Biostatistics Commons^™

Hierarchical Rank Aggregation With Applications To Nanotoxicology, Trina Patel, Donatello Telesca, Robert Rallo, Saji George, Xia Tian, Nel Andre

COBRA Preprint Series

The development of high throughput screening (HTS) assays in the field of nanotoxicology provide new opportunities for the hazard assessment and ranking of engineered nanomaterials (ENM). It is often necessary to rank lists of materials based on multiple risk assessment parameters, often aggregated across several measures of toxicity and possibly spanning an array of experimental platforms. Bayesian models coupled with the optimization of loss functions have been shown to provide an effective framework for conducting inference on ranks. In this article we present various loss function based ranking approaches for comparing ENM within experiments and toxicity parameters. Additionally, we propose …

Robustness Of Measures Of Interaction To Unmeasured Confounding, Eric J. Tchetgen Tchetgen, Tyler J. Vanderweele

Harvard University Biostatistics Working Paper Series

No abstract provided.

Bootstrap-Based Inference On The Difference In The Means Of Two Correlated Functional Processes, Ciprian M. Crainiceanu, Ana-Maria Staicu, Shubankar Ray, Naresh Punjabi

Johns Hopkins University, Dept. of Biostatistics Working Papers

Nonparametric inference methods on the mean difference between two correlated Functional processes are proposed. We compare methods that: 1) incorporate different levels of smoothing of the mean and covariance; 2) preserve the sampling design; and 3) use parametric and nonparametric estimation of the mean functions. We apply our method to estimating the mean difference between average normalized δ-power of sleep electroencephalograms for 51 subjects with severe sleep apnea and 51 matched controls in the first 4 hours after sleep onset. Data are obtained from the Sleep Heart Health Study (SHHS), the largest community cohort study of sleep. While methods are …

Robustness Of Measures Of Interaction To Unmeasured Confounding, Eric J. Tchetgen Tchetgen, Tyler J. Vanderweele

COBRA Preprint Series

In this paper, we study the impact of unmeasured confounding on inference about a two-way interaction in a mean regression model with identity, log or logit link function. Necessary and sufficient conditions are established for a two-way interaction to be nonparametrically identified from the observed data, despite unmeasured confounding for the factors defining the interaction. A lung cancer data application illustrates the results.

Does Secondary Inflammatory Breast Cancer Represent Post-Surgical Metastatic Disease?, Salman Hashmi, Ladan Zolfaghari, Paul H. Levine

Epidemiology Faculty Publications

The phenomenon of accelerated tumor growth following surgery has been observed repeatedly and merits further study. Inflammatory breast carcinoma (IBC) is widely recognized as an extremely aggressive malignancy characterized by micrometastasis at the time of diagnosis, with one interesting subgroup defined as secondary IBC where pathologically identifiable IBC appears after surgical treatment of a primary non-inflammatory breast cancer. One possible mechanism can be related to the stimulation of dormant micrometastasis through local angiogenesis occurring as part of posttraumatic healing. In this report, we review cases of secondary IBC and others where localized trauma was followed by the appearance of IBC …

On A Logistic Mixed Model Formulation Of A Quadratic Exponential Model For Correlated Binary Outcomes, Eric J. Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.

On A Closed-Form Doubly Robust Estimator Of The Adjusted Odds Ratio For A Binary Exposure, Eric J. Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.

Formulae For Causal Mediation Analysis In An Odds Ratio Context Without A Normality Assumption For The Continuous Mediator, Eric J. Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.

A Cautionary Note On Specification Of The Correlation Structure In Inverse-Probability-Weighted Estimation For Repeated Measures, Eric J. Tchetgen Tchetgen, M. Maria Glymour, Jennifer Weuve, James Robins

Harvard University Biostatistics Working Paper Series

No abstract provided.

On Parametrization, Robustness And Sensitivity Analysis In A Marginal Structural Cox Proportional Hazards Model For Point Exposure, Eric J. Tchetgen Tchetgen, James M. Robins

Harvard University Biostatistics Working Paper Series

No abstract provided.

Multiple-Robust Estimation Of An Odds Ratio Interaction, Eric J. Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.

Inverse Odds Ratio-Weighted Estimation For Causal Mediation Analysis, Eric J. Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.

Effect Of Nutrition Changes On Foods Selected By Students In A Middle School-Based Diabetes Prevention Intervention Program: The Healthy Experience, Connie Mobley, Diane D. Stadler, Myrlene A. Staten, Laure El Ghormli, Bonnie Gillis, Jill Hartstein, Anna Maria Siega-Riz, Amy Virus, Healthy Study Group

GW Biostatistics Center

No abstract provided.

