Statistics and Probability Commons^™

How To Combine Independent Data Sets For The Same Quantity, Theodore P. Hill, Jack Miller

Research Scholars in Residence

This paper describes a new mathematical method called conflation for consolidating data from independent experiments that measure the same physical quantity. Conflation is easy to calculate and visualize and minimizes the maximum loss in Shannon information in consolidating several independent distributions into a single distribution. A formal mathematical treatment of conflation has recently been published. For the benefit of experimenters wishing to use this technique, in this paper we derive the principal basic properties of conflation in the special case of normally distributed (Gaussian) data. Examples of applications to measurements of the fundamental physical constants and in high energy physics …

A Bayesian Model Averaging Approach For Observational Gene Expression Studies, Xi Kathy Zhou, Fei Liu, Andrew J. Dannenberg

COBRA Preprint Series

Identifying differentially expressed (DE) genes associated with a sample characteristic is the primary objective of many microarray studies. As more and more studies are carried out with observational rather than well controlled experimental samples, it becomes important to evaluate and properly control the impact of sample heterogeneity on DE gene finding. Typical methods for identifying DE genes require ranking all the genes according to a pre-selected statistic based on a single model for two or more group comparisons, with or without adjustment for other covariates. Such single model approaches unavoidably result in model misspecification, which can lead to increased error …

When Does Combining Markers Improve Classification Performance And What Are Implications For Practice?, Aasthaa Bansal, Margaret Sullivan Pepe

UW Biostatistics Working Paper Series

When an existing standard marker does not have sufficient classification accuracy on its own, new markers are sought with the goal of yielding a combination with better performance. The primary criterion for selecting new markers is that they have good performance on their own and preferably be uncorrelated with the standard. Most often linear combinations are considered. In this paper we investigate the increment in performance that is possible by combining a novel continuous marker with a moderately performing standard continuous marker under a variety of biologically motivated models for their joint distribution. We find that an uncorrelated continuous marker …

Hierarchical Probit Models For Ordinal Ratings Data, Allison M. Butler

Theses and Dissertations

University students often complete evaluations of their courses and instructors. The evaluation tool typically contains questions about the course and the instructor on an ordinal Likert scale. We assess instructor effectiveness while adjusting for known confounders. We present a probit regression model with a latent variable to measure the instructor effectiveness accounting for student specific covariates, such as student grade in the course, high school and university GPA, and ACT score.

Targeted Maximum Likelihood Estimation Of Conditional Relative Risk In A Semi-Parametric Regression Model, Cathy Tuglus, Kristin E. Porter, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

The conditional relative risk is an important measure in medical and epidemiological studies when the outcome of interest is binary (i.e. disease vs. no disease). When the outcome is common, estimation of conditional relative risk and related parameters can be problematic, especially when the exposure or covariates are continuous. We propose a new estimation procedure based on targeted maximum likelihood methodology that targets the parameters relating to the conditional relative risk for common outcomes under a log-linear, or multiplicative, semi-parametric model. In this paper, we present three possible targeted maximum likelihood estimators for relative risk parameters implied by such a …

Copy Number Variants In Candidate Genes Are Genetic Modifiers Of Hirschsprung Disease, Qian Jiang, Yen Yi Ho, Li Hao, Courtney Nichols Berrios, Aravinda Chakravarti

Faculty Publications

Hirschsprung disease (HSCR) is a neurocristopathy characterized by absence of intramural ganglion cells along variable lengths of the gastrointestinal tract. The HSCR phenotype is highly variable with respect to gender, length of aganglionosis, familiality and the presence of additional anomalies. By molecular genetic analysis, a minimum of 11 neuro-developmental genes (RET, GDNF, NRTN, SOX10, EDNRB, EDN3, ECE1, ZFHX1B, PHOX2B, KIAA1279, TCF4) are known to harbor rare, high-penetrance mutations that confer a large risk to the bearer. In addition, two other genes (RET, NRG1) harbor common, low-penetrance polymorphisms that contribute only partially to risk and can act as genetic modifiers. To …

Probabilistic Assessment Of Drought Characteristics Using A Hidden Markov Model, Ganeshchandra Mallya, Shivam Tripathi, Sergey Kirshner, Rao S. Govindaraju

