Multivariate Analysis Commons^™

“Seeing” The Elephant: Assessing The Impact Of Library-Composition Program Collaboration On First-Year Student Learning, Erin E. Rinto

Presentations (Libraries)

Though university libraries and composition programs have historically collaborative relationships, these partnerships can take a variety of formats, including single course period library sessions, teaching-the-teachers, and librarian-driven assignment models. A hybrid of these collaborative approaches was implemented Fall 2012 at UNLV in an effort to provide first-year composition students with a more systematic information literacy experience in the required ENG 102 course. A two-pronged assessment method was used to evaluate the impact of the collaboration for both first-year student learning as well as to implement programmatic change.

Learning Outcomes For Library Student Workers, Jeanne M. Brown

Presentations (Libraries)

Our Dean of Libraries, Patty Iannuzzi has indicated that employment in the library can and should offer value to the student worker beyond convenience and flexible hours. In her words, "The libraries are well positioned to add value to our students' work experience in ways that can contribute to their academic success. As one of the largest employers of student workers on campus, we owe this to our students. As an organization, we want to clearly send a message that we care about them as students -- not just our employees." In Spring 2011, the Libraries partnered with Campus Life to ...

Quest For Continuous Improvement: Gathering Feedback And Data Through Multiple Methods To Evaluate And Improve A Library’S Discovery Tool, Jeanne M. Brown

Presentations (Libraries)

Summon at UNLV

• Implemented fall 2011: a web-scale discovery tool
• Expectations for Summon
• Continuous Summon Improvement (CSI)Group

The environment

• User changes
• Library changes
• Vendor changes
• Product changes
• Complex information environment
• Change + complexity = need to assess using multiple streams of feedback

A Bayesian Regression Tree Approach To Identify The Effect Of Nanoparticles Properties On Toxicity Profiles, Cecile Low-Kam, Haiyuan Zhang, Zhaoxia Ji, Tian Xia, Jeffrey I. Zinc, Andre Nel, Donatello Telesca

COBRA Preprint Series

We introduce a Bayesian multiple regression tree model to characterize relationships between physico-chemical properties of nanoparticles and their in-vitro toxicity over multiple doses and times of exposure. Unlike conventional models that rely on data summaries, our model solves the low sample size issue and avoids arbitrary loss of information by combining all measurements from a general exposure experiment across doses, times of exposure, and replicates. The proposed technique integrates Bayesian trees for modeling threshold effects and interactions, and penalized B-splines for dose and time-response surfaces smoothing. The resulting posterior distribution is sampled via a Markov Chain Monte Carlo algorithm. This ...

Global Quantitative Assessment Of The Colorectal Polyp Burden In, Patrick M. Lynch, Jeffrey S. Morris, William A. Ross, Miguel A. Rodriguez-Bigas, Juan Posadas, Rossa Khalaf, Diane M. Weber, Valerie O. Sepeda, Bernard Levin, Imad Shureiqi

Jeffrey S. Morris

Background: Accurate measures of the total polyp burden in familial adenomatous polyposis (FAP) are lacking. Current assessment tools include polyp quantitation in limited-field photographs and qualitative total colorectal polyp burden by video.

Objective: To develop global quantitative tools of the FAP colorectal adenoma burden.

Design: A single-arm, phase II trial.

Patients: Twenty-seven patients with FAP.

Intervention: Treatment with celecoxib for 6 months, with before-treatment and after-treatment videos posted to an intranet with an interactive site for scoring.

Main Outcome Measurements: Global adenoma counts and sizes (grouped into categories: less than 2 mm, 2-4 mm, and greater than 4 mm) were ...

The Growth Curve Model For High Dimensional Data And Its Application In Genomics, Sayantee Jana

Open Access Dissertations and Theses

Recent advances in technology have allowed researchers to collect high-dimensional biological data simultaneously. In genomic studies, for instance, measurements from tens of thousands of genes are taken from individuals across several experimental groups. In time course microarray experiments, gene expression is measured at several time points for each individual across the whole genome resulting in massive amount of data. In such experiments, researchers are faced with two types of high-dimensionality. The first is global high-dimensionality, which is common to all genomic experiments. The global high-dimensionality arises because inference is being done on tens of thousands of genes resulting in multiplicity ...

