"plot"(x, which="dfbetas", sort=FALSE, to.sort=NA, abs=FALSE, cutoff=0,
parameters=seq_len(ncol(estex$alt.fixed)), groups=seq_len(nrow(estex$alt.fixed)), ...)"dfbetas" to visualize dfbetas, "cook" to plot the cook's distances, "pchange" to plot the percentage change, and "sigtest" to plot the test statistic of a parameter estimate after deletion of specific cases.sort=TRUE The values of the selected measure of influence are ordered based on magnitude before visualization. If sort=FALSE (default) no sorting takes place.parameters), this parameter can be omitted. If multiple variables are visualized, and sort=TRUE, specification of to.sort is required, or an error is returned.abs=TRUE, the absolute values of the values of the selected measure of influence are visualized, while if abs=FALSE (default), both positive and negative values are possible. If both abs=TRUE and sort=TRUE, the abs parameters precedes the sort parameter, and thus the absolute values of the selected measure of influence are sorted.cutoff) value are plotted visually different from values not exceeding the cutoff. If cutoff=0 (default), no such differentiation is made in the way values are plotted.influence, dfbetas.estex,
cooks.distance.estex, pchange, sigtest
data(school23)
model <- lmer(math ~ structure + SES + (1 | school.ID), data=school23)
alt.est <- influence(model, "school.ID")
plot(alt.est, which="dfbetas")
plot(alt.est, which="cook", sort=TRUE)
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