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Breakthroughs in Statistics
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Editor(s):
Samuel Kotz
,
Norman L. Johnson
Publication date
(Print):
1992
Publisher:
Springer New York
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Annual Reviews Biomedical Breakthroughs
Author and book information
Book
ISBN (Print):
978-0-387-94039-7
ISBN (Electronic):
978-1-4612-4380-9
Publication date (Print):
1992
DOI:
10.1007/978-1-4612-4380-9
SO-VID:
79e64729-2653-4cb8-b2a0-ef144d2ba65f
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Book chapters
pp. 1
Introduction
pp. 1
Models for Network Graphs
pp. 1
Sampling and Estimation in Network Graphs
pp. 1
Introduction
pp. 1
Mapping Networks
pp. 1
Modeling and Prediction for Processes on Network Graphs
pp. 1
Probability Models
pp. 1
Preliminaries
pp. 1
Principles of Bootstrap Methodology
pp. 1
Network Topology Inference
pp. 1
Graphical Models
pp. 1
Analysis of Network Flow Data
pp. 1
Descriptive Analysis of Network Graph Characteristics
pp. 1
Functional data structures
pp. 1
Introduction
pp. 1
Introduction and Examples
pp. 1
Introduction and Overview
pp. 11
On the Criterion that a Given System of Deviations from the Probable in the Case of a Correlated System of Variables is Such that it Can be Reasonably Supposed to have Arisen from Random Sampling
pp. 3
Dilemmas and Craftsmanship
pp. 3
The Open Problem
pp. 8
The Sequential Probability Ratio Test
pp. 11
Rao’s Inequalities and Improvements
pp. 13
Simple Univariate Density Estimation
pp. 21
Defining the Model and Parameter
pp. 21
Hilbert space model for functional data
pp. 21
Causal Inference in Randomized Experiments
pp. 345
Sequential Design of Experiments
pp. 34
Brownian Approximations and Truncated Tests
pp. 37
Functional principal components
pp. 37
Orthogonal Arrays and Galois Fields
pp. 37
Introduction to the DLM: The First-Order Polynomial Model
pp. 39
Principles of Edgeworth Expansion
pp. 40
Smoother Univariate Density Estimation
pp. 43
Super Learning
pp. 45
Canonical correlation analysis
pp. 61
Orthogonal Arrays and Error-Correcting Codes
pp. 65
Two sample inference for the mean and covariance functions
pp. 65
Two Simple Models for Observational Studies
pp. 66
Statistical Methods for Research Workers
pp. 67
Introduction to TMLE
pp. 70
Tests with Curved Stopping Boundaries
pp. 75
Introduction to the DLM: The Dynamic Regression Model
pp. 79
Detection of changes in the mean function
pp. 82
Sufficient Statistics
pp. 82
The Arrangement of Field Experiments
pp. 83
An Edgeworth View of the Bootstrap
pp. 83
Understanding TMLE
pp. 87
Construction of Orthogonal Arrays from Codes
pp. 95
Competing Theories Structure Design
pp. 96
Multivariate Density Estimation
pp. 101
Why TMLE?
