VetResearchLMM: Linear Mixed Models with Applications in Veterinary Research

The VetResearchLMM package gives the data sets and every analysis of Duchateau, Janssen and Rowlands (1998), Linear Mixed Models. An Introduction with Applications in Veterinary Research, with its own engine for linear mixed models. The engine gives the results that the book prints from SAS PROC MIXED and PROC GLM, and extends them.

Functions

vlm_fit()

fits a linear mixed model by REML, ML or Type 3 moments: covariance parameters, fixed-effects solution, Type 3 or Type 1 tests and fit statistics.

vlm_random(), vlm_repeated()

random coefficients (VC or UN) and residual structures (CS, AR(1), SP(POW), UN).

vlm_lsmeans(), vlm_estimate(), vlm_contrast()

least-squares means, estimates in the broad and narrow inference spaces, and contrasts.

vlm_blup()

best linear unbiased predictions of the random effects.

vlm_ems()

analysis of variance with expected mean squares and synthesised F tests.

vlm_compare()

information criteria and likelihood ratio tests of several fits.

vlm_interpret(), vlm_cite(), vlm_app()

plain-language interpretation, references and a shiny application.

emmeans_mixed_model(), report_mixed_model()

the helpers of version 1.1.0, now also for vlm_fit results.

The help pages Examp1.3.2 to Examp3.3 give the code of every example of the book, and the data sets are ex121 to ex127, ex31, ex32 and ex33.

References

Duchateau, L., Janssen, P. and Rowlands, G. J. (1998). Linear Mixed Models. An Introduction with Applications in Veterinary Research. International Livestock Research Institute, Nairobi.

See also

Useful links:

• https://myaseen208.com/VetResearchLMM/

• https://github.com/myaseen208/VetResearchLMM

• Report bugs at https://github.com/myaseen208/VetResearchLMM/issues

Author

Muhammad Yaseen (myaseen208@gmail.com); the book and its data: Luc Duchateau, Paul Janssen and John Rowlands.