Statistical Methods for Modeling Count Data with Overdispersion and Missing Time Varying Categorical Covariates

In studying the association between count outcomes and covariates using Poisson regression, the necessary requirement that the mean and variance of responses are equivalent for each covariate pattern is not always met in real datasets. This violation of equidispersion can lead to invalid inference unless proper alternative models are considered. There is currently no comprehensive and definitive assessment of the different methods of dealing with overdispersion, nor is there a standard approach for determining the threshold of overdispersion such that statistical intervention is necessary. The issue of overdispersion can be further complicated by the presence of missing covariate data in count outcome models. In this dissertation we have (1) compared the performance of different statistical models for dealing with overdispersion, (2) determined an appropriate threshold of the ratio of the Pearson chi-squared goodness of fit statistic to degrees of freedom σp such that statistical intervention is necessary to address the overdispersion, (3) developed a latent transition multiple imputation (LTMI) approach for dealing with missing time varying categorical covariates in count outcome models, and (4) compared the performance of LTMI with complete case analysis (CCA) and latent class multiple imputation (LCMI) in addressing missing time varying categorical covariates in the presence of overdispersion. Latent class assignment was determined via both SAS software and random effect modeling, and missing observation imputation was performed using predictive mean matching multiple imputation methods. We utilized extensive simulation studies to assess the performance of the proposed methods on a variety of overdispersion and missingness scenarios. We further demonstrated the application of the proposed models and methods via real data examples. We conclude that the negative binomial generalized linear mixed model (NB-GLMM) is superior overall for modeling count data characterized by overdispersion. Furthermore, a general threshold for relying on the simple Poisson model for cross-sectional and longitudinal datasets is in cases where σp \u3c=1.2. LTMI methods outperform CCA and LCMI in many scenarios, particularly when there is a higher percentage of missingness and data are MAR. Lastly, NBGLMM is preferable to address overdispersion while LTMI is preferable for imputing covariate observations when jointly considering both issues

Grade Distributions in the Basic Public Speaking Course: Exploring the Differences and Pedagogical Implications of Faculty Rank

This study examines differences in grade distributions in the introductory public speaking course at two American universities based on instructor rank. A sample of 442 sections with 11,381 students over a 2-year period was collected and analyzed using analysis of variance and chi-square analysis. We found significant differences in grade distributions, with instructors assigning lower grades overall than graduate teaching assistants (GTAs) and adjunct faculty. Instructors assigned significantly more D’s and F’s than tenure/track faculty, adjuncts, and GTAs. Chi-square analysis also revealed instructors and tenure/track faculty assign fewer A’s, but tenure/track faculty assign more B’s than the other faculty groups. The results point to pedagogic implications of maintaining a high number of adjuncts and GTAs in teaching the basic course. Implications of the study are discussed including ways to develop a more inclusive instructional community and culture for adjuncts through course standardization, mentoring, assessment, and technology use

Novel insights into the mechanisms of venous thrombosis

Venous thrombosis is a major health concern, with an annual incidence of ~1 per 1000 adults (Cushman 2007). This includes deep vein thrombosis (DVT) and pulmonary embolism (PE), the fatal consequence of a clot detaching and moving to the lungs, together these diseases are termed venous thromboembolism (VTE). Current treatment options for VTE are often associated with serious side effects and bleeding complications, highlighting the need for more effective prophylaxis. This study therefore aimed to identify new targets to treat DVT, which would not have the associated negative side effects. This study shows the platelet receptor CLEC-2 (C-type lectin receptor 2) plays an important role in DVT, probably through interaction with podoplanin in the IVC wall, and that lack of CLEC-2 is protective in this disease. We show other immune cells may also play a role in DVT, and demonstrate that mast cell deficiency is protective in vivo. Furthermore, we suggest that the mast cell constituent responsible for the prothrombotic phenotype is likely to be histamine. Preliminary data also suggests that T-cells may have a protective role in DVT, and that thrombin may be important for the release of neutrophil extracellular traps (NETs) from neutrophils inside a growing thrombus

Exile Vol. XXXVII No. 1

And It Was Sunday by Julie Gruen 1-6 Like a Lady by Grace Mulvihill 7 The Final You by Eric Franzon 8 Joseph\u27s Children by Seneca Murley 9 Ain\u27t the 1950s Anymore by Ellen Stader 10-12 Bonding Women by Shannon salser 13 Ice Man (for mami 1905-1975) by Anne Mulligan 14 The Car Salesman by Tom Ream 15 Cancelling the Bunny by Stewart Engesser 16-17 Richard Brautigan\u27s Body by Michael Payne 18-19 Dinner in Barcelona by Holly Kurtz 20 Untitled by Margaret Strachen 21 Candles by Eric Franzon 22 Summer Rules by Jim Cox 23-31 My Boat by Holly Kurtz 32 Untitled by Michael Payne 33 Half the Birds in the City by Tiffany Richardson 34-35 Down Queen Anne Hill by Julie Gruen 36-37 Your Music by Tim Emrick 38 Zephyrs by Steve Corinth 39-41 Mother by Anne Mulligan 42 As I Look to the Sky, Maize by Shannon Salser 43-45 Close Book before Striking by Sarah Verdon 46-47 Smoked by Tom Ream 48 Driving through Rain by Stewart Engesser 49-50 Contributors 51 Editorial decision is shared equally among the Editorial Board. -i 35th Yea