pp. 105
Portmanteau test of independence
pp. 105
Examples of Repeated Significance Tests
pp. 105
The Dynamic Linear Model
pp. 113
Opportunities, Devices, and Instruments
pp. 113
Orthogonal Arrays and Difference Schemes
pp. 121
Bounded Continuous Outcomes
pp. 127
Functional linear models
pp. 133
Direct Effects and Effect Among the Treated
pp. 134
Nonparametric Regression
pp. 141
Allocation of Treatments
pp. 143
Univariate Time Series DLM Theory
pp. 144
Decision Theory
pp. 145
Marginal Structural Models
pp. 145
Orthogonal Arrays and Hadamard Matrices
pp. 147
Test for lack of effect in the functional linear model
pp. 147
Transparency
pp. 153
A Matched Observational Study
pp. 155
Interval Estimation of Prescribed Accuracy
pp. 155
Bootstrap Curve Estimation
pp. 161
Positivity
pp. 162
Relations Between Two Sets of Variates
pp. 163
Basic Tools of Multivariate Matching
pp. 165
Random Walk and Renewal Theory
pp. 167
Orthogonal Arrays and Latin Squares
pp. 169
Two sample inference for regression kernels
pp. 173
Model Specification and Design
pp. 187
Robust Analysis of RCTs Using Generalized Linear Models
pp. 187
Various Practical Issues in Matching
pp. 188
Nonlinear Renewal Theory
pp. 191
Tests for error correlation in the functional linear model
pp. 196
Individual Comparisons by Ranking Methods
pp. 197
Fine Balance
pp. 199
Mixed Orthogonal Arrays
pp. 201
Polynomial Trend Models
pp. 201
Targeted ANCOVA Estimator in RCTs
pp. 207
Matching Without Groups
pp. 213
Corrected Brownian Approximations
pp. 214
Hypothesis Testing
pp. 215
Smoothing Ordered Categorical Data
pp. 219
Independent Case-Control Studies
pp. 223
Further Constructions and Related Structures
pp. 223
Risk-Set Matching
pp. 225
A test of significance in functional quadratic regression
pp. 229
Miscellaneous Boundary Crossing Problems
pp. 229
Why Match? Matched Case-Control Studies
pp. 229
Seasonal Models
pp. 235
Information and the Accuracy Attainable in the Estimation of Statistical Parameters
pp. 235
Functional autoregressive model
pp. 237
Matching in R
pp. 237
Details of Mathematical Rigour
pp. 239
Nested Case-Control Risk Score Prediction
pp. 247
Statistical Application of Orthogonal Arrays
pp. 249
Super Learning for Right-Censored Data
pp. 252
Further Applications of Smoothing
pp. 253
Change point detection in the functional autoregressive process
pp. 257
The Power of a Sensitivity Analysis and Its Limit
pp. 259
RCTs with Time-to-Event Outcomes
pp. 270
On the Experimental Attainment of Optimum Conditions
pp. 271
RCTs with Time-to-Event Outcomes and Effect Modification Parameters
pp. 273
Regression, Transfer Function and Noise Models
pp. 275
Heterogeneity and Causality
pp. 277
Determining the order of the functional autoregressive model
pp. 287
Uncommon but Dramatic Responses to Treatment
pp. 289
Functional time series
pp. 296
Estimation
pp. 299
Anticipated Patterns of Response
pp. 301
C-TMLE of an Additive Point Treatment Effect
pp. 315
After Matching, Before Analysis
pp. 317
Tables of Orthogonal Arrays
pp. 319
Illustrations and Extensions of Standard DLMS
pp. 323
C-TMLE for Time-to-Event Outcomes
pp. 327
Planning the Analysis
pp. 343
Propensity-Score-Based Estimators and C-TMLE
pp. 343
Spatially distributed functional data
pp. 344
Equivariance
pp. 367
Targeted Methods for Biomarker Discovery
pp. 375
Consistency of the simple mean and the empirical functional principal components for spatially distributed curves
pp. 379
Intervention and Monitoring
pp. 383
Finding Quantitative Trait Loci Genes
pp. 394
Large Sample Theory
pp. 397
Case Study: Longitudinal HIV Cohort Data
pp. 419
Probability of Success of an In Vitro Fertilization Program
pp. 435
Individualized Antiretroviral Initiation Rules
pp. 437
Multi-Process Models
pp. 459
Cross-Validated Targeted Minimum-Loss-Based Estimation
pp. 475
Targeted Bayesian Learning
pp. 476
Hierarchical Models
pp. 492
Robust Estimation of a Location Parameter
pp. 495
TMLE in Adaptive Group Sequential Covariate-Adjusted RCTs
pp. 511
Non-Linear Dynamic Models
pp. 521
Foundations of TMLE
pp. 527
Regression Models and Life-Tables
pp. 536
Sequential Analysis
pp. 547
Exponential Family Dynamic Models
pp. 569
Bootstrap Methods: Another Look at the Jackknife
pp. 585
Introduction to R Code Implementation
pp. 597
Multivariate Modelling and Forecasting
pp. 610
Information Theory and an Extension of the Maximum Likelihood Principle
pp. 653
Appendix: Distribution Theory and Linear Algebra
pp. 704
Erratum
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