2011 Symposium on Data-Driven Approaches to Droughts

Droughts are evaluated using drought indices that measure the departure of meteorological and hydrological variables such as precipitation and stream flow from their long-term averages. While there are many drought indices proposed in the literature, most of them use pre-defined thresholds for identifying drought classes ignoring the inherent uncertainties in characterizing droughts. In this study, a hidden Markov model (HMM) [1] is developed for probabilistic classification of drought states. The HMM captures space and time dependence in the data. The proposed model is applied to assess drought characteristics in Indiana using monthly precipitation and stream flow data. The comparison of …

Super Learner Based Conditional Density Estimation With Application To Marginal Structural Models, Ivan Diaz Munoz, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

In this paper we present a histogram-like estimator of a conditional density that uses super learner crossvalidation to estimate the histogram probabilities, as well as the optimal number and position of the bins. This estimator is an alternative to kernel density estimators when the dimension of the problem is large. We demonstrate its applicability to estimation of Marginal Structural Model (MSM) parameters in which an initial estimator of the treatment %mechanism is needed. MSM estimation based on the proposed density estimator results in less biased estimates, when compared to estimates based on a misspecified parametric model.

Comparing Roc Curves Derived From Regression Models, Venkatraman E. Seshan, Mithat Gonen, Colin B. Begg

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

In constructing predictive models, investigators frequently assess the incremental value of a predictive marker by comparing the ROC curve generated from the predictive model including the new marker with the ROC curve from the model excluding the new marker. Many commentators have noticed empirically that a test of the two ROC areas often produces a non-significant result when a corresponding Wald test from the underlying regression model is significant. A recent article showed using simulations that the widely-used ROC area test [1] produces exceptionally conservative test size and extremely low power [2]. In this article we show why the ROC …

On Causal Mediation Analysis With A Survival Outcome, Eric J. Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

Suppose that having established a marginal total effect of a point exposure on a time-to-event outcome, an investigator wishes to decompose this effect into its direct and indirect pathways, also know as natural direct and indirect effects, mediated by a variable known to occur after the exposure and prior to the outcome. This paper proposes a theory of estimation of natural direct and indirect effects in two important semiparametric models for a failure time outcome. The underlying survival model for the marginal total effect and thus for the direct and indirect effects, can either be a marginal structural Cox proportional …

Semiparametric Estimation Of Models For Natural Direct And Indirect Effects, Eric J. Tchetgen Tchetgen, Ilya Shpitser

Harvard University Biostatistics Working Paper Series

In recent years, researchers in the health and social sciences have become increasingly interested in mediation analysis. Specifically, upon establishing a non-null total effect of an exposure, investigators routinely wish to make inferences about the direct (indirect) pathway of the effect of the exposure not through (through) a mediator variable that occurs subsequently to the exposure and prior to the outcome. Natural direct and indirect effects are of particular interest as they generally combine to produce the total effect of the exposure and therefore provide insight on the mechanism by which it operates to produce the outcome. A semiparametric theory …

Semiparametric Theory For Causal Mediation Analysis: Efficiency Bounds, Multiple Robustness, And Sensitivity Analysis, Eric J. Tchetgen Tchetgen, Ilya Shpitser

Harvard University Biostatistics Working Paper Series

Whilst estimation of the marginal (total) causal effect of a point exposure on an outcome is arguably the most common objective of experimental and observational studies in the health and social sciences, in recent years, investigators have also become increasingly interested in mediation analysis. Specifically, upon establishing a non-null total effect of the exposure, investigators routinely wish to make inferences about the direct (indirect) pathway of the effect of the exposure not through (through) a mediator variable that occurs subsequently to the exposure and prior to the outcome. Although powerful semiparametric methodologies have been developed to analyze observational studies, that …

Component Extraction Of Complex Biomedical Signal And Performance Analysis Based On Different Algorithm, Hemant Pasusangai Kasturiwale

Johns Hopkins University, Dept. of Biostatistics Working Papers

Biomedical signals can arise from one or many sources including heart ,brains and endocrine systems. Multiple sources poses challenge to researchers which may have contaminated with artifacts and noise. The Biomedical time series signal are like electroencephalogram(EEG),electrocardiogram(ECG),etc The morphology of the cardiac signal is very important in most of diagnostics based on the ECG. The diagnosis of patient is based on visual observation of recorded ECG,EEG,etc, may not be accurate. To achieve better understanding , PCA (Principal Component Analysis) and ICA algorithms helps in analyzing ECG signals . The immense scope in the field of biomedical-signal processing Independent Component Analysis( …

Music And Radio Preferences On The Cal Poly Campus, Rory Bloch

Statistics

No abstract provided.