Red-Emitting Manganese-doped Aluminum Nitride Phosphor

We report high efficiency luminescence with a manganese-doped aluminum nitride red-emitting phosphor under 254 nm excitation, as well as its excellent lumen maintenance in fluorescent lamp conditions, making it a candidate replacement for the widely deployed europium-doped yttria red phosphor. Solid-state reaction of aluminum nitride powders with manganese metal at 1900 °C, 10 atm N2 in a reducing environment results in nitrogen deficiency, as revealed diffuse reflectance spectra. When these powders are subsequently annealed in flowing nitrogen at 1650 °C, higher nitrogen content is recovered, resulting in white powders. Silicon was added to samples as an oxygen getter to improve emission efficiency. NEXAFS spectra and DFT calculations indicate that the Mn dopant is divalent. From DFT calculations, the UV absorption band is proposed to be due to an aluminum vacancy coupled with oxygen impurity dopants, and Mn2+ is assumed to be closely associated with this site. In contrast with some previous reports, we find that the highest quantum efficiency with 254 nm excitation (Q.E. = 0.86 ± 0.14) is obtained in aluminum nitride with a low manganese doping level of 0.06 mol.%. The principal Mn2+ decay of 1.25 ms is assigned to non-interacting Mn sites, while additional components in the microsecond range appear with higher Mn doping, consistent with Mn clustering and resultant exchange coupling. Slower components are present in samples with low Mn doping, as well as strong afterglow, assigned to trapping on shallow traps followed by detrapping and subsequent trapping on Mn

Information-sharing with respite care services for older adults:a qualitative exploration of carers’ experiences

This study was financially supported by the Queen’s Nursing Institute Scotland (QNIS Project ELCRI01), Edinburgh, Scotland.Respite services play an important role in supporting older adults and their carers. When an older person is unable to fully represent themselves, provision of respite care relies on effective information-sharing between carers and respite staff. This study aimed to explore, from carers’ perspectives, the scope, quality and fit of information-sharing between carers, older people and respite services. An explorative, cross-sectional qualitative study involving a purposive sample of 24 carers, recruited via carer support groups and community groups in voluntary organisations, was undertaken in North East Scotland. Data were collected from August 2013 to September 2014, with participants taking part in a focus group or individual interview. Data were analysed systematically using the Framework Approach. The multiple accounts elicited from carers identified how barriers and facilitators to information-sharing with respite services changed over time across three temporal phases: ‘Reaching a point’, ‘Trying it out’ and ‘Settled in’. Proactive information-sharing about accessibility and eligibility for respite care, and assessment of carers’ needs in their own right, were initially important; as carers and older people moved on to try services out, time and space to develop mutual understandings and negotiate care arrangements came to the fore; then, once shared expectations had been established, carers’ chief concerns were around continuity of care and maintaining good interpersonal relationships. The three temporal phases also impacted on which modes of information-sharing were available to, and worked best for, carers as well as on carers’ perceptions of how information and communication technologies should be utilised. This study highlights the need for respite staff to take proactive, flexible approaches to working with carers and to make ongoing efforts to engage with carers, and older people, throughout the months and years of them utilising respite services. Information and communication technologies have potential to enhance information-sharing but traditional approaches will remain important.PostprintPeer reviewe

Enrollee Characteristics in an Intensive Tobacco Dependence Treatment Program: The Relationship of Race and Sex to Demographic Factors and Tobacco Use Patterns

Intensive tobacco treatment programs offer many advantages relative to other treatment options, particularly for more complex patients, e.g., highly nicotine dependent, or those with medical and psychiatric symptoms and disorders. Efforts to better understand those who choose to enroll in these programs, particularly regarding the characteristics they possess known to mediate outcomes, are important considerations in tailoring available services. In this study, we examined how participants differed on key descriptive and tobacco use variables within race (i.e., African-American, Caucasian) and sex subgroups. Baseline characteristics from a large group of consecutive program enrollees were examined across targeted subgroups. Strong racial effects and some sex effects were noted for marital status, education, employment and health insurance status, alcohol consumption, presence of medical and psychiatric disorders, as well as participant tobacco use patterns and tobacco use rates of family, friends and coworkers. The differences in participant tobacco use measures across race and sex factors remained significant after adjusting for the confounding effects of all other covariates. These findings have implications for characterizing key patient subgroups who present at tobacco treatment clinics. Such information may contribute to options for tailoring treatment regimens

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes