Analysis of Longitudinal Data (2nd ed.) (Book)
By Tapabrata Maiti. 2004
892 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/7971d9b47efc01abf451ffdf4761a7d19ee5a3ee
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Jianqing Fan
- Tommaso Cai
- Sara A. van de Geer
- Francis R. Bach
- Karim Lounici
- Victor Chernozhukov
- Martin J. Wainwright
- Ming Yuan
Citations in the corpus
- Foundations of Linear and Generalized Linear Models (2015, background): “See Diggle et al. (2002, Chapter 5), Littell et al. (2000), and Verbeke and Molenberghs (2000, Chapter 9, 10) for examples.”
- Likelihood Ratio Tests for Dependent Data with Applications to Longitudinal and Functional Data Analysis (2014, background): “Statistical inference for the mean function has been one of the main foci of LDA research (Diggle et al., 2002).”
- Using Generalized Estimating Equations for Longitudinal Data Analysis (2004, methodology): “Otherwise, they can make incorrect inferences about the regression coefficients (because of incorrect estimation of the variances) and inefficient or biased estimates of the regression coefficients (Diggle et al., 2002) that could lead to incorrect conclusions regarding their research questions.”
- Procedures for numerical analysis of circadian rhythms (2007, background): “…different points in time is extensively used by economists, meteorologists, engineers, public health researchers, and many other professionals whose main concern is not biological rhythms (Brockwell & Davis 2002; Chatfield 2004; Diggle et al. 2002; Percival & Walden 2000; Shumway & Stoffer 2000).”
- Likelihood-Based Inference on Haplotype Effects in Genetic Association Studies (2006, background): “Epstein and Satten (2003) also reported the estimates for these two haplotypes, which agree with our numbers.”
- A Geometric Approach to Maximum Likelihood Estimation of the Functional Principal Components From Sparse Longitudinal Data (2007, methodology): “The data are from Diggle et al. (2002) (http://www.maths.lancs.ac.uk/~diggle/ lda/Datasets/ lda.dat).”
- Covariance Estimation: The GLM and Regularization Perspectives (2011, methodology): “In the literature of longitudinal data analysis (Liang and Zeger, 1986; Diggle et al., 2002; Zimmerman and Núñez-Antón, 2010) and other application areas dealing with correlated data, in the interest of expediency, parsimony and ensuring positivedefiniteness structured correlation matrices with a fe”
- 25 years of time series forecasting (2006, background): “A great deal of research on count time series has also been done in the biostatistical area (see, for example, Diggle et al. 2002).”
- Estimation of the covariance matrix of random effects in longitudinal studies (2007, methodology): “The methodology for parametric-based longitudinal data analysis is quite mature; see, for example, Diggle, Heagerty, Liang and Zeger [5] and the references therein.”
- Simulation-Based Confidence Intervals for Functions With Complicated Derivatives (2013, methodology): “, Xn), has an asymptotic normal law with variance that can be easily estimated (Diggle et al. 2002).”
- Asymptotic optimality and efficient computation of the leave-subject-out cross-validation (2012, methodology): “We refer to the books by Green and Silverman (1994), Gu (2002) and Wood (2006) for thorough treatments of this subject. The idea of using working correlation for longitudinal data can be traced back to the generalized estimating equations (GEE) of Liang and Zeger (1986), where it is established that”
- Patient race/ethnicity and quality of patient-physician communication during medical visits. (2004, methodology): “An exchangeable correlation structure was assumed with strongly consistent estimation, which was likely to yield more accurate or valid coefficient estimates, even if the correct correlation structure was specified incorrectly.(29) There were 29 sites that had an average of only 2 physicians per sit”
- Sleep duration: how well do self-reports reflect objective measures? The CARDIA Sleep Study (2008, methodology): “The standard approach to fitting such models would be to use generalized estimating equations (GEE), most often with an exchangeable or exponential correlation structure, and then to employ a robust variance estimator to obtain standard errors and confidence intervals.(33) The analysis here requires”