An assessment of mixed-modeling approaches for characterizing profiles of time-varying response and predictor variables

Phytopathology

Volumn 100, Issue 10, 2010, Pages 1015-1029

  Madden, L V ^a   Paul, P A ^a  

^a OHIO STATE UNIVERSITY   (United States)

Author keywords

Maximum likelihood; Radial smoothing.

Indexed keywords

ARTICLE; BIOLOGICAL MODEL; FUNGUS SPORE; GIBBERELLA; HOST PATHOGEN INTERACTION; MICROBIOLOGY; PHYSIOLOGY; PLANT DISEASE; STATISTICAL MODEL; TIME; WHEAT;

GIBBERELLA; HOST-PATHOGEN INTERACTIONS; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PLANT DISEASES; SPORES, FUNGAL; TIME FACTORS; TRITICUM;

GIBBERELLA; GIBBERELLA ZEAE; TRITICUM AESTIVUM;

EID: 77958070441     PISSN: 0031949X     EISSN: None     Source Type: Journal    
DOI: 10.1094/PHYTO-01-10-0001     Document Type: Article

References (48)

1. Almon, S. 1965. The distributed lag between capital appropriations and expenditures. Econometrica 33:178-196.
2. Angelosante Bruno, A., Pace, L., Tomassetti, B., Coppola, E., Verdecchia, M., Pacioni, G., and Visconti, G. 2007. Estimation of fungal spore concentrations associated to meteorological variables. Aerobiologia 23:221-228.
3. Armstrong, B. 2006. Models for the relationship between ambient temperature and daily mortality. Epidemiology 17:624-631.
4. Batten, D. S., and Thornton, D. L. 1983. Polynomial distributed lags and the estimation of the St. Louis equation. Federal Reserve Bank of St. Louis Review April:13-25.
5. Berhane, K., and Thomas, D. C. 2002. A two-stage model for multiple time series data of counts. Biostatistics 3:21-32.
6. Braga, A. L. F., Zanobetti, A., and Schwartz, J. 2001. The time course of weather-related deaths. Epidemiology 12:662-667.
7. Burnham, K. P., and Anderson, D. R. 2002. Model Selection and Multimodel Inference: A Practical Information-Theoretical Approach, 2nd ed. Springer, New York.
8. Burnham, K. P., and Anderson, D. R. 2004. Multimodel inference: understanding AIC and BIC in model selection. Sociol. Methods Res. 33:261-304.
9. Crisafulli, D., Almqvist, C., Marks, G., and Tovey, E. 2007. Seasonal trends in house dust mite allergen in children's beds over a 7-year period. Allergy 62:1394-1400.
10. De Wolf, E., Francl, L., Lipps, P., Madden, L., Osborne, L., and Jin, Y. 2000. Factors affecting the development of wheat Fusarium head blight. Pages 137-140 in: Proc. 2000 Natl. Fusarium Head Blight Forum, Erlanger, KY.
11. Dominici, F., McDermott, A., Zeger, S., and Samet, J. M. 2003. Airborne particulate matter and mortality: timescale effects in four US cities. Am. J. Epidemiol. 157:1055-1065.
12. Edwards, L. J., Stewart, P. W., Muller, K. E., and Helms R. W. 2001. Linear equality constraints in the general linear mixed model. Biometrics 57:1185-1190.
13. Fitt, B. D. L., and McCartney, H. A. 1986. Spore dispersal in relation to epidemic models. Pages 311-345 in: Plant Disease Epidemiology: Population Dynamics and Management. K. J. Leonard and W. E. Fry, eds. Macmillan Publishers, New York.
14. Francl, L., Shaner, G., Bergstrom, G., Gilbert, J., Pedersen, W., DillMacky, R., Sweets, L., Corwin, B., Jin, Y., Gallenberg, D., and Wiersma, J. 1999. Daily inoculum levels of Gibberella zeae on wheat spikes. Plant Dis. 83:662-666.
15. Ganguli, B., and Wand, M. P. 2007. Feature significance in generalized additive models. Stat. Comput. 17:179-192.
16. Grinn-Gofron, A, and Mika, A. 2008. Selected airborne allergenic fungal spores and meteorological factors in Szczecin, Poland, 2004-2006. Aerobiologia 24:89-97.
17. Gujarati, D. N., and Porter, D. C. 2009. Basic Econometrics, 5th ed. McGraw-Hill, New York.
18. Gurrin, L. C., Scurrah, K. J., and Hazelton, M. L. 2005. Tutorial in biostatistics: spline smoothing with linear mixed models. Stat. Med. 24:3361-3381.
19. Hastie, T. J., and Tibshirani, R. J. 1990. Generalized Additive Models. Chapman & Hall, New York.
20. Hill, R. C., Griffiths, W. E., and Judge, G. G. 1997. Undergraduate Econometrics. John Wiley & Sons, New York.
21. Hsiao, C. 2003. Analysis of Panel Data. Cambridge University Press, UK.
22. Huang,Y. J., Fitt, B. D. L., Jedryczka, M., Dakowska, S., West, J., Gladders, P., Steed, J. M., and Li, Z.-Q. 2005. Patterns of ascospore release in relation to Phoma stem canker epidemiology in England (Leptosphaeria maculans) and Poland (Leptosphaeria biglobosa). Eur. J. Plant Pathol. 111:263-277.
