Double hierarchical generalized linear models
暂无分享,去创建一个
[1] William G. Cochran,et al. The analysis of groups of experiments , 1938, The Journal of Agricultural Science.
[2] H. Chernoff. On the Distribution of the Likelihood Ratio , 1954 .
[3] G. Patil. A characterization of the exponential - type distribution , 1963 .
[4] Calyampudi R. Rao,et al. The theory of least squares when the parameters are stochastic and its application to the analysis of growth curves. , 1965, Biometrika.
[5] John A. Nelder,et al. The analysis of randomized experiments with orthogonal block structure. I. Block structure and the null analysis of variance , 1965, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.
[6] R. W. Wedderburn. Quasi-likelihood functions, generalized linear models, and the Gauss-Newton method , 1974 .
[7] C. R. Henderson,et al. Best linear unbiased estimation and prediction under a selection model. , 1975, Biometrics.
[8] D. Harville. Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems , 1977 .
[9] Ashok Saxena,et al. Development of Standard Methods of Testing and Analyzing Fatigue Crack Growth Rate Data , 1978 .
[10] N. Laird. Nonparametric Maximum Likelihood Estimation of a Mixing Distribution , 1978 .
[11] P. W. Lane,et al. Analysis of covariance and standardization as instances of prediction. , 1982, Biometrics.
[12] O. Barndorff-Nielsen. On a formula for the distribution of the maximum likelihood estimator , 1983 .
[13] P. McCullagh,et al. Generalized Linear Models , 1984 .
[14] J. Heckman,et al. A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data , 1984 .
[15] H. Goldstein. Multilevel mixed linear model analysis using iterative generalized least squares , 1986 .
[16] S. Zeger,et al. Longitudinal data analysis using generalized linear models , 1986 .
[17] B. Efron. Double Exponential Families and Their Use in Generalized Linear Regression , 1986 .
[18] D. Cox,et al. Parameter Orthogonality and Approximate Conditional Inference , 1987 .
[19] G. McLachlan. On Bootstrapping the Likelihood Ratio Test Statistic for the Number of Components in a Normal Mixture , 1987 .
[20] M. Jacobs,et al. A controlled study of progabide in partial seizures , 1987, Neurology.
[21] J. Nelder,et al. An extended quasi-likelihood function , 1987 .
[22] H. Goldstein. Multilevel Statistical Models , 2006 .
[23] M. Schumacher,et al. The impact of heterogeneity on the comparison of survival times. , 1987, Statistics in medicine.
[24] Marie Davidian,et al. A Note on Extended Quasi-Likelihood , 1988 .
[25] O. Aalen,et al. Heterogeneity in survival analysis. , 1988, Statistics in medicine.
[26] Jeremy MG Taylor,et al. Robust Statistical Modeling Using the t Distribution , 1989 .
[27] P. Thall,et al. Some covariance models for longitudinal count data with overdispersion. , 1990, Biometrics.
[28] Andrew Harvey,et al. Forecasting, Structural Time Series Models and the Kalman Filter , 1990 .
[29] G. Wahba. Spline models for observational data , 1990 .
[30] E. Seneta,et al. The Variance Gamma (V.G.) Model for Share Market Returns , 1990 .
[31] D. Bates,et al. Nonlinear mixed effects models for repeated measures data. , 1990, Biometrics.
[32] D. Duffie,et al. Simulated Moments Estimation of Markov Models of Asset Prices , 1990 .
[33] John A. Nelder,et al. Generalized linear models for the analysis of Taguchi-type experiments , 1991 .
[34] G. Robinson. That BLUP is a Good Thing: The Estimation of Random Effects , 1991 .
[35] R. Schall. Estimation in generalized linear models with random effects , 1991 .
[36] R. Payne,et al. General balance, combination of information and the analysis of covariance , 1992 .
[37] John A. Nelder,et al. Likelihood, Quasi-likelihood and Pseudolikelihood: Some Comparisons , 1992 .
[38] N. Breslow,et al. Approximate inference in generalized linear mixed models , 1993 .
[39] R. Wolfinger. Covariance structure selection in general mixed models , 1993 .
[40] B. Silverman,et al. Nonparametric Regression and Generalized Linear Models: A roughness penalty approach , 1993 .
