Examples of mixed-effects modeling with crossed random effects and with binomial data

Journal of Memory and Language

Volumn 59, Issue 4, 2008, Pages 413-425

  Quené, Hugo ^a   van den Bergh, Huub ^a  

^a UTRECHT UNIVERSITY   (Netherlands)

Author keywords

Analysis of variance; Crossed random effects; GLMM; Logistic regression; Mixed effects models

Indexed keywords

EID: 55649085770     PISSN: 0749596X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jml.2008.02.002     Document Type: Article

References (42)

1. Afshartous D., and Wolf M. Avoiding 'data snooping' in multilevel and mixed effects models. Journal of the Royal Statistical Society Series A (Statistics in Society) 170 4 (2007) 1035-1059
2. Baayen R.H., Davidson D.J., and Bates D.M. Mixed effects modeling with crossed random effects for subjects and items. Journal of Memory and Language 59 (2008) 390-412
3. Baayen R.H., Tweedie F.J., and Schreuder R. The subjects as a simple random effect fallacy: Subject variability and morphological family effects in the mental lexicon. Brain and Language 81 1-3 (2002) 55-65
4. Bailey R. Confounding. In: Johnson N., and Kotz S. (Eds). Encyclopedia of statistical sciences Vol. 2 (1982), Wiley, New York 128-134
5. Bates D. Fitting linear models in R: Using the lme4 package. R News 5 1 (2005) 27-30
6. Clark H. The language-as-fixed-effect fallacy: A critique of language statistics in psychological research. Journal of Verbal Learning and Verbal Behavior 12 (1973) 335-359
7. Cnaan A., Laird N.M., and Slasor P. Using the general linear mixed model to analyse unbalanced repeated measures and longitudinal data. Statistics in Medicine 16 20 (1997) 2349-2380
8. Cochran W., and Cox G. Experimental designs (1957), Wiley, New York
9. Connine C.M., and Titone D. Phoneme monitoring. Language and Cognitive Processes 11 6 (1996) 635-645
10. Cox D. Planning of experiments (1958), Wiley, New York
11. Faraway J.J. Extending the linear model with R: Generalized linear, mixed effects and nonparametric regression models (2006), Chapman and Hall, Boca Raton, FL
12. Goldstein H. Multilevel statistical models. 2nd (electronic update) ed. (1999), Edward Arnold, London
13. Guo G., and Zhao H. Multilevel modeling for binary data. Annual Review of Sociology 26 (2000) 441-462
14. Hoffmann L., and Rovine M.J. Multilevel models for the experimental psychologist: Foundations and illustrative examples. Behavior Research Methods 39 1 (2007) 101-117
15. Hosmer D.W., and Lemeshow S. Applied logistic regression. 2nd ed. (2000), Wiley, New York
16. Hox J. Applied multilevel analysis (1995), TT Publicaties, Amsterdam
17. Janse E., and Quené H. On measuring multiple lexical activation using the cross-modal semantic priming technique. In: Quené H., and van Heuven V.J. (Eds). On speech and language: Studies for Sieb G. Nooteboom (2004), LOT, Utrecht 105-114
18. Keene O.N. The log transformation is special. Statistics in Medicine 14 (1995) 811-819
19. Kleinbaum D.G. Logistic regression: A self-learning text (1992), Springer, New York
20. Kreft I.G., and De Leeuw J. Introducing multilevel modeling (1998), Sage, London
21. Limpert E., Stahel W.A., and Abbt M. Lognormal distributions across the sciences: Keys and clues. Bioscience 51 5 (2001) 341-352
22. Luke D.A. Multilevel modeling (2004), Sage, Thousand Oaks, CA
23. Maxwell S.E., and Delaney H.D. Designing experiments and analyzing data: A model comparison perspective. 2nd ed. (2004), Lawrence Erlbaum Associates, Mahwah, NJ
24. Meuffels B., and van den Bergh H. De ene tekst is de andere niet: The language-as-fixed-effect fallacy revisited: Statistische implicaties. Tijdschrift voor Taalbeheersing 28 4 (2006) 323-345
25. O'Brien R.G., and Kaiser M.K. MANOVA method for analyzing repeated measures designs: An extensive primer. Psychological Bulletin 97 2 (1985) 316-333
26. Pampel F.C. Logistic regression: A primer (2000), Sage, Thousand Oaks, CA
27. Pinheiro J.C., and Bates D.M. Mixed-effects models in S and S-Plus (2000), Springer, New York
28. Pitt M.A., and Samuel A.G. The use of rhythm in attending to speech. Journal of Experimental Psychology: Human Perception and Performance 16 3 (1990) 564-573
29. Pollatsek A., and Well A.D. On the use of counterbalanced designs in cognitive research: A suggestion for a better and more powerful analysis. Journal of Experimental Psychology: Learning, Memory, and Cognition 21 3 (1995) 785-794
30. Quené H. Multilevel modeling of between-speaker and within-speaker variation in spontaneous speech tempo. Journal of the Acoustical Society of America 123 2 (2008) 1104-1113
31. Quené H., and Port R. Effects of timing regularity and metrical expectancy on spoken-word perception. Phonetica 62 1 (2005) 1-13
32. Quené H., and van den Bergh H. On multi-level modeling of data from repeated measures designs: A tutorial. Speech Communication 43 1-2 (2004) 103-121
33. R Development Core Team. (2008). R: A language and environment for statistical computing. R Foundation for Statistical Computing. [Computer program (version 2.6.2)]. Available from: http://www.r-project.org.
34. Raaijmakers J.G., Schrijnemakers J.M., and Gremmen F. How to deal with "the language-as-fixed-effect fallacy": Common misconceptions and alternative solutions. Journal of Memory and Language 41 (1999) 416-426
35. Rasbash, J., Browne, W., Goldstein, H., Yang, M., Plewis, I., Healy, M., et al. (2000). A user's guide to MLwiN (Computer program (version 2.02) and manual. Available from: http://www.cmm.bristol.ac.uk/team/userman.pdf). Multilevel Models Project, Institute of Education, University of London.
36. Raudenbush S.W., and Bryk A.S. Hierarchical linear models: Applications and data analysis methods. 2nd ed. (2002), Sage, Thousand Oaks, CA
37. Richter T. What is wrong with ANOVA and multiple regression? Analyzing sentence reading times with hierarchical linear models. Discourse Processes 41 3 (2006) 221-250
38. Rietveld T., and Van Hout R. Statistics in language research: Analysis of variance (2005), Mouton de Gruyter, Berlin
39. Searle S.R., Casella G., and McCulloch C.E. Variance components (1992), Wiley, New York
40. Snijders T., and Bosker R. Multilevel analysis: An introduction to basic and advanced multilevel modeling (1999), Sage, London
41. van der Leeden R. Multilevel analysis of repeated measures data. Quality and Quantity 32 (1998) 15-19
42. Winer B. Statistical principles in experimental design. 2nd ed. (1971), McGraw-Hill, New York