On composite marginal likelihoods

Composite marginal likelihoods are pseudolikelihoods constructed by compounding marginal densities. In several applications, they are convenient surrogates for the ordinary likelihood when it is too cumbersome or impractical to compute. This paper presents an overview of the topic with emphasis on applications.

[1]  Satterthwaite Fe.  An approximate distribution of estimates of variance components. , 1946 .

[2]  R. A. Leibler,et al.  On Information and Sufficiency , 1951 .

[3]  V. P. Godambe.  An Optimum Property of Regular Maximum Likelihood Estimation , 1960 .

[4]  R. Plackett.  A Class of Bivariate Distributions , 1965 .

[5]  H. Akaike,et al.  Information Theory and an Extension of the Maximum Likelihood Principle , 1973 .

[6]  R. W. Wedderburn.  Quasi-likelihood functions, generalized linear models, and the Gauss-Newton method , 1974 .

[7]  J. Besag.  Spatial Interaction and the Statistical Analysis of Lattice Systems , 1974 .

[8]  J. Besag.  Efficiency of pseudolikelihood estimation for simple Gaussian fields , 1977 .

[9]  Peter J. Diggle,et al.  Binary Mosaics and the Spatial Pattern of Heather , 1981 .

[10]  J. Kent.  Robust properties of likelihood ratio tests , 1982 .

[11]  Adelchi Azzalini,et al.  Maximum likelihood estimation of order m for stationary stochastic processes , 1983 .

[12]  J A Anderson,et al.  The grouped continuous model for multivariate ordered categorical variables and covariate adjustment. , 1985, Biometrics.

[13]  P. Hougaard.  A class of multivanate failure time distributions , 1986 .

[14]  S. Zeger,et al.  Longitudinal data analysis using generalized linear models , 1986 .

[15]  Brian D. Ripley,et al.  Problems with likelihood estimation of covariance functions of spatial Gaussian processes , 1987 .

[16]  A. Raftery,et al.  Space-time modeling with long-memory dependence: assessing Ireland's wind-power resource. Technical report , 1987 .

[17]  Wai-Yin Poon,et al.  Maximum likelihood estimation of multivariate polyserial and polychoric correlation coefficients , 1988 .

[18]  M. West,et al.  Bayesian forecasting and dynamic models , 1989 .

[19]  L. Zhao,et al.  Correlated binary regression using a quadratic exponential model , 1990 .

[20]  Noel A Cressie,et al.  Statistics for Spatial Data. , 1992 .

[21]  Mike Rees,et al.  5. Statistics for Spatial Data , 1993 .

[22]  N. Breslow,et al.  Approximate inference in generalized linear mixed models , 1993 .

[23]  P. Diggle,et al.  Modelling multivariate binary data with alternating logistic regressions , 1993 .

[24]  Noel A. C. Cressie,et al.  Statistics for Spatial Data: Cressie/Statistics , 1993 .

[25]  Peter McCullagh,et al.  REML Estimation with Exact Covariance in the Logistic Mixed Model , 1993 .

[26]  H. Omre,et al.  Topics in spatial statistics. Discussion and comments , 1994 .

[27]  T. Rydén.  Consistent and Asymptotically Normal Parameter Estimates for Hidden Markov Models , 1994 .

[28]  J. C. van Houwelingen,et al.  Logistic Regression for Correlated Binary Data , 1994 .

[29]  Noreen Goldman,et al.  An assessment of estimation procedures for multilevel models with binary responses , 1995 .

[30]  Y. Vardi,et al.  Network Tomography: Estimating Source-Destination Traffic Intensities from Link Data , 1996 .

[31]  Bing-Yi Jing,et al.  On Sample Reuse Methods for Dependent Data , 1996 .

[32]  C. Heyde,et al.  Quasi-likelihood and its application , 1997 .

[33]  Michael A. West,et al.  Bayesian Forecasting and Dynamic Models (2nd edn) , 1997, J. Oper. Res. Soc..

[34]  Stuart R. Lipsitz,et al.  Marginal models for the analysis of longitudinal measurements with nonignorable non-monotone missing data , 1998 .