[41] R. Wolfinger,et al. Generalized linear mixed models a pseudo-likelihood approach , 1993 .
[42] P. Diggle,et al. Semiparametric models for longitudinal data with application to CD4 cell numbers in HIV seroconverters. , 1994, Biometrics.
[43] P. Diggle,et al. Analysis of Longitudinal Data , 2003 .
[44] Adrian F. M. Smith,et al. Bayesian Analysis of Linear and Non‐Linear Population Models by Using the Gibbs Sampler , 1994 .
[45] N. Shephard,et al. Multivariate stochastic variance models , 1994 .
[46] N. Shephard,et al. Stochastic Volatility: Likelihood Inference And Comparison With Arch Models , 1996 .
[47] Noreen Goldman,et al. An assessment of estimation procedures for multilevel models with binary responses , 1995 .
[48] A. Gallant,et al. Which Moments to Match? , 1995, Econometric Theory.
[49] N. Breslow,et al. Bias correction in generalised linear mixed models with a single component of dispersion , 1995 .
[50] E. Eberlein,et al. Hyperbolic distributions in finance , 1995 .
[51] Harvey Goldstein,et al. Improved Approximations for Multilevel Models with Binary Responses , 1996 .
[52] E. Vonesh,et al. A note on the use of Laplace's approximation for nonlinear mixed-effects models , 1996 .
[53] J. F. Bjørnstad. On the Generalization of the Likelihood Function and the Likelihood Principle , 1996 .
[54] N. Shephard. Statistical aspects of ARCH and stochastic volatility , 1996 .
[55] G. McLachlan,et al. The EM algorithm and extensions , 1996 .
[56] N. Breslow,et al. Bias Correction in Generalized Linear Mixed Models with Multiple Components of Dispersion , 1996 .
[57] M. Pitt,et al. Likelihood analysis of non-Gaussian measurement time series , 1997 .
[58] Jianqing Fan,et al. Smoothing spline models for the analysis of nested and crossed samples of curves. Commentaries. Authors' reply , 1998 .
[59] J. Rice,et al. Smoothing spline models for the analysis of nested and crossed samples of curves , 1998 .
[60] Siem Jan Koopman,et al. Time Series Analysis of Non-Gaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives , 1999 .
[61] Marco Alfò,et al. Regression models for binary longitudinal responses , 1998, Stat. Comput..
[62] Siem Jan Koopman,et al. Estimation of stochastic volatility models via Monte Carlo maximum likelihood , 1998 .
[63] John A. Nelder,et al. Generalized linear models for the analysis of quality‐improvement experiments , 1998 .
[64] B. Everitt,et al. Analysis of longitudinal data , 1998, British Journal of Psychiatry.
[65] Steven G. Gilmour,et al. The analysis of designed experiments and longitudinal data by using smoothing splines - Discussion , 1999 .
[66] D. Firth,et al. Estimating Intraclass Correlation for Binary Data , 1999, Biometrics.
[67] Kani Chen,et al. Strong consistency of maximum quasi-likelihood estimators in generalized linear models with fixed and adaptive designs , 1999 .
[68] Gordon K. Smyth,et al. Adjusted likelihood methods for modelling dispersion in generalized linear models , 1999 .
[69] Renjun Ma. An orthodox blup approach to generalized linear mixed models , 1999 .
[70] J. Besag,et al. Bayesian analysis of agricultural field experiments , 1999 .
[71] M. Pourahmadi. Maximum likelihood estimation of generalised linear models for multivariate normal covariance matrix , 2000 .
[72] John A. Nelder,et al. Two ways of modelling overdispersion in non‐normal data , 2000 .
[73] John A. Nelder,et al. The relationship between double‐exponential families and extended quasi‐likelihood families, with application to modelling Geissler's human sex ratio data , 2000 .
[74] M E Robinson,et al. Bayesian Methods for a Growth-Curve Degradation Model with Repeated Measures , 2000, Lifetime data analysis.
[75] Sj Senn. Consensus and controversy in pharmaceutical statistics. (With discussion) , 2000 .
[76] Youngjo Lee,et al. Hierarchical likelihood approach for frailty models , 2001 .