Repeat Prenatal Corticosteroid Prior To Preterm Birth: A Systematic Review And Individual Participant Data Meta-Analysis For The Precise Study Group (Prenatal Repeat Corticosteroid International Ipd Study Group: Assessing The Effects Using The Best Level Of Evidence) - Study Protocol, Caroline A. Crowther, Fariba Aghajafari, Lisa M. Askie, Elizabeth V. Asztalos, Peter Brocklehurst, Elizabeth A. Thom, +22 Additional Authors

GW Biostatistics Center

Background

The aim of this individual participant data (IPD) meta-analysis is to assess whether the effects of repeat prenatal corticosteroid treatment given to women at risk of preterm birth to benefit their babies are modified in a clinically meaningful way by factors related to the women or the trial protocol.

Methods/Design

The Prenatal Repeat Corticosteroid International IPD Study Group: assessing the effects using the best level of Evidence (PRECISE) Group will conduct an IPD meta-analysis. The PRECISE International Collaborative Group was formed in 2010 and data collection commenced in 2011. Eleven trials with up to 5,000 women and 6,000 infants …

Alternate Estrogen Receptors Promote Invasion Of Inflammatory Breast Cancer Cells Via Non-Genomic Signaling, Kazufumi Ohshiro, Arnold M. Schwartz, Paul H. Levine, Rakesh Kumar

Epidemiology Faculty Publications

Although Inflammatory Breast Cancer (IBC) is a rare and an aggressive type of locally advanced breast cancer with a generally worst prognosis, little work has been done in identifying the status of non-genomic signaling in the invasiveness of IBC. The present study was performed to explore the status of non-genomic signaling as affected by various estrogenic and anti-estrogenic agents in IBC cell lines SUM149 and SUM190. We have identified the presence of estrogen receptor α (ERα) variant, ERα36 in SUM149 and SUM190 cells. This variant as well as ERβ was present in a substantial concentration in IBC cells. The treatment …

Statistical Methods For Normalization And Analysis Of High-Throughput Genomic Data, Tobias Guennel

Theses and Dissertations

High-throughput genomic datasets obtained from microarray or sequencing studies have revolutionized the field of molecular biology over the last decade. The complexity of these new technologies also poses new challenges to statisticians to separate biological relevant information from technical noise. Two methods are introduced that address important issues with normalization of array comparative genomic hybridization (aCGH) microarrays and the analysis of RNA sequencing (RNA-Seq) studies. Many studies investigating copy number aberrations at the DNA level for cancer and genetic studies use comparative genomic hybridization (CGH) on oligo arrays. However, aCGH data often suffer from low signal to noise ratios resulting …

A Systematic Selection Method For The Development Of Cancer Staging Systems, Yunzhi Lin, Richard Chappell, Mithat Gonen

Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series

The tumor-node-metastasis (TNM) staging system has been the anchor of cancer diagnosis, treatment, and prognosis for many years. For meaningful clinical use, an orderly, progressive condensation of the T and N categories into an overall staging system needs to be defined, usually with respect to a time-to-event outcome. This can be considered as a cutpoint selection problem for a censored response partitioned with respect to two ordered categorical covariates and their interaction. The aim is to select the best grouping of the TN categories. A novel bootstrap cutpoint/model selection method is proposed for this task by maximizing bootstrap estimates of …

On Identification Of Natural Direct Effects When A Confounder Of The Mediator Is Directly Affected By Exposure, Eric J. Tchetgen Tchetgen, Tyler J. Vanderweele

Harvard University Biostatistics Working Paper Series

No abstract provided.

Analysis Of Periodontal Data Using Circular Statistics, Samopriyo Maitra, Thomas M. Braun

The University of Michigan Department of Biostatistics Working Paper Series

Periodontal disease is a common cause of tooth loss in adults. The severity of periodontal disease is usually quantified based upon the magnitudes of several tooth-level clinical parameters, the most common of which is clinical attachment level (CAL). Re- cent clinical studies have presented data on the distribution of periodontal disease in hopes of providing information for localized treatments that can reduce the prevalence of periodontal disease. However, these findings have been descriptive without consid- eration of statistical modeling for estimation and inference. To this end, we visualize the mouth as a circle and the teeth as points located on …

The Bayesian Continual Reassessment Method Using A Mixture-Of-Uniforms Prior, Thomas M. Braun

The University of Michigan Department of Biostatistics Working Paper Series

Traditionally, the Bayesian formulation of the Continual Reassessment Method (CRM) is implemented with a one-parameter model describing the association of dose with the probability of dose-limiting toxicity (DLT). Determination of the appropriate value of the prior variance is often done via simulation over a grid search of possible values until suitable operating characteristics are found. However, it is under-appreciated that the operating characteristics for a given value of the prior variance vary by the “skeleton,” which is the vector of a priori probabilities of DLT for each dose. The skeleton implicitly leads to a set of indifference intervals, with one …