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Full-Text Articles in Design of Experiments and Sample Surveys

On The Formation Of Weighting Adjustment Cells For Unit Nonresponse, Sonya Vartivarian, Rod Little Aug 2003

On The Formation Of Weighting Adjustment Cells For Unit Nonresponse, Sonya Vartivarian, Rod Little

The University of Michigan Department of Biostatistics Working Paper Series

A method is proposed for weighting adjustments for unit nonresponse based on a crossclassification by the estimated propensity to respond and by the predicted mean of a survey outcome. Simulations to assess the performance of the method are described.

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Design Considerations For Efficient And Effective Microarray Studies, M. Kathleen Kerr Jun 2003

Design Considerations For Efficient And Effective Microarray Studies, M. Kathleen Kerr

UW Biostatistics Working Paper Series

This paper describes the theoretical and practical issues in experimental design for gene expression microarrays. Specifically, this paper (1) discusses the basic principles of design (randomization, replication, and blocking) as they pertain to microarrays, and (2) provides some general guidelines for statisticians designing microarray studies.

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Mixtures Of Varying Coefficient Models For Longitudinal Data With Discrete Or Continuous Non-Ignorable Dropout, Joseph W. Hogan, Xihong Lin, Benjamin A. Herman May 2003

Mixtures Of Varying Coefficient Models For Longitudinal Data With Discrete Or Continuous Non-Ignorable Dropout, Joseph W. Hogan, Xihong Lin, Benjamin A. Herman

The University of Michigan Department of Biostatistics Working Paper Series

The analysis of longitudinal repeated measures data is frequently complicated by missing data due to informative dropout. We describe a mixture model for joint distribution for longitudinal repeated measures, where the dropout distribution may be continuous and the dependence between response and dropout is semiparametric. Specifically, we assume that responses follow a varying coefficient random effects model conditional on dropout time, where the regression coefficients depend on dropout time through unspecified nonparametric functions that are estimated using step functions when dropout time is discrete (e.g., for panel data) and using smoothing splines when dropout time is continuous. Inference under the …

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Semiparametric Regression Models With Missing Data: The Mathematics In The Work Of Robins Et Al., Menggang Yu, Bin Nan May 2003

Semiparametric Regression Models With Missing Data: The Mathematics In The Work Of Robins Et Al., Menggang Yu, Bin Nan

The University of Michigan Department of Biostatistics Working Paper Series

This review is an attempt to understand the landmark papers of Robins, Rotnitzky, and Zhao (1994) and Robins and Rotnitzky (1992). We revisit their main results and corresponding proofs using the theory outlined in the monograph by Bickel, Klaassen, Ritov, and Wellner (1993). We also discuss an illustrative example to show the details of applying these theoretical results.

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Design Of The Hiv Prevention Trials Network (Hptn) Protocol 054: A Cluster Randomized Crossover Trial To Evaluate Combined Access To Nevirapine In Developing Countries, Jim Hughes, Robert L. Goldenberg, Catherine M. Wilfert, Megan Valentine, Kasonde G. Mwinga, Laura A. Guay, Francis Mmiro, Jeffrey S. A. Stringer Mar 2003

Design Of The Hiv Prevention Trials Network (Hptn) Protocol 054: A Cluster Randomized Crossover Trial To Evaluate Combined Access To Nevirapine In Developing Countries, Jim Hughes, Robert L. Goldenberg, Catherine M. Wilfert, Megan Valentine, Kasonde G. Mwinga, Laura A. Guay, Francis Mmiro, Jeffrey S. A. Stringer

UW Biostatistics Working Paper Series

HPTN054 is a cluster randomized trial designed to compare two approaches to providing single dose nevirapine to HIV-seropositive mothers and their infants to prevent mother-to-child transmission of HIV in resource limited settings. A number of challenging issues arose during the design of this trial. Most importantly, the need to achieve high participation rates among pregnant, HIV-seropositive women in selected prenatal care clinics led us to develop a method of collecting anonymous and unlinked information on a key surrogate endpoint instead of pursuing linked and identified information on a clinical endpoint. In addition, since group counseling is the standard model for …

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Penalized Spline Nonparametric Mixed Models For Inference About A Finite Population Mean From Two-Stage Samples, Hui Zheng, Rod Little Mar 2003

Penalized Spline Nonparametric Mixed Models For Inference About A Finite Population Mean From Two-Stage Samples, Hui Zheng, Rod Little

The University of Michigan Department of Biostatistics Working Paper Series

Samplers often distrust model-based approaches to survey inference due to concerns about model misspecification when applied to large samples from complex populations. We suggest that the model-based paradigm can work very successfully in survey settings, provided models are chosen that take into account the sample design and avoid strong parametric assumptions. The Horvitz-Thompson (HT) estimator is a simple design-unbiased estimator of the finite population total in probability sampling designs. From a modeling perspective, the HT estimator performs well when the ratios of the outcome values and the inclusion probabilities are exchangeable. When this assumption is not met, the HT estimator …

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Selective Multiple Imputation Of Keys For Statistical Disclosure Control In Microdata, Rod Little, Fang Liu Jan 2003

Selective Multiple Imputation Of Keys For Statistical Disclosure Control In Microdata, Rod Little, Fang Liu

The University of Michigan Department of Biostatistics Working Paper Series

The fundamental tension in statistical disclosure control (SDC) of microdata is the trade-off between the protection of individual respondents and the release of enough information for statistical inferences. We consider microdata that include key variables that contain identifying information and target variables that include sensitive information. Releasing the original data may expose some individuals in the sample to high risk of disclosure; deleting key variables is a common approach, but this loses information for some statistical analysis. This paper proposes selective multiple imputation of key variables (SMIKe) as an alternative SDC technique between those two extremes, and applies SMIKe to …

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Estimating Disease Prevalence In Two-Phase Studies, Todd A. Alonzo, Margaret S. Pepe Jan 2003

Estimating Disease Prevalence In Two-Phase Studies, Todd A. Alonzo, Margaret S. Pepe

UW Biostatistics Working Paper Series

Disease prevalence is ideally estimated using a “gold standard” to ascertain true disease status on all subjects in a population of interest. In practice, however, the gold standard may be too costly or invasive to be applied to all subjects, in which case a two-phase design is often employed. Phase 1 data consisting of inexpensive and non-invasive screening tests on all study subjects are used to determine the subjects that receive the gold standard in the second phase. Naïve estimates of prevalence in two-phase studies can be biased (verification bias). Imputation and re-weighting estimators are often used to avoid this …

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Assessing The Accuracy Of A New Diagnostic Test When A Gold Standard Does Not Exist, Todd A. Alonzo, Margaret S. Pepe Oct 1998

Assessing The Accuracy Of A New Diagnostic Test When A Gold Standard Does Not Exist, Todd A. Alonzo, Margaret S. Pepe

UW Biostatistics Working Paper Series

Often the accuracy of a new diagnostic test must be assessed when a perfect gold standard does not exist. Use of an imperfect test biases the accuracy estimates of the new test. This paper reviews existing approaches to this problem including discrepant resolution and latent class analysis. Deficiencies with these approaches are identified. A new approach is proposed that combines the results of several imperfect reference tests to define a better reference standard. We call this the composite reference standard (CRS). Using the CRS, accuracy can be assessed using multistage sampling designs. Maximum likelihood estimates of accuracy and expressions for …

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