# Analysis of semiparametric regression models for repeated outcomes in the presence of missing data

@article{Robins1995AnalysisOS, title={Analysis of semiparametric regression models for repeated outcomes in the presence of missing data}, author={James M. Robins and Andrea Rotnitzky and Lue Ping Zhao}, journal={Journal of the American Statistical Association}, year={1995}, volume={90}, pages={106-121} }

Abstract We propose a class of inverse probability of censoring weighted estimators for the parameters of models for the dependence of the mean of a vector of correlated response variables on a vector of explanatory variables in the presence of missing response data. The proposed estimators do not require full specification of the likelihood. They can be viewed as an extension of generalized estimating equations estimators that allow for the data to be missing at random but not missing… Expand

#### 1,379 Citations

Semiparametric regression estimation in the presence of dependent censoring

- Mathematics
- 1995

SUMMARY We propose a semiparametric estimation procedure for estimating the regression of an outcome Y, measured at the end of a fixed follow-up period, on baseline explanatory variables X, measured… Expand

Semiparametric Efficiency in Multivariate Regression Models with Missing Data

- Mathematics
- 1995

Abstract We consider the efficiency bound for the estimation of the parameters of semiparametric models defined solely by restrictions on the means of a vector of correlated outcomes, Y, when the… Expand

Semiparametric Regression for Repeated Outcomes With Nonignorable Nonresponse

- Mathematics
- 1998

Abstract We consider inference about the parameter β* indexing the conditional mean of a vector of correlated outcomes given a vector of explanatory variables when some of the outcomes are missing in… Expand

Regression analysis of longitudinal data with outcome-dependent sampling and informative censoring.

- Mathematics, Medicine
- Scandinavian journal of statistics, theory and applications
- 2019

A semi-parametric joint regression model is proposed and a composite likelihood function based on a conditional order statistics argument is constructed, which bypasses the need to integrate over the random effect and offers the advantage of easy computation. Expand

Double robust and efficient estimation of a prognostic model for events in the presence of dependent censoring.

- Computer Science, Medicine
- Biostatistics
- 2016

This work introduces sequentially augmented regression (SAR) and proposes a closely related non-parametric approach using targeted maximum likelihood estimation (TMLE; van der Laan and Rubin, 2006), and compares IPCW, SAR, and TMLE (implemented parametrically and with Super Learner) through simulation and the above-mentioned case study. Expand

Estimation of Regression Coefficients When Some Regressors are not Always Observed

- Mathematics
- 1994

Abstract In applied problems it is common to specify a model for the conditional mean of a response given a set of regressors. A subset of the regressors may be missing for some study subjects either… Expand

Semiparametric estimation of the average causal effect of treatment on an outcome measured after a postrandomization event, with missing outcome data.

- Medicine
- Biostatistics
- 2010

This work extends the semiparametric likelihood sensitivity analysis approach of Gilbert and others (2003) and Jemiai and Rotnitzky (2005) to allow the outcome to be MAR, and combines these methods with the robust likelihood-based method of Little and An (2004) for handling MAR data to provide semibarametric estimation of the average causal effect of treatment on the outcome. Expand

APPLICATION OF SEMIPARAMETRIC METHODS FOR REGRESSION MODELS WITH MISSING COVARIATE INFORMATION

- Mathematics
- 2005

This dissertation addresses regression models with missing covariate data. These methods are shown to be significant to public health research since they enable researchers to use a wider spectrum of… Expand

Semiparametric inference in matched case-control studies with missing covariate data

- Mathematics
- 2002

We consider the problem of matched studies with a binary outcome that are analysed using conditional logistic regression, and for which data on some covariates are missing for some study… Expand

Semiparametric modeling of repeated measurements under outcome-dependent follow-up.

- Mathematics, Medicine
- Statistics in medicine
- 2009

A natural extension of the semiparametric regression procedure of Lin and Ying by building a class of 'inverse-intensity-rate-ratio' weighted estimators that accommodate such outcome-dependent follow-up in regression analysis of repeated measurements. Expand

#### References

SHOWING 1-10 OF 48 REFERENCES

Semiparametric Efficiency in Multivariate Regression Models with Missing Data

- Mathematics
- 1995

Abstract We consider the efficiency bound for the estimation of the parameters of semiparametric models defined solely by restrictions on the means of a vector of correlated outcomes, Y, when the… Expand

Recovery of Information and Adjustment for Dependent Censoring Using Surrogate Markers

- Mathematics
- 1992

A class of tests and estimators for the parameters of the Cox proportional hazards model, the accelerated failure time model, and a model for the effect of treatment on the mean of a response… Expand

Estimation of Regression Coefficients When Some Regressors are not Always Observed

- Mathematics
- 1994

Abstract In applied problems it is common to specify a model for the conditional mean of a response given a set of regressors. A subset of the regressors may be missing for some study subjects either… Expand

Locally Efficient Median Regression with Random Censoring and Surrogate Markers

- Mathematics
- 1996

Robins and Rotnitzky (1992) proved a general representation theorem for (1) the efficient score and (2) the set of influence functions for regular asymptotically linear (RAL) estimators in arbitrary… Expand

Correcting for non-compliance in randomized trials using structural nested mean models

- Mathematics
- 1994

In a randomized trial designed to study the effect of a treatment of interest on the evolution of the mean of a time-dependent outcome variable, subjects are assigned to a treatment regime, or,… Expand

Longitudinal data analysis using generalized linear models

- Mathematics
- 1986

SUMMARY This paper proposes an extension of generalized linear models to the analysis of longitudinal data. We introduce a class of estimating equations that give consistent estimates of the… Expand

An analytic method for randomized trials with informative censoring: Part II

- Mathematics, Medicine
- Lifetime data analysis
- 1995

A class of consistent and reasonably efficient semiparametric tests and estimators for the treatment effect under two non-identifiable assumptions that allow one to test for and estimate an effect of treatment on time to disease in the presence of informative censoring is provided. Expand

A comparison of likelihood-based and marginal estimating equation methods for analysing repeated ordered categorical responses with missing data: application to an intervention trial of vitamin prophylaxis for oesophageal dysplasia.

- Mathematics, Medicine
- Statistics in medicine
- 1994

This research develops appropriate methods for analysing repeated ordinal categorical data that arose in an intervention trial to prevent oesophageal cancer and recommends the adapted likelihood-based approach for problems of this type, in which there are abundant data for estimating parameters. Expand

Statistical Analysis with Missing Data

- Mathematics, Business
- 1987

Preface.PART I: OVERVIEW AND BASIC APPROACHES.Introduction.Missing Data in Experiments.Complete-Case and Available-Case Analysis, Including Weighting Methods.Single Imputation Methods.Estimation of… Expand

A kernel method for incorporating information on disease progression in the analysis of survival

- Mathematics
- 1994

SUMMARY This paper considers incorporating information on disease progression in the analysis of survival. A three-state model is assumed, with the distribution of each transition estimated… Expand