[77] J. Nelder,et al. Hierarchical generalised linear models: A synthesis of generalised linear models, random-effect models and structured dispersions , 2001 .
[78] Ana Ivelisse Avilés,et al. Linear Mixed Models for Longitudinal Data , 2001, Technometrics.
[79] M. Kenward,et al. Parametric modelling of growth curve data: An overview , 2001 .
[80] X Xue. Analysis of childhood brain tumour data in New York City using frailty models. , 2001, Statistics in medicine.
[81] Youngjo Lee. Can we recover information from concordant pairs in binary matched pairs? , 2001 .
[82] Anukool Lakhina,et al. BRITE: Universal Topology Generation from a User''s Perspective , 2001 .
[83] Youngjo Lee,et al. Modelling and analysing correlated non-normal data , 2001 .
[84] A. Kuk,et al. Robust estimation in generalized linear mixed models , 2002 .
[85] Harvey Goldstein,et al. Likelihood methods for fitting multilevel models with complex level-1 variation , 2002 .
[86] Eric R. Ziegel,et al. Generalized Linear Models , 2002, Technometrics.
[87] Youngjo Lee,et al. Hierarchical-Likelihood Approach for Mixed Linear Models with Censored Data , 2002, Lifetime data analysis.
[88] James R. Kenyon,et al. Analysis of Multivariate Survival Data , 2002, Technometrics.
[89] Bradley P. Carlin,et al. Bayesian measures of model complexity and fit , 2002 .
[90] Y. Pawitan. In all likelihood : statistical modelling and inference using likelihood , 2002 .
[91] Dibyen Majumdar,et al. Conditional Second-Order Generalized Estimating Equations for Generalized Linear and Nonlinear Mixed-Effects Models , 2002 .
[92] Taesung Park,et al. Joint Modelling of Repeated Measures and Survival Time Data , 2003 .
[93] Gilbert MacKenzie,et al. On modelling mean‐covariance structures in longitudinal studies , 2003 .
[94] Daniel Krewski,et al. Random effects Cox models: A Poisson modelling approach , 2003 .
[95] M. Crowder,et al. Covariates and Random Effects in a Gamma Process Model with Application to Degradation and Failure , 2004, Lifetime data analysis.
[96] Estimating intraclass correlation for binary data using extended quasi-likelihood , 2004 .
[97] Youngjo Lee,et al. Comparison of hierarchical and marginal likelihood estimators for binary outcomes , 2004, Comput. Stat. Data Anal..
[98] D. Cox,et al. A note on pseudolikelihood constructed from marginal densities , 2004 .
[99] R. Rigby,et al. Generalized additive models for location, scale and shape , 2005 .
[100] C. Varin,et al. A note on composite likelihood inference and model selection , 2005 .
[101] Ruggero Bellio,et al. A pairwise likelihood approach to generalized linear models with crossed random effects , 2005 .
[102] G. Molenberghs,et al. Models for Discrete Longitudinal Data , 2005 .
[103] Youngjo Lee,et al. Robust ascertainment‐adjusted parameter estimation , 2005, Genetic epidemiology.
[104] Maengseok Noh,et al. HGLM modelling of dropout process using a frailty model , 2005, Comput. Stat..
[105] Sudhir Paul,et al. Bias-corrected maximum likelihood estimator of the negative binomial dispersion parameter. , 2005, Biometrics.
[106] P. J. Lindsey,et al. Multivariate distributions with correlation matrices for nonlinear repeated measurements , 2006, Comput. Stat. Data Anal..
[107] Robust estimation in mixed linear models with non‐monotone missingness , 2006, Statistics in medicine.
[108] John A. Nelder,et al. Fitting via alternative random-effect models , 2006, Stat. Comput..
[109] J. Nelder,et al. Double hierarchical generalized linear models (with discussion) , 2006 .
[110] Youngjo Lee,et al. Dispersion frailty models and HGLMs , 2006, Statistics in medicine.
[111] Y Pawitan,et al. Multicomponent variance estimation for binary traits in family‐based studies , 2006, Genetic epidemiology.
[112] J. F. Bjørnstad. ----On the Generalization of the Likelihood Function and the Likelihood Principle , 2008 .