Book Reviews

References

• Jones , R. M. 1993 . Longitudinal Data with Serial Correlation: A State-Space Approach , London : Chapman and Hall .
   Google Scholar
• Latour , D. , Latour , K. and Wolfinger , R. 1994 . Getting Started with Proc Mixed , Cary , NC : SAS Institute Inc. .
   Google Scholar
• Liang , K.-Y. and Zeger , S. L. 1986 . “Longitudinal Data Analysis Using Generalized Linear Models,” . Biometrika , 73 : 13 – 22 .
   Web of Science ®Google Scholar
• Lindsey , J. K. 1993 . Models for Repeated Measurements , New York : Oxford University Press .
   Google Scholar
• Longford , N. T. 1993 . Random Coefficient Models , New York : Oxford University Press .
   Google Scholar
• Neuhaus , J. M. , Kalbfleisch , J. D. and Hauck , W. W. 1991 . “A Comparison of Cluster-Specific and Population-Averaged Approaches for Analyzing Correlated Binary Data,” . International Statistical Review , 59 : 25 – 36 .
   Web of Science ®Google Scholar
• Neuhaus , J. M. 1992 . “Statistical Methods for Longitudinal and Clustered Designs With Binary Responses,” . Statistical Methods in Medical Research , 1 : 249 – 273 .
   PubMedGoogle Scholar
• Neuhaus , J. M. and Segal , M. R. 1993 . “Design Effects for Binary Regression Models Fitted to Dependent Data,” . Statistics in Medicine , 12 : 1259 – 1268 .
   PubMed Web of Science ®Google Scholar
• Ware , J. H. , Dockery , D. Louis , T. A. 1990 . “Longitudinal and Cross-Sectional Estimates of Pulmonary Function Decline in Never-Smoking Adults,” . American Journal of Epidemiology , 32 : 685 – 700 .
   Google Scholar
• Zeger , S. L. , Liang , K.-Y. and Albert , P. S. 1988 . “Models for Longitudinal Data: A Generalized Estimating Equation Approach,” . Biometrics , 44 : 1049 – 1060 .
   PubMed Web of Science ®Google Scholar
• Zeger , S. L. and Liang , K.-Y. 1992 . “Analysis of Longitudinal Data,” . Statistics in Medicine , 11 : 1825 – 1839 .
   PubMed Web of Science ®Google Scholar
• Bahadur , R. R. 1961 . “A Representation of the Joint Distribution of Responses to n Dichotomous Items,” . In Studies in Item Analysis and Prediction, Stanford Mathematical Studies in the Social Sciences VI , Edited by: Solomon , H. 158 – 168 . Stanford , CA : Stanford University Press .
   Google Scholar
• Diggle , P. J. , Liang , K. Y. and Zeger , S. L. 1994 . Analysis of Longitudinal Data , Oxford , , UK : Oxford University Press .
   Google Scholar
• Rasch , G. “On General Laws and the Meaning of Measurement in Psychology,” . Proceedings 4th Berkeley Symposium Mathematics Statistics Probability . Edited by: Neyman , J. vol. 4 , pp. 321 – 333 . Berkeley , CA : University of California Press .
   Google Scholar
• Rosner , B. 1984 . “Multivariate Methods in Ophthalmology With Application to Other Paired-Data Situations,” . Biometrics , 40 : 1025 – 1035 .
   PubMed Web of Science ®Google Scholar
• Cox , D. R. and Oakes , D. 1984 . Analysis of Survival Data , London : Chapman and Hall .
   Google Scholar
• Kalbfleisch , J. D. and Prentice , R. L. 1980 . The Statistical Analysis of Failure Time Data , New York : John Wiley .
   Google Scholar
• Lawless , J. F. 1980 . Statistical Models and Methods for Lifetime Data , New York : John Wiley .
   Google Scholar
• Miller , R. 1980 . Survival Analysis , New York : John Wiley .
   Google Scholar
• Odell , P. M. , Anderson , K. M. and D'Agostino , R. B. 1992 . “Maximum Likelihood Estimation for Interval-Censored Data Using a Weibull-Based Accelerated Failure Time Model,” . Biometrics , 48 : 951 – 959 .
   PubMed Web of Science ®Google Scholar
• Buja , A. , Asimov , D. , Hurley , C. and McDonald , J. A. 1988 . “Elements of a Viewing Pipeline for Data Analysis,” . In Dynamic Graphics for Statistics , Edited by: Cleveland , W. S. and McGill , M. E. 277 – 308 . Monterey , CA : Wadsworth .