[35]  R. Nelsen.  An Introduction to Copulas , 1998 .

[36]  P. Diggle,et al.  Model-based geostatistics (with discussion). , 1998 .

[37]  S. Lele,et al.  A Composite Likelihood Approach to Binary Spatial Data , 1998 .

[38]  David J. Nott,et al.  Pairwise likelihood methods for inference in image models , 1999 .

[39]  Subhash R. Lele,et al.  A composite likelihood approach to semivariogram estimation , 1999 .

[40]  G. Molenberghs,et al.  Pseudolikelihood Modeling of Multivariate Outcomes in Developmental Toxicology , 1999 .

[41]  Gerda Claeskens,et al.  Bootstrapping Pseudolikelihood Models for Clustered Binary Data , 1999 .

[42]  K. Liang,et al.  Regression analysis under non‐standard situations: a pairwise pseudolikelihood approach , 2000 .

[43]  Patrick J. Heagerty,et al.  Window Subsampling of Estimating Functions with Application to Regression Models , 2000 .

[44]  David J. Nott,et al.  A pairwise likelihood approach to analyzing correlated binary data , 2000 .

[45]  D. Oakes,et al.  Regression in a bivariate copula model , 2000 .

[46]  D. Bates,et al.  Mixed-Effects Models in S and S-PLUS , 2001 .

[47]  C. A. Glasbey,et al.  Non‐linear autoregressive time series with multivariate Gaussian mixtures as marginal distributions , 2001 .

[48]  Erik T. Parner,et al.  A Composite Likelihood Approach to Multivariate Survival Data , 2001 .

[49]  R. Hudson.  Two-locus sampling distributions and their application. , 2001, Genetics.

[50]  K. Jöreskog,et al.  Factor Analysis of Ordinal Variables: A Comparison of Three Approaches , 2001, Multivariate behavioral research.

[51]  G. Molenberghs,et al.  Multivariate Clustered Data Analysis in Developmental Toxicity Studies , 2001 .

[52]  Geert Molenberghs,et al.  Two latent variable risk assessment approaches for mixed continuous and discrete outcomes from developmental toxicity data , 2001 .

[53]  P. Donnelly,et al.  Approximate likelihood methods for estimating local recombination rates , 2002 .

[54]  Chris A. Glasbey,et al.  A Spectral Estimator of Arma Parameters from Thresholded Data , 2002, Stat. Comput..

[55]  Hao Zhang.  On Estimation and Prediction for Spatial Generalized Linear Mixed Models , 2002, Biometrics.

[56]  Subhash R. Lele,et al.  A composite likelihood approach to (co)variance components estimation , 2002 .

[57]  Geert Molenberghs,et al.  Validation of Surrogate Endpoints in Multiple Randomized Clinical Trials with Discrete Outcomes , 2002 .

[58]  R. Waagepetersen,et al.  Bayesian Prediction of Spatial Count Data Using Generalized Linear Mixed Models , 2002, Biometrics.

[59]  P. Fearnhead,et al.  A coalescent-based method for detecting and estimating recombination from gene sequences. , 2002, Genetics.

[60]  Bin Yu,et al.  Maximum pseudo likelihood estimation in network tomography , 2003, IEEE Trans. Signal Process..

[61]  Paul Fearnhead,et al.  Consistency of estimators of the population-scaled recombination rate. , 2003, Theoretical population biology.

[62]  R. Henderson,et al.  A serially correlated gamma frailty model for longitudinal count data , 2003 .

[63]  Geert Molenberghs,et al.  A pairwise likelihood approach to estimation in multilevel probit models , 2004, Comput. Stat. Data Anal..

[64]  Zhiyi Chi,et al.  Approximating likelihoods for large spatial data sets , 2004 .

[65]  E. Andersen.  Composite likelihood and two-stage estimation in family studies. , 2004, Biostatistics.

[66]  Permutation invariance of alternating logistic regression for multivariate binary data , 2004 .

[67]  G. Molenberghs,et al.  Modelling associations between time‐to‐event responses in pilot cancer clinical trials using a Plackett–Dale model , 2004, Statistics in medicine.

