object>, type = "variance")` instead.
#>        grp         vcov          icc      percent
#> 1        x 2.078321e-09 8.647959e-09 8.647959e-07
#> 2        y 1.971133e-01 8.201945e-01 8.201945e+01
#> 3 Residual 4.321178e-02 1.798055e-01 1.798055e+01