   Google Scholar
• Cleveland , W. S. 1993 . Visualizing Data , Summit , NJ : Hobart Press .
   Google Scholar
• Cleveland , W. S. and McGill , M. E. 1988 . Dynamic Graphics for Statistics , Monterey , CA : Wadsworth .
   Google Scholar
• Tierney , L. 1991 . LispStat: An Object-Orientated Environment for Statistical Computing and Dynamic Graphics , New York : John Wiley .
   Google Scholar
• Mandel , J. 1991 . Evaluation and Control of Measurements , New York : Marcel Dekker .
   Google Scholar
• Marasinghe , M. G. 1994 . Review of “Evaluation and Control of Measurements,” . Journal of the American Statistical Association , 89 : 720
   Google Scholar
• Gabriel , K. R. and Bradu , D. 1978 . “The Biplot as a Diagnostic Tool for Models of Two-Way Tables,” . Technometrics , 20 : 47 – 68 .
   Web of Science ®Google Scholar
• Bickel , P. J. , Klassen , C. A. , Ritov , Y. and Wellner , J. A. 1993 . Efficient and Adaptive Estimation for Semiparametric Models , Baltimore : Johns Hopkins University Press .
   Google Scholar
• Hampel , F. R. , Ronchetti , E. M. , Rousseeuw , P. J. and Stahel , W. A. 1986 . Robust Statistics: The Approach Based on Influence Functions , New York : John Wiley .
   Google Scholar
• Huber , P. J. 1981 . Robust Statistics , New York : John Wiley .
   Google Scholar
• Pfanzagl , J. 1994 . Parametric Statistical Theory , Berlin : Walter de Gruyter .
   Google Scholar
• Barndorff-Nielsen , O. E. 1983 . “On a Formula for the Distribution of the Maximum Likelihood Estimator,” . Biometrika , 70 : 343 – 365 .
   Web of Science ®Google Scholar
• Barndorff-Nielsen , O. E. and Cox , D. R. 1979 . “Edgeworth and Saddlepoint Approximations With Statistical Applications” . Journal of the Royal Statistical Society , 41 : 279 – 312 . (with discussion), Ser. B
   Google Scholar
• Bickel , P. J. and Ghosh , J. K. 1990 . “A Decomposition for the Likelihood Ratio Statistic and the Bartlett Correction–A Bayesian Argument,” . The Annals of Statistics , 18 : 1070 – 1090 .
   Web of Science ®Google Scholar
• Cox , D. R. and Reid , N. 1987 . “Parameter Orthogonality and Approximate Conditional Inference” . Journal of the Royal Statistical Society , 49 : 1 – 39 . (with discussion), Ser. B
   Google Scholar
• Efron , B. 1975 . “Defining the Curvature of a Statistical Problem (With Applications to Second-Order Sufficiency)” . The Annals of Statistics , 3 : 1189 – 1242 . (with discussion)
   Web of Science ®Google Scholar
• Efron , B. and Hinkley , D. V. 1978 . “Assessing the Accuracy of the Maximum Likelihood Estimator: Observed Versus Expected Fisher Information” . Biometrika , 65 : 457 – 487 . (with discussion)
   Web of Science ®Google Scholar
• Fisher , R. A. 1934 . “Two New Properties of Mathematical Likelihood,” . Proceedings of the Royal Society , 144 : 285 – 307 . Ser. A
   Google Scholar
• Lawley , D. N. 1956 . “A General Method for Approximating to the Distribution of the Likelihood Ratio Criterion,” . Biometrika , 43 : 295 – 303 .
   Web of Science ®Google Scholar
• McCullagh , P. 1987 . Tensor Methods in Statistics , London : Chapman and Hall .
   Google Scholar
• Skovgaard , I. M. 1990 . “On the Density of Minimum Contrast Estimators,” . The Annals of Statistics , 18 : 779 – 789 .
   Web of Science ®Google Scholar
• Bechhofer , R. E. 1954 . “A Single-Sample Multiple Decision Procedure for Ranking Means of Normal Populations With Unknown Variances,” . The Annals of Mathematical Statistics , 25 : 16 – 39 .
   Google Scholar
• Bechhofer , R. E. and Sobel , M. 1954 . “A Single-Sample Multiple-Decision Procedure for Ranking Variances of Normal Populations,” . The Annals of Mathematical Statistics , 25 : 273 – 289 .
   Google Scholar
• Gibbons , J. D. , Olkin , I. and Sobel , M. 1977 . Selecting and Ordering Populations: A New Statistical Methodology , New York : John Wiley .
