A result of glmer (the object it returned, not a copy).
Optionaloptions: GlmerSummaryOptions
None yet (see GlmerSummaryOptions).
// R: summary(lme4::glmer(y ~ x + (1 | g), data, family = poisson))
const fit = glmer("y ~ x + (1 | g)", {
y: [2, 3, 6, 7, 8, 1, 0, 3, 2, 5, 4, 6, 9, 8, 13, 0, 2, 1, 4, 3],
x: [1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5],
g: ["a", "a", "a", "a", "a", "b", "b", "b", "b", "b", "c", "c", "c", "c", "c", "d", "d", "d", "d", "d"],
}, { family: "poisson" });
const s = glmerSummary(fit);
s.statisticName; // "z value"
s.pValue; // [0.5482, 6.226e-5]
s.minus2LogLik; // 78.785
s.dfResidual; // 17
The summary of a generalized linear mixed model fitted by glmer: the coefficient table with p-values, the correlation of the fixed effects, the quantiles of the scaled residuals, the information criteria, the variance components and the numbers of groups. Equivalent to
lme4::summary()in R.The p-values are from the normal distribution for every family, as lme4's (whose third column is named
t valuefor the families with a dispersion, although its p-values are normal ones). The values are those of the fit at the exact optimum (see glmer), so they typically differ from lme4's in the 4th to 6th significant digit. FornAGQ > 1,logLik,AIC,BICandminus2LogLikare those of the log-likelihood, as the fit's.