References

Balota, D. A., Yap, M. J., Hutchison, K. A., Cortese, M. J., Kessler, B., Loftis, B., Neely, J. H., Nelson, D. L., Simpson, G. B., & Treiman, R. (2007). The English lexicon project. Behavior Research Methods, 39(3), 445–459. https://doi.org/10.3758/bf03193014

Bates, D., Maechler, M., Bolker, B. M., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01

Bouchet-Valat, M., & Kamiński, B. (2023). DataFrames.jl: Flexible and fast tabular data in Julia. Journal of Statistical Software, 107(4), 1–32. https://doi.org/10.18637/jss.v107.i04

Box, G. E. P. (1950). Problems in the analysis of growth and wear curves. Biometrics, 6(4), 362. https://doi.org/10.2307/3001781

Box, G. E. P., & Cox, D. R. (1964). An analysis of transformations. Journal of the Royal Statistical Society: Series B (Methodological), 26(2), 211–243. https://doi.org/10.1111/j.2517-6161.1964.tb00553.x

Box, G. E. P., & Tiao, G. C. (1973). Bayesian inference in statistical analysis. Addison-Wesley.

Danisch, S., & Krumbiegel, J. (2021). Makie.jl: Flexible high-performance data visualization for Julia. Journal of Open Source Software, 6(65), 3349. https://doi.org/10.21105/joss.03349

Davies, O. L., & Goldsmith, P. L. (Eds.). (1972). Statistical methods in research and production (4th ed.). Hafner.

Davis, C. S. (2002). Statistical methods for the analysis of repeated measurements. In Springer Texts in Statistics (pp. xxiv + 415). New York, NY: Springer. https://doi.org/10.1007/b97287

Elston, R. C., & Grizzle, J. E. (1962). Estimation of time-response curves and their confidence bands. Biometrics, 18, 148–159. https://doi.org/10.2307/2527453

Harper, F. M., & Konstan, J. A. (2016). The MovieLens datasets. ACM Transactions on Interactive Intelligent Systems, 5(4), 1–19. https://doi.org/10.1145/2827872

Huq, N. M., & Cleland, J. (1990). Bangladesh fertility survey 1989 (main report). National Institute of Population Research; Training.

Kamiński, B. (2023). Julia for data analysis. Manning.

Pinheiro, J. C., & Bates, D. M. (2000). Mixed-effects models in S and S-Plus (pp. xvi + 528). New York, NY: Springer. https://doi.org/10.1007/b98882

Powell, M. J. (2009). The BOBYQA algorithm for bound constrained optimization without derivatives. Cambridge NA Report NA2009/06, University of Cambridge, Cambridge, 26.

Rasbash, J., Browne, W., Goldstein, H., Yang, M., & Plewis, I. (2000). A user’s guide to MLwiN. Multilevel Models Project, Institute of Education, University of London.

Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Sage.

Sakamoto, Y., Ishiguro, M., & Kitagawa, G. (1986). Akaike information criterion statistics (p. 290). Reidel.

Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6, 461–464.

Tierney, L., & Kadane, J. B. (1986). Accurate approximations for posterior moments and marginal densities. Journal of the American Statistical Association, 81(393), 82–86. https://doi.org/10.1080/01621459.1986.10478240

Wickham, H. (2011). The split-apply-combine strategy for data analysis. Journal of Statistical Software, 40(1), 1–29. https://doi.org/10.18637/jss.v040.i01

Software versions

versioninfo()

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 16 × Intel(R) Xeon(R) E-2288G CPU @ 3.70GHz
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, skylake)
Threads: 16 default, 0 interactive, 8 GC (on 16 virtual cores)
Environment:
  JULIA_PROJECT = @.
  JULIA_LOAD_PATH = @:@stdlib

using LinearAlgebra
BLAS.get_config()

LinearAlgebra.BLAS.LBTConfig
Libraries: 
└ [ILP64] libopenblas64_.so

using Pkg
Pkg.status()

Project EmbraceUncertainty v0.1.0
Status `~/Work/EmbraceUncertainty/Project.toml`
  [cbdf2221] AlgebraOfGraphics v0.10.4
  [69666777] Arrow v2.8.0
  [6e4b80f9] BenchmarkTools v1.6.0
  [336ed68f] CSV v0.10.15
  [13f3f980] CairoMakie v0.13.4
  [324d7699] CategoricalArrays v0.10.8
  [8be319e6] Chain v0.6.0
  [9a962f9c] DataAPI v1.16.0
  [75880514] DataFrameMacros v0.4.1
  [a93c6f00] DataFrames v1.7.0
  [31c24e10] Distributions v0.25.119
  [8f03c58b] Effects v1.4.0
  [da1fdf0e] FreqTables v0.4.6
  [38e38edf] GLM v1.9.0
  [ff71e718] MixedModels v4.34.1
  [7e9fb7ac] MixedModelsDatasets v0.1.2
  [b12ae82c] MixedModelsMakie v0.4.7
  [76087f3c] NLopt v1.1.3
  [2dfb63ee] PooledArrays v1.4.3
  [27983f2f] RectangularFullPacked v0.2.1
  [6c6a2e73] Scratch v1.2.1
  [5064a6a7] StandardizedPredictors v1.0.1
  [82ae8749] StatsAPI v1.7.0
  [2913bbd2] StatsBase v0.34.5
  [3eaba693] StatsModels v0.7.4
  [bd369af6] Tables v1.12.0
  [337ecbd1] TidierPlots v0.11.1
  [9d95f2ec] TypedTables v1.4.6
  [a5390f91] ZipFile v0.10.1
  [ade2ca70] Dates v1.11.0
  [f43a241f] Downloads v1.6.0
  [37e2e46d] LinearAlgebra v1.11.0
  [d6f4376e] Markdown v1.11.0
  [44cfe95a] Pkg v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v0.7.0

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