   Google Scholar
• Gupta , S. S. 1956 . “On a Decision Rule for a Problem in Ranking Means,” , Ph.D. dissertation Chapel Hill : University of North Carolina .
   Google Scholar
• Gupta , S. S. and Panchapakesan , S. 1979 . Multiple Decision Procedures , New York : John Wiley .
   Google Scholar
• Feller , W. 1968 . An Introduction to Probability Theory and Its Applications , Vol. I , New York : John Wiley .
   Google Scholar
• Goodman , L. A. 1974a . “The Analysis of Systems of Qualitative Variables When Some of the Variables are Unobservable. I. A Modified Latent Structure Approach,” . American Journal of Sociology , 79 : 1179 – 1259 .
   Web of Science ®Google Scholar
• Goodman , L. A. 1974b . “Exploratory Latent Structure Analysis Using Both Identifiable and Unidentifiable Models,” . Biometrika , 61 : 215 – 231 .
   Web of Science ®Google Scholar
• Haberman , S. J. 1977a . “Product Models for Frequency Tables Involving Indirect Observation,” . The Annals of Statistics , 5 : 1124 – 1147 .
   Web of Science ®Google Scholar
• Haberman , S. J. 1977b . “Maximum Likelihood Estimates in Exponential Response Models,” . The Annals of Statistics , 5 : 815 – 841 .
   Web of Science ®Google Scholar
• Haberman , S. J. 1979 . Analysis of Qualitative Data. II. New Developments , New York : Academic Press .
   Google Scholar
• Haberman , S. J. 1988 . “A Stabilized Newton-Raphson Algorithm for Log-Linear Models for Frequency Tables Derived by Indirect Observation,” . Sociological Methodology , 18 : 193 – 211 .
   Google Scholar
• Karlin , S. and Studden , W. 1966 . Tchebycheff Systems, With Applications to Analysis and Statistics , New York : Wiley Interscience .
   Google Scholar
• Kiefer , J. and Wolfowitz , J. 1956 . “Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Nuisance Parameters,” . The Annals of Mathematical Statistics , 27 : 887 – 906 .
   Google Scholar
• Neyman , J. and Scott , E. L. 1948 . “Consistent Estimates Based on Partially Consistent Observations,” . Econometrica , 16 : 1 – 32 .
   Web of Science ®Google Scholar
• Wu , C. F. J. 1983 . “On the Convergence Properties of the EM Algorithm,” . The Annals of Statistics , 11 : 95 – 103 .
   Web of Science ®Google Scholar
• Daley , D. and Vere-Jones , D. 1988 . An Introduction to the Theory of Point Processes , New York : Springer-Verlag .
   Google Scholar
• Cox , D. R. and Isham , V. 1980 . Point Processes , London : Chapman and Hall .
   Google Scholar
• Karr , A. F. 1986 . Point Processes and Their Statistical Inference , New York : Marcel Dekker .
   Google Scholar
• Leadbetter , M. R. , Lindgren , G. and Rootzén , H. 1983 . Extremes and Related Properties of Random Sequences and Processes , New York : Springer-Verlag .
   Google Scholar
• Reiss , R. D. 1989 . Approximate Distributions of Order Statistics , New York : Springer-Verlag .
   Google Scholar
• Resnick , S. I. 1987 . Extreme Values, Regular Variation, and Point Processes , New York : Springer-Verlag .
   Google Scholar
• Diaconis , P. 1988 . “Bayesian Numerical Analysis,” . In Statistical Decision Theory and Related Topics IV , Edited by: Gupta , S. S. and Berger , J. Vol. I , 163 – 175 . New York : John Wiley .
   Google Scholar
• O'Hagan , A. 1992 . “Some Bayes Numerical Analysis,” . In Bayesian Statistics , Edited by: Bernardo , J. Vol. IV , Amsterdam : North-Holland .
   Google Scholar
• Davis , M. H. A. 1984 . “Piecewise-Deterministic Markov Processes: A General Class of Non-Diffusion Stochastic Models” . Journal of the Royal Statistical Society , 46 : 353 – 388 . (with discussion), Ser. B
   Google Scholar
• Embrechts , P. and Schmidli , H. 1994 . “Ruin Estimation for a General Insurance Risk Model,” . Advances in Applied Probability , 26 : 404 – 422 .
   Web of Science ®Google Scholar
• Ethier , S. N. and Kurtz , T. G. 1986 . Markov Processes: Characterization and Convergence , New York : John Wiley .
   Google Scholar