# Statistical Methods for Incomplete Covariates and Two-Phase Designs

@inproceedings{McIsaac2013StatisticalMF, title={Statistical Methods for Incomplete Covariates and Two-Phase Designs}, author={Michael A. McIsaac}, year={2013} }

Incomplete data is a pervasive problem in health research, and as a result statistical methods enabling inference based on partial information play a critical role. This thesis explores estimation of regression coefficients and associated inferences when variables are incompletely observed. In the later chapters, we focus primarily on settings with incomplete covariate data which arise by design, as in studies with two-phase sampling schemes, as opposed to incomplete data which arise due to… CONTINUE READING

Create an AI-powered research feed to stay up to date with new papers like this posted to ArXiv

#### Citations

##### Publications citing this paper.

## Response‐dependent two‐phase sampling designs for biomarker studies

VIEW 4 EXCERPTS

CITES BACKGROUND & METHODS

HIGHLY INFLUENCED

#### References

##### Publications referenced by this paper.

SHOWING 1-10 OF 138 REFERENCES

## The Canadian Longitudinal Study on Aging (CLSA)

VIEW 4 EXCERPTS

HIGHLY INFLUENTIAL

## Statistical analysis with missing data (second edition)

VIEW 22 EXCERPTS

HIGHLY INFLUENTIAL

## Observational cohort studies: lessons learnt from the University of Toronto Psoriatic Arthritis Program.

VIEW 6 EXCERPTS

HIGHLY INFLUENTIAL

## Comparison of ustekinumab and etanercept for moderate-to-severe psoriasis.

VIEW 4 EXCERPTS

HIGHLY INFLUENTIAL

## Semiparametric methods for response‐selective and missing data problems in regression

VIEW 17 EXCERPTS

HIGHLY INFLUENTIAL

## Multi-stage sampling in genetic epidemiology.

VIEW 7 EXCERPTS

HIGHLY INFLUENTIAL

## Estimation of Regression Coefficients When Some Regressors Are Not Always Observed

VIEW 10 EXCERPTS

HIGHLY INFLUENTIAL

## Multiple Imputation for Nonresponse in Surveys

VIEW 4 EXCERPTS

HIGHLY INFLUENTIAL

## Longitudinal data analysis using generalized linear models

VIEW 4 EXCERPTS

HIGHLY INFLUENTIAL