23. Laranjeira, F. F., Bergamin Filho, A., Amorim, L., and Lopes, J. R. S. 2003. Comportamento sazonal da clorose variegada dos citros em três regiões do Estado de São Paulo. Fitopatol. Bras. 28:633-641.
24. 10. Risk Anal. 25:711-718.
25. Lima, M. A., Maffia, L. A., Barreto, R. W., and Mizubuti, E. S. G. 2009. Phytophthora infestans in a subtropical region: survival on tomato debris, temporal dynamics of airborne sporangia and alternative hosts. Plant Pathol. 58:87-99.
26. Littell, R. C., Milliken, G. A., Stroup, W. W., Wolfinger, R. D., and Schabenberger, O. 2006. SAS System for Mixed Models. SAS Institute, Cary, NC.
27. Liu, H., Zheng, Y., and Shen, J. 2008. Goodness-of-fit measures of R2 for repeated measures mixed effect models. J. Appl. Stat. 35:1081-1092.
28. Madden, L. V. 2009. Analysis of temporal observations in epidemics when there is no definable functional relationship between the variable and time. Pages 86-87 in: Proc. 10th Int. Epidemiol. Workshop. D. M. Gadoury, R. C. Seem, M. Moyer, and W. E. Fry, eds. Cornell University, New York.
29. Madden, L. V., Hughes, G., and van den Bosch, F. 2007. The Study of Plant Disease Epidemics. American Phytopathological Society Press, St. Paul, MN.
30. Morton, R., Kang, E. L., and Henderson, B. L. 2009. Smoothing splines for trend estimation and prediction in time series. Environmetrics 20:249-259.
31. Ngo, L., and Wand, M. P. 2004. Smoothing with mixed model software. J. Stat. Software 9:1-54 (online journal).
32. Pagano, M., and Hartley, M. J. 1981. On fitting distributed lag models subject to polynomial restrictions. J. Econometrics 16:171-198.
33. Paul, P. A., Lipps, P. E., De Wolf, E., Shaner, G., Buechley, G., Adhikari, T., Ali, S., Stein, J., Osborne, L., and Madden, L. V. 2007. A distributed lag analysis of the relationship between Gibberella zeae inoculum density on wheat spikes and weather variables. Phytopathology 97:1608-1624.
34. Peng, R. D., Dominici, F., and Louis, T. A. 2006. Model choice in time series studies of air pollution and mortality. J. R. Stat. Soc. A 169 (part 2):179-203.
35. Post, E., Hoaglin, D., Deck, L., and Larntz, K. 2001. An empirical Bayes approach to estimating the relation of mortality to exposure to particulate matter. Risk Anal. 21:837-842.
36. Ruppert, D., Wand, M. P., and Carroll, R. J. 2003. Semiparametric Regression. Cambridge University Press, Cambridge.
37. Schabenberger, O, and Gotway, C. A. 2005. Statistical Methods for Spatial Data Analysis. Chapman & Hall/CRC, Boca Raton, FL.
38. Schabenberger, O., and Pierce, F. J. 2002. Contemporary Statistical Models for the Plant and Soil Sciences. CRC Press, New York.
39. Schwartz, J. 2000. The distributed lag between air pollution and daily deaths. Epidemiology 11:320-326.
40. Schwartz, J., Laden, F., and Zanobetti, A. 2002. The concentration response relation between PM2.5 and daily deaths. Environ. Health Perspect. 110:1025-1029.
41. Sims, M., Elston, D. A., Larkham, A., Nussey, D. H., and Albon, S. D. 2007. Identifying when weather influences life-history traits of grazing herbivores. J. Anim. Ecol. 76:761-770.
42. Speed, T. 1991. Comment. Stat. Sci. 6:42-44.
43. Teklehaimanot, H. D., Lipsitch, M., Teklehaimanot, A., and Schwartz, J. 2004. Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia I. Patterns of lagged weather effects reflect biological mechanisms. Malaria J. 41:1-11.
44. Van Hemelrijck, M. J. J., Lindblade, K. A., Kubaje, A., Hamel, M. J., Odhiambo, F., Phillips-Howard, P. A., Laserson, K. F., Slutsker, L., and Feikin, D. R. 2009. Trends observed during a decade of paediatric sick visits to peripheral health facilities in rural western Kenya, 1997-2006. Trop. Med. Int. Health 14:62-69.
45. Welham, S. J., Cullis, B. R., Kenward, M. G., and Thompson, R. 2007. A comparison of mixed model splines for curve fitting. Aust. N. Z. J. Stat. 49:1-23.
46. Zanobetti, A., Schwartz, J., Samoli, E., Gryparis, A., Touloumi, G., Atkinson, R., Le Tertre, A, Bobros, J., Celko, M., Goren, A., Forsberg, B., Michelozzi, P., Rabczenko, D., Aranguez Ruiz, E., and Katsouyanni, K. 2002. Epidemiology 13:87-93.
47. Zanobetti, A., Wand, M. P., Schwartz, J., and Ryan, L. M. 2000. Generalized additive distributed lag models: quantifying mortality displacement. Biostatistics 1:279-292.
48. Zeger, S. L., Irizarry, R., and Peng, R. D. 2006. On time series analysis of public health and biomedical data. Annu. Rev. Public Health 27:57-79.