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Two-way and nested clustering via
cluster = c("g1","g2") and
nested = TRUE/FALSE, generating (1|g1/g2) or
(1|g1) + (1|g2) random-effects structures in
lme4.
Automatic knot / df selection
(df = "auto" in nl_fit() or via
nl_knots()) using AIC or BIC over a user-specified
grid.
Multilevel R-squared decomposition
(nl_r2()): Nakagawa-Schielzeth marginal R2m and conditional
R2c, plus a level-specific variance partition table (r2_mlm style) for
LMM, GLMM, and single-level OLS / GAM models.
Full postestimation suite:
nl_derivatives() — first and second derivatives with
delta-method confidence bands.nl_turning_points() — local maxima, minima, inflection
regions, and slope-direction regions.nl_plot() gains type = "slope",
"curvature", and "combo" in addition to the
original "trajectory".Built-in model comparison workflow
(nl_compare()): contrasts linear, polynomial, and spline
fits by AIC, BIC, log-likelihood, and likelihood-ratio tests.
B-spline basis (method = "bs",
bs_degree argument).
Random spline slopes
(random_slope = TRUE) to allow the nonlinear effect to vary
across clusters.
Cluster heterogeneity analysis
(nl_het()): plots cluster-specific trajectories (BLUPs) and
performs an LRT comparing random-slope vs random-intercept
models.
CI for glmerMod: approximate
confidence intervals via the delta method on the link scale (default,
fast) or parametric bootstrap (glmer_ci = "boot").
None. All v0.1.0 calls remain valid.
nl_r2() variance partition now correctly excludes NA
entries that could appear when lme4 internal row names are
ambiguous in nested models.nl_predict() now correctly computes CI when control
variables are stored as character (not factor) in the original
data.nl_plot() no longer errors when
time = NULL and the data frame has no time column.%||% is now imported from rlang rather
than defined internally, avoiding namespace masking.reformulas moved from Imports to Suggests (used
opportunistically for nobars(); falls back to
lme4::nobars() if unavailable).nl_fit(), nl_predict(),
nl_plot(), nl_summary(),
nl_icc().These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.