Mussel Survivorship, Growth Rate And Shell Decay Rate In The New River Basin Of Tennessee: An Experimental Approach Using Corbicula Fluminea, Grant Andrew Mincy

Masters Theses

The New River Basin (NRB) of Tennessee is home to a number of rare endemic aquatic communities. One such community of particular importance to the area, experiencing a precipitous population decline due to the fouling and pollution of their freshwater systems, is that of freshwater mussels (Bogan 2006). This study in the NRB involves measuring the mortality rates of live Asian clams (Corbicula fluminea) assemblages and the shell decay rates of their death assemblages. This study also examines the decay rates of the native Villosa iris to gather information on molluscan health and the ability of their shells to be ...

Spectral Cross Correlation As A Supervised Approach For The Analysis Of Complex Raman Datasets: The Case Of Nanoparticles In Biological Cells, Mark E. Keating, Franck Bonnier, Hugh Byrne

Articles

Spectral Cross-correlation is introduced as a methodology to identify the presence and subcellular distribution of nanoparticles in cells. Raman microscopy is employed to spectroscopically image biological cells previously exposed to polystyrene nanoparticles, as a model for the study of nano-bio interactions. The limitations of previously deployed strategies of K-means clustering analysis and principal component analysis are discussed and a novel methodology of Spectral Cross Correlation Analysis is introduced and compared with the performance of Classical Least Squares Analysis, in both unsupervised and supervised modes. The previous study demonstrated the feasibility of using Raman spectroscopy to map cells and identify polystyrene ...

Analysis Of Dietary Patterns Over Freshman Year Of College, Chelsea Lofland

Statistics

This analysis is an investigation of changes in Cal Poly students’ eating habits over freshman year. The motivation behind this was an interest in college students’ lifestyles; college is the first time most students live on their own and it can be an important maturation period. College is stressful, exciting, liberating, and terrifying all at the same time. This distinctive life experience, along with my desire to handle big and messy data, led me to this research question.

The response variable analyzed was food consumption and the explanatory variables were: sex, race, quarter, food group, stress, exercise, BMI, sleep quality ...

Blunt Impact Performance Evaluation Of Helmet Lining Systems For Military And Recreational Use, Jaclyn Siniora, Ryan Taylor, Darren Suey

Industrial Technology

With the increasing problem in collegiate athletes experiencing injuries to the brain, different helmet liners where put to the test to see which liner provided athletes the greatest protection under specific conditions.

This senior project evaluates five different liners in football helmets. Each of the helmet liners were tested at three different temperatures: hot, cold, and ambient. Each helmet had seven different impact locations which were put to the test. The project was designed to be used to test ACH military combat liners as well. Due to shipping bottle necks the ACH combat liners have been left to future Cal ...

Sparse Principal Component Analysis For High-Dimensional Data: A Comparative Study, Ashley J. Bonner

Open Access Dissertations and Theses

Background: Through unprecedented advances in technology, high-dimensional datasets have exploded into many fields of observational research. For example, it is now common to expect thousands or millions of genetic variables (p) with only a limited number of study participants (n). Determining the important features proves statistically difficult, as multivariate analysis techniques become flooded and mathematically insufficient when n < p. Principal Component Analysis (PCA) is a commonly used multivariate method for dimension reduction and data visualization but suffers from these issues. A collection of Sparse PCA methods have been proposed to counter these flaws but have not been tested in comparative detail. Methods: Performances of three Sparse PCA methods were evaluated through simulations. Data was generated for 56 different data-structures, ranging p, the number of underlying groups and the variance structure within them. Estimation and interpretability of the principal components (PCs) were rigorously tested ...