Design of Experiments and Sample Surveys Commons^™

Robust Likelihood-Based Analysis Of Multivariate Data With Missing Values, Rod Little, An Hyonggin

The University of Michigan Department of Biostatistics Working Paper Series

The model-based approach to inference from multivariate data with missing values is reviewed. Regression prediction is most useful when the covariates are predictive of the missing values and the probability of being missing, and in these circumstances predictions are particularly sensitive to model misspecification. The use of penalized splines of the propensity score is proposed to yield robust model-based inference under the missing at random (MAR) assumption, assuming monotone missing data. Simulation comparisons with other methods suggest that the method works well in a wide range of populations, with little loss of efficiency relative to parametric models when the latter …

Marginalized Transition Models For Longitudinal Binary Data With Ignorable And Nonignorable Dropout, Brenda F. Kurland, Patrick J. Heagerty

UW Biostatistics Working Paper Series

We extend the marginalized transition model of Heagerty (2002) to accommodate nonignorable monotone dropout. Using a selection model, weakly identified dropout parameters are held constant and their effects evaluated through sensitivity analysis. For data missing at random (MAR), efficiency of inverse probability of censoring weighted generalized estimating equations (IPCW-GEE) is as low as 40% compared to a likelihood-based marginalized transition model (MTM) with comparable modeling burden. MTM and IPCW-GEE regression parameters both display misspecification bias for MAR and nonignorable missing data, and both reduce bias noticeably by improving model fit

Clinical Effectiveness Of A Subperiosteal Anchorage Device, Monica Anne Witte

Loma Linda University Electronic Theses, Dissertations & Projects

The purpose of this pilot study was to evaluate the clinical efficacy of a subperiosteal anchorage device, the palatal OnPlant™, during orthodontic retraction of protruding anterior teeth in cases requiring maxillary premolar extraction. Seven subjects (5 female, 2 male), ages 13 to 55, were selected for the study. The OnPlant was surgically placed in the mid-palatal region through a well-defined subperiosteal tunnel. Following the manufacturer recommended osseointegration period of four months, the OnPlant was uncovered and attached to the first molars by means of a transpalatal bar. Standard orthodontic treatment then commenced to retract the anterior teeth after the first …

Weighting Adjustments For Unit Nonresponse With Multiple Outcome Variables, Sonya L. Vartivarian, Rod Little

The University of Michigan Department of Biostatistics Working Paper Series

Weighting is a common form of unit nonresponse adjustment in sample surveys where entire questionnaires are missing due to noncontact or refusal to participate. Weights are inversely proportional to the probability of selection and response. A common approach computes the response weight adjustment cells based on covariate information. When the number of cells thus created is too large, a coarsening method such as response propensity stratification can be applied to reduce the number of adjustment cells. Simulations in Vartivarian and Little (2002) indicate improved efficiency and robustness of weighting adjustments based on the joint classification of the sample by two …

To Model Or Not To Model? Competing Modes Of Inference For Finite Population Sampling, Rod Little

The University of Michigan Department of Biostatistics Working Paper Series

Finite population sampling is perhaps the only area of statistics where the primary mode of analysis is based on the randomization distribution, rather than on statistical models for the measured variables. This article reviews the debate between design and model-based inference. The basic features of the two approaches are illustrated using the case of inference about the mean from stratified random samples. Strengths and weakness of design-based and model-based inference for surveys are discussed. It is suggested that models that take into account the sample design and make weak parametric assumptions can produce reliable and efficient inferences in surveys settings. …

Inference For The Population Total From Probability-Proportional-To-Size Samples Based On Predictions From A Penalized Spline Nonparametric Model, Hui Zheng, Rod Little

The University of Michigan Department of Biostatistics Working Paper Series

Inference about the finite population total from probability-proportional-to-size (PPS) samples is considered. In previous work (Zheng and Little, 2003), penalized spline (p-spline) nonparametric model-based estimators were shown to generally outperform the Horvitz-Thompson (HT) and generalized regression (GR) estimators in terms of the root mean squared error. In this article we develop model-based, jackknife and balanced repeated replicate variance estimation methods for the p-spline based estimators. Asymptotic properties of the jackknife method are discussed. Simulations show that p-spline point estimators and their jackknife standard errors lead to inferences that are superior to HT or GR based inferences. This suggests that nonparametric …

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.

Behavioral Evaluation Of The Psychological Welfare And Environmental Requirements Of Agricultural Research Animals: Theory, Measurement, Ethics, And Practical Implications, Lesley A. King

Experimentation Collection

The welfare of agricultural research animals relies not only on measures of good health but also on the presence of positive emotional states and the absence of aversive or unpleasant subjective states such as fear, frustration, or association with pain. Although subjective states are not inherently observable, their interaction with motivational states can be measured through assessment of motivated behavior, which indicates the priority animals place on obtaining or avoiding specific environmental stimuli and thus allows conclusions regarding the impact of housing, husbandry, and experimental procedures on animal welfare. Preference tests and consumer demand models demonstrate that animal choices are …

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.

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 …

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.

Assessing Left-Handedness With Exact And Approximate Confidence Intervals Appropriate For Samples Of Different Sizes, Virginia Gardner

Honors Capstones

Capstone submitted as a graduation requirement for the BSU Honors Program.

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 …

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 …

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 …

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 …

Pain And Distress Associated With Polyclonal Antibody Production: Discussion And Recommendations, The Humane Society Of The United States

ANIMAL RESEARCH

The Humane Society of the United States (HSUS) held a workshop in August 2002 in order to develop recommendations for minimizing pain and distress associated with polyclonal antibody (Pab) production. A small group of experts in the fields of antibody production, animal welfare, in vitro alternatives, and/or regulatory compliance participated in the roundtable discussion. The workshop was a scientifically based meeting, and recommendations were based on the extensive experience of the workshop participants as well as published literature regarding the relevant issues.

Participants recognized that insufficient attention has been paid to animal welfare aspects of Pab production, in part because …