Motivating sample sizes in adaptive Phase I trials via Bayesian posterior credible intervals

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146418/1/biom12872-sup-0001-SuppData.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146418/2/biom12872_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146418/3/biom12872.pd

Genomic Clinical Trials and Predictive Medicine by Richard M. Simon

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109589/1/insr12085_3.pd

Adaptive Design Theory and Implementation Using SAS and R, Second Edition

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/116075/1/insr12143.pd

Analysis of Periodontal Data using Circular Statistics

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 circumference of the circle to allow the use of circular statistical methods to determine the mean location of diseased teeth. We assume the directions of diseased teeth, as determined by their tooth averaged CAL values, to be observations from a von Mises distribution, the mean of which is a function of mouth-level covariates. Because multiple teeth from a subject are correlated, we use a bias-corrected generalized estimating equation approach (Mancl and DeRouen, 2001, Biometrics 57, 126–134) to obtain robust variance estimates for our parameter estimates. Via simulations of data motivated from an actual study of periodontal disease, we demonstrate that our methods have excellent performance in the moderately small sample sizes common to most periodontal studies

Impact and Recovery Process of Mini Flash Crashes: An Empirical Study

In an Ultrafast Extreme Event (or Mini Flash Crash), the price of a traded stock increases or decreases strongly within milliseconds. We present a detailed study of Ultrafast Extreme Events in stock market data. In contrast to popular belief, our analysis suggests that most of the Ultrafast Extreme Events are not primarily due to High Frequency Trading. In at least 60 percent of the observed Ultrafast Extreme Events, the main cause for the events are large market orders. In times of financial crisis, large market orders are more likely which can be linked to the significant increase of Ultrafast Extreme Events occurrences. Furthermore, we analyze the 100 trades following each Ultrafast Extreme Events. While we observe a tendency of the prices to partially recover, less than 40 percent recover completely. On the other hand we find 25 percent of the Ultrafast Extreme Events to be almost recovered after only one trade which differs from the usually found price impact of market orders

Permutation Tests for Random Effects in Linear Mixed Models

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/92041/1/j.1541-0420.2011.01675.x.pd

Adaptive prior variance calibration in the Bayesian continual reassessment method

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98219/1/sim5621.pd

Correlation of Matrix Metalloproteinases and Tissue Inhibitors of Matrix Metalloproteinase Expression in Ileal Carcinoids, Lymph Nodes and Liver Metastasis with Prognosis and Survival

Purpose: Ileal carcinoids are gut epithelial tumors originating from serotonin-containing enterochromaffin (EC) cells. Therapeutic options for effectively inhibiting the growth and spread of metastatic carcinoids are still limited. We aimed to identify the role of matrix metalloproteinases (MMPs) and their endogenous tissue inhibitors (TIMPs) during tumor development and metastasis. Patients and Methods: Tissue samples were obtained from surgically treated patients. Expression of the EC-cell marker, vesicular monoamine transporter-1 (VMAT-1), was used to verify ileal carcinoids. We investigated the differential expression of MMP-2, 7, 9, 11, and 13 and their endogenous inhibitors (TIMP-1, 2, and 3) by quantitative real-time RT-PCR in 25 primary tumors, their corresponding lymph node metastases and/or liver metastases and matched normal mucosa. Results: Significantly increased expression of VMAT-1, MMP-2, MMP-11, TIMP-1 and TIMP-3 was determined by quantitative RT-PCR in EC-cell carcinoids compared to normal intestinal mucosa (p < 0.05). In contrast, MMP-2 and MMP-9 as well as TIMP-1, TIMP-2, and TIMP-3 expression in primary tumors of patients with liver metastases (M1) was significantly lower than in patients lacking liver metastases (M0). EC-cell tumors were significantly larger in the M1 group of tumors, while VMAT-1 expression was significantly decreased. We found an inverse correlation between tumor size and prognosis. Univariate analysis further revealed that decreased expression of VMAT-1, MMP-2 and TIMP-3 in primary tumors was significantly associated with a reduced survival time of the patients. Conclusion: Our data reveal that MMP-2 and TIMP-3 expression together with VMAT-1 expression are of potential prognostic and clinical value in ileal carcinoids. Copyright (C) 2008 S. Karger AG, Base

The Bayesian Continual Reassessment Method Using a Mixture-of-Uniforms Prior

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 interval for each dose, that contain values of the model parameter that support each dose being the MTD. To remove the need of selecting a value for the prior variance, we propose placing a uniform distribution over each of the indifference intervals, making the prior distribution for the model parameter a mixture of uniform distributions. Via simulation, we compare the operating characteristics of the CRM using a traditional continuous prior to using the mixture-of-uniforms prior in a variety of settings and show that the mixture-of-uniforms prior leads to operating characteristics that are less sensitive to the chosen skeleton

Parents' dental anxiety and oral health literacy: effects on parents' and children's oral health‐related experiences

Objective To explore a) the relationship between parents'/guardians' dental anxiety and oral health literacy and b) those between these variables and background and oral health‐related characteristics. Methods Survey data were collected from 187 parents/guardians (81% female; average age 37 years). Dental anxiety was measured with the Dental Anxiety Scale – Revised ( DAS ‐ R ) and oral health literacy with the Rapid Estimate of Adult Literacy in Dentistry ( REALD ‐30). Children's dental charts were reviewed to collect information about their dental treatment. Results DAS ‐ R and REALD ‐30 scores were correlated ( r  = −0.22; P  = 0.003). A multivariate regression model with DAS ‐ R score as the dependent variable showed that the DAS ‐ R score has a significant multivariate association with REALD ‐30, oral health, income, and presence of fillings. Conclusions Dental anxiety and oral health literacy are related. However, DAS score has a significant multivariate association with the four variables REALD ‐30 score, oral health, income, and presence of fillings. These findings show that among socioeconomically disadvantaged patients, the contributors to poor oral health are interrelated and multidetermined and include poor oral health literacy and dental anxiety. The public health message is that in order to improve the overall oral health of socioeconomically disadvantaged patients, public health stakeholders need to consider how to communicate with these patients effectively and how to reduce dental anxiety. Gaining a better understanding of how to communicate with parents a) at an appropriate literacy level and b) in a way that it reduces dental anxiety is therefore crucial.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108635/1/jphd12046.pd