[68]  G. Molenberghs,et al.  Pseudo‐likelihood estimation for a marginal multivariate survival model , 2004, Statistics in medicine.

[69]  John J. Hanfelt,et al.  Composite conditional likelihood for sparse clustered data , 2004 .

[70]  D. Cox,et al.  A note on pseudolikelihood constructed from marginal densities , 2004 .

[71]  Øivind Skare,et al.  Pairwise likelihood inference in spatial generalized linear mixed models , 2005, Comput. Stat. Data Anal..

[72]  A. R. de Leon.  Pairwise likelihood approach to grouped continuous model and its extension , 2005 .

[73]  H. Joe,et al.  Composite likelihood estimation in multivariate data analysis , 2005 .

[74]  C. Varin,et al.  A note on composite likelihood inference and model selection , 2005 .

[75]  Ruggero Bellio,et al.  A pairwise likelihood approach to generalized linear models with crossed random effects , 2005 .

[76]  G. Molenberghs,et al.  Models for Discrete Longitudinal Data , 2005 .

[77]  P. Vandekerkhove.  Consistent and asymptotically normal parameter estimates for hidden Markov mixtures of Markov models , 2005 .

[78]  Geert Verbeke,et al.  High dimensional multivariate mixed models for binary questionnaire data , 2006 .

[79]  Subhash R Lele,et al.  Sampling variability and estimates of density dependence: a composite-likelihood approach. , 2006, Ecology.

[80]  Joseph G Ibrahim,et al.  Pseudo‐likelihood methods for longitudinal binary data with non‐ignorable missing responses and covariates , 2006, Statistics in medicine.

[81]  Geert Verbeke,et al.  Pairwise Fitting of Mixed Models for the Joint Modeling of Multivariate Longitudinal Profiles , 2006, Biometrics.

[82]  Yongtao Guan,et al.  A Composite Likelihood Approach in Fitting Spatial Point Process Models , 2006 .

[83]  Cristiano Varin,et al.  Pairwise likelihood inference for ordinal categorical time series , 2006, Comput. Stat. Data Anal..

[84]  D. Louis,et al.  A pseudolikelihood approach for simultaneous analysis of array comparative genomic hybridizations. , 2005, Biostatistics.

[85]  Jorge Mateu,et al.  Covariance functions that are stationary or nonstationary in space and stationary in time , 2007 .

[86]  Yohay Carmel,et al.  Analyzing Spatially Distributed Binary Data Using Independent‐Block Estimating Equations , 2007, Biometrics.

[87]  Alexander R. de Leon,et al.  General mixed‐data model: Extension of general location and grouped continuous models , 2007 .

[88]  Richard L. Smith,et al.  Asymptotic properties of computationally efficient alternative estimators for a class of multivariate normal models , 2007 .

[89]  P. X. Song,et al.  Correlated data analysis : modeling, analytics, and applications , 2007 .

[90]  G Molenberghs,et al.  Random-effects models for multivariate repeated measures , 2007, Statistical methods in medical research.

[91]  Fitting negative spatial covariances to geothermal field temperatures in Nea Kessani (Greece) , 2007 .

[92]  Yongtao Guan.  A Composite Likelihood Cross-validation Approach in Selecting Bandwidth for the Estimation of the Pair Correlation Function. , 2007 .

[93]  A. Kuk.  A Hybrid Pairwise Likelihood Method , 2007 .

[94]  Richard E. Chandler,et al.  Inference for clustered data using the independence loglikelihood , 2007 .

[95]  Nils Lid Hjort,et al.  ML, PL, QL in Markov Chain Models , 2008 .

[96]  Cristiano Varin,et al.  Pairwise Likelihood Inference for General State Space Models , 2008 .

[97]  David Ruppert,et al.  Aberrant Crypt Foci and Semiparametric Modeling of Correlated Binary Data , 2008, Biometrics.

[98]  D. Stoyan,et al.  Stochastic Geometry and Its Applications , 1989 .

[99]  Michael Parzen.  Pseudo-likelihood Methods for the Analysis of Longitudinal Binary Data Subject to Nonignorable Non-monotone Missingness , 2021, Journal of Data Science.