Analysis of covariance models for data from observational field studies

Journal of Wildlife Management

Volumn 72, Issue 1, 2008, Pages 34-43

  Riggs, Michael R ^a   Haroldson, Kurt J ^b   Hanson, Mark A ^b  

^a RHO INC   (United States)

^b MINNESOTA DEPARTMENT OF NATURAL RESOURCES   (United States)

Author keywords

Analysis of covariance; Causal inference; Confounding; Cross sectional study; Interaction; Longitudinal study; Model misspecification; Nonlinear models; Observational studies; Overfitted models

Indexed keywords

COVARIANCE ANALYSIS; ESTIMATION METHOD; EXPERIMENTAL DESIGN; MODELING; OBSERVATIONAL METHOD; SOFTWARE;

EID: 38649129930     PISSN: 0022541X     EISSN: None     Source Type: Journal    
DOI: 10.2193/2007-315     Document Type: Article

References (38)

1. Agresti, A. 1996. An introduction to categorical data analysis. John Wiley and Sons, New York, New York, USA.
2. Bretagnolle, J., and C. Huber-Carol. 1988. Effects of omitting covariates in Cox's model for survival data. Scandinavian Journal of Statistics 15:125-138.
3. Buckland, S., D. R. Anderson, K. P. Burnham, J. Laake, D. L. Borchers, and L. Thomas. 2001. Introduction to distance sampling. Oxford University Press, Oxford, United Kingdom.
4. Buckland, S., D. R. Anderson, K. P. Burnham, J. Laake, D. L. Borchers, and L. Thomas. 2004. Advanced distance sampling. Oxford University Press, Oxford, United Kingdom.
5. Burnham, K. P., and D. Anderson. 2002. Model selection and multi-model inference. Springer, New York, New York, USA.
6. Chambers, J. M., and T. J. Hastie. 1991. Statistical models in S. Chapman and Hall/CRC Press, Boca Raton, Florida, USA.
7. Cochran, W. G. 1969. The use of covariance in observational studies. Applied Statistics 18:270-275.
8. Everitt, B. S. 1998. The Cambridge dictionary of statistics. Cambridge University Press, New York, New York, USA.
9. Everitt, B. S., and T. Hothorn. 2006. Statistical analyses using R. Chapman Hall/CRC Press, Boca Raton, Florida, USA.
10. Faraway, J. 2004. Linear models with R. Chapman Hall/CRC Press, Boca Raton, Florida, USA.
11. Faraway, J. 2006. Extending the linear model with R. Chapman Hall/CRC Press, Boca Raton, Florida, USA.
12. Fitzmaurice, G. M., N. Laird, and J. Ware. 2004. Applied longitudinal analysis. John Wiley and Sons, Hoboken, New Jersey, USA.
13. Framstad, E., S. Engen, and N. Stenseth. 1985. Regression analysis, residual analysis and missing variables in regression models. Oikos 44:319-323.
14. Gilbert, R. O. 1987. Statistical methods for environmental pollution monitoring. Van Nostrand Reinhold, New York, New York, USA.
15. Hanson, M. A., and M. Riggs. 1995. Potential effects of fish predation on wetland invertebrates: a comparison of wetlands with and without fathead minnows. Wetlands 15:167-175.
16. Haroldson, K. J., R. O. Kimmel, M. R. Riggs, and A. H. Berner. 2006. Association of ring-necked pheasant, gray partridge, and meadowlark abundance to CRP grasslands. Journal of Wildlife Management 70:1276-1284.
17. Harrell, F. E. 2001. Regression modeling strategies with applications to linear models, logistic regression and survival analysis. Springer, New York, New York, USA.
18. Hauk, W., J. Neuhaus, J. Kalbfleish, and S. Anderson. 1991. The consequence of omitted covariates when estimating the odds ratios. Journal of Clinical Epidemiology 44:77-81.
19. Hosmer, D., and S. Lemeshow. 2000. Applied logistic regression. Second edition. John Wiley and Sons, New York, New York, USA.
20. Hurlbert, S. H. 1984. Pseudoreplication and the design of ecological field experiments. Ecological Monographs 54:187-211.
21. Kish, L. 1987. Statistical designs for research. John Wiley and Sons, New York, New York, USA.
22. Lin, D., B. M. Psaty, and R. Kronmal. 1998. Assessing the sensitivity of regression results to unmeasured confounders in observational studies. Biometrics 54:948-963.
23. Littell, R. C., G. A. Milliken, W. W. Stroup, R. D. Wolfinger, and O. Schabenberger. 2006. SAS system for mixed models. Second edition. SAS Institute, Cary, North Carolina, USA.
24. Littell, R. C., J. Pendergast, and R. Natarajan. 2000. Modeling covariance structures in the analysis of repeated measures data. Statistics in Medicine 19:1793-1819.
25. Millard, S. P., and N. K. Neerchal. 2000. Environmental statistics with S-PLUS. CRC Press, Boca Raton, Florida, USA.
26. Milliken, G. A., and D. E. Johnson. 2001. Analysis of messy data. Volume 3: analysis of covariance. Chapman and Hall/CRC Press. Boca Raton, Florida, USA.
27. Neuhaus, J., and N. Jewell. 1993. A geometric approach to assess bias due to omitted covariates in generalized linear models. Biometrika 80:807-815.
28. Palta, M., T.-J. Yao, and R. Velu. 1994. Testing for omitted variables and non-linearity in regression models for longitudinal data. Statistics in Medicine 13:2219-2231.
29. Peterson, S. A., N. S. Urquhart, and E. B. Welch. 1999. Sample representativeness: a must for reliable regional lake condition estimates. Environmental Science and Technology 33:1559-1565.
30. Peterson, W. J., and M. Lankester. 1991. Aspects of the epiziootiology of Parelaphostrongylus tenuis in a white-tailed deer population. Alces 27:183-192.
31. Pinheiro, J., and D. Bates. 2000. Mixed effects models in S and SPLUS. Springer, New York, New York, USA.
32. Rosenbaum, P. 2002. Observational studies. Second edition. Springer, New York, New York, USA.
33. Skalski, J. R., and D. S. Robson. 1992. Techniques for wildlife investigations: design and analysis of capture data. Academic Press, San Diego, California, USA.
34. Stevens, D., and A. Olsen. 2004. Spatially balanced sampling of natural resources. Journal of the American Statistical Association 99:262-278.
35. Therneau, T., and P. Grambsch. 2000. Modeling survival data: extending the Cox model. Springer-Verlag, New York, New York, USA.
36. Thompson, S. K. 2002. Sampling. Second edition. John Wiley and Sons, New York, New York, USA.
37. Thompson, S. K., and G. A. F. Seber. 1996. Adaptive sampling. John Wiley and Sons, New York, New York, USA.
38. U.S. Environmental Protection Agency. 2002. Guidance on choosing a sampling design for environmental data collection (QA/G-5S). EPA/240/R-02/005. Office of Environmental Information, Washington, D.C., USA. 〈http://www. epa.gov/QUALITY/qs-docs/g5s-final.pdf〉 Accessed 29 Oct 2007.