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2016 | OriginalPaper | Buchkapitel

4. Adaptive Regression Modeling of Multivariate Continuous Outcomes

verfasst von : George J. Knafl, Kai Ding

Erschienen in: Adaptive Regression for Modeling Nonlinear Relationships

Verlag: Springer International Publishing

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Abstract

This chapter formulates and demonstrates adaptive regression modeling of means and variances for repeatedly measured continuous outcomes treated as multivariate normal. Analyses are presented of dental measurements of the distance in mm from the center of the pituitary to the pterygomaxillary fissure in terms of the age and gender of the child while accounting for dependence of dental measurements for the same child. These are example analyses of data with no missing outcome values. Analyses are also presented of strength in terms of time and type of weightlifting program while accounting for dependence of strength measurements for the same subject. These are example analyses of data with missing outcome values. Analyses of these data sets use marginal models based on order 1 autoregressive (AR1) correlations and exchangeable correlations (EC) and estimated with maximum likelihood (ML) or generalized estimating equations (GEE). They also use transition models, with the current outcome value a function of prior outcome values, and general conditional models, with the current outcome value a function of other, past as well as prior, outcome values. The issue of moderation is addressed, that is, how the effect of a predictor on an outcome can change with values of a moderator variable. For example, how the effect of age on the child’s dental measurements can change with the gender of the child. Moderation analyses are commonly based on interactions, but can be more generally based on geometric combinations, that is, products of power transforms of primary predictors using possibly different powers.

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Literatur
Zurück zum Zitat Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park: Sage. Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park: Sage.
Zurück zum Zitat Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychology research: Conceptual, strategic, and statistical considerations. Journal of Personality & Social Psychology, 51, 1173–1182. Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychology research: Conceptual, strategic, and statistical considerations. Journal of Personality & Social Psychology, 51, 1173–1182.
Zurück zum Zitat Brown, H., & Prescott, R. (1999). Applied mixed models in medicine. New York: John Wiley & Sons.MATH Brown, H., & Prescott, R. (1999). Applied mixed models in medicine. New York: John Wiley & Sons.MATH
Zurück zum Zitat Claeskens, G., & Hjort, N. L. (2009). Model selection and model averaging. Cambridge: Cambridge University Press.MATH Claeskens, G., & Hjort, N. L. (2009). Model selection and model averaging. Cambridge: Cambridge University Press.MATH
Zurück zum Zitat Diggle, P. J., Heagarty, P., Liang, K.-Y., & Zeger, S. L. (2002). Analysis of longitudinal data (2nd ed.). Oxford: Oxford University Press. Diggle, P. J., Heagarty, P., Liang, K.-Y., & Zeger, S. L. (2002). Analysis of longitudinal data (2nd ed.). Oxford: Oxford University Press.
Zurück zum Zitat Fitzmaurice, G. M., Laird, N. M., & Ware, J. H. (2011). Applied longitudinal analysis (2nd ed.). Hoboken, NJ: John Wiley & Sons.MATH Fitzmaurice, G. M., Laird, N. M., & Ware, J. H. (2011). Applied longitudinal analysis (2nd ed.). Hoboken, NJ: John Wiley & Sons.MATH
Zurück zum Zitat Kleinbaum, D. G., Kupper, L. L., Muller, K. E., & Nizam, A. (1998). Applied regression analysis and other multivariable methods (3rd ed.). Belmont, CA: Thomson Brooks/Cole.MATH Kleinbaum, D. G., Kupper, L. L., Muller, K. E., & Nizam, A. (1998). Applied regression analysis and other multivariable methods (3rd ed.). Belmont, CA: Thomson Brooks/Cole.MATH
Zurück zum Zitat Knafl, G. J., & Riegel, B. (2014). What puts heart failure patients at risk for poor medication adherence? Patient Preference and Adherence, 8, 1007–1018. Knafl, G. J., & Riegel, B. (2014). What puts heart failure patients at risk for poor medication adherence? Patient Preference and Adherence, 8, 1007–1018.
Zurück zum Zitat Morrison, D. F. (1967). Multivariate statistical models. New York: McGraw-Hill.MATH Morrison, D. F. (1967). Multivariate statistical models. New York: McGraw-Hill.MATH
Zurück zum Zitat Potthoff, R. F., & Roy, S. N. (1964). A generalized multivariate analysis of variance model useful especially for growth curve problems. Biometrika, 51, 313–326.MathSciNetCrossRefMATH Potthoff, R. F., & Roy, S. N. (1964). A generalized multivariate analysis of variance model useful especially for growth curve problems. Biometrika, 51, 313–326.MathSciNetCrossRefMATH
Zurück zum Zitat Riegel, B., & Knafl, G. J. (2014). Electronically monitored medication adherence predicts hospitalization in heart failure patients. Patient Preference and Adherence, 8, 1–13. Riegel, B., & Knafl, G. J. (2014). Electronically monitored medication adherence predicts hospitalization in heart failure patients. Patient Preference and Adherence, 8, 1–13.
Zurück zum Zitat Royston, P., & Sauerbrei, W. (2008). Multivariable model-building: A practical approach to regression analysis based on fractional polynomials for modelling continuous variables. Hoboken, NJ: John Wiley & Sons. Royston, P., & Sauerbrei, W. (2008). Multivariable model-building: A practical approach to regression analysis based on fractional polynomials for modelling continuous variables. Hoboken, NJ: John Wiley & Sons.
Zurück zum Zitat SAS Institute (2004). SAS/STAT 9.1 user’s guide. Cary, NC: SAS Institute. SAS Institute (2004). SAS/STAT 9.1 user’s guide. Cary, NC: SAS Institute.
Zurück zum Zitat Stone, M. (1977). An asymptotic equivalence of choice of model by cross-validation and Akaike’s criterion. Journal of the Royal Statistical Society, Series B, 39, 44–47.MathSciNetMATH Stone, M. (1977). An asymptotic equivalence of choice of model by cross-validation and Akaike’s criterion. Journal of the Royal Statistical Society, Series B, 39, 44–47.MathSciNetMATH
Zurück zum Zitat Verbeke, G., & Molenberghs, G. (2000). Linear mixed models for longitudinal data. New York: Springer.MATH Verbeke, G., & Molenberghs, G. (2000). Linear mixed models for longitudinal data. New York: Springer.MATH
Metadaten
Titel
Adaptive Regression Modeling of Multivariate Continuous Outcomes
verfasst von
George J. Knafl
Kai Ding
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-33946-7_4

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