An Exploration Of Non-Detects In Environmental Data, Juliana Fajardo

Statistics

No abstract provided.

Analysis Of Roms Estimated Posterior Error Utilizing 4dvar Data Assimilation, Joseph Patrick Horton

Mathematics

The appropriateness of the approximate error calculated by the Regional Ocean Modeling System (ROMS) is analyzed using Four-Dimensional Data Assimilation (4DVAR) performed on a numerical model of the San Luis Obispo Bay. An effective method of sampling data to minimize the actual error associated with the assimilated numerical model is explored by using different data sampling methods. An idealized state of the SLO bay region ("Real Run") is created to be used as the real ocean, then a numerical model of this region is created approximating this Real Run; this is known as the "Simulated State". By taking samples from …

A Multivariate Variable Model With Possibility Of Missing Data On A Stochastic Process, Ehsan B. Samani

Applications and Applied Mathematics: An International Journal (AAM)

A joint model for multivariate responses with potentially non-random missing values on a stochastic process is proposed. A full likelihood-based approach that allows yielding maximum likelihood estimates of the model parameters is used. Sensitivity of the results to the assumptions is also investigated. A common way to investigate whether perturbations of model components influence key results of the analysis is to compare the results derived from the original and perturbed models using a general index of sensitivity (ISNI). The approach is illustrated by analyzing a finance data set.

Empirical Comparison Of Some Test Statistics For Testing The Mean Of A Poisson Distribution, B. M. Golam Kibria, Florence George

Applications and Applied Mathematics: An International Journal (AAM)

This paper considers the problem of hypotheses testing of the mean of a Poisson distribution. Accordingly we consider the following test statistics: Wald, WCC, Score (S), FT, VS, RVS, Exact and Bayes test statistics. A simulation study based on both one and two sided alternatives has been conducted to compare the performances of the test statistics. The study suggests that for a large sample size, all proposed test statistics except VCC and FT perform well in the sense of correct type I error rate of the test and power. However, for a small sample size, Score and VS have better …

Using Survival Analysis Methods To Study Santa Barbara County Divorces, Joel Vazquez

Statistics

No abstract provided.

Stock Market Reaction To Selected Macroeconomic Variables In The Nigerian Economy, Abraham Williams Terfa

CBN Journal of Applied Statistics (JAS)

This study examines the relationship between the stock market and selected macroeconomic variables in Nigeria. The all share index was used as a proxy for the stock market while inflation, interest and exchange rates were the macroeconomic variables selected. Employing error correction model, it was found that a significant negative short run relationship exists between the stock market and the minimum rediscounting rate (MRR) implying that, a decrease in the MRR, would improve the performance of the Nigerian stock market. It was also found that exchange rate stability in the long run, improves the performance of the stock market. Though …

Effects Of Global Climate Change On Nigerian Agriculture: An Empirical Analysis, Apata T. .G

CBN Journal of Applied Statistics (JAS)

This paper presents an empirical analysis of the effects of global warming on Nigerian agriculture and estimation of the determinants of adaptation to climate change. Data used for this study are from both secondary and primary sources. The set of secondary sources of data helped to examine the coverage of the three scenarios (1971-1980; 1981-1990 and 1991-2000). The primary data set consists of 900 respondents’ but only 850 cases were useful. This study analyzed determinants of farm-level climate adaptation measures using a Multinomial choice and stochastic-simulation model to investigate the effects of rapid climatic change on grain production and the …

Management And Support Of Shared Integrated Library Systems, Jason Vaughan, Kristen Costello

Library Faculty Research

The University of Nevada, Las Vegas (UNLV) University Libraries has hosted and managed a shared integrated library system (ILS) since 1989. The system and the number of partner libraries sharing the system has grown significantly over the past two decades. Spurred by the level of involvement and support contributed by the host institution, the authors administered a comprehensive survey to current Innovative Interfaces libraries. Research findings are combined with a description of UNLV’s local practices to provide substantial insights into shared funding, support, and management activities associated with shared systems.

Analysis Of The 2008 Flare Of Markarian 421 Flare With Veritas, Casey Allard

Physics

A theoretical light curve model is fit to an observed short term flare of Markarian (Mrk) 421 in the very high energy spectrum. The flare is characterized by its measured light curve from the Very Energetic Radiation Imaging telescope Array System (VERITAS). The flare we analyzed occurred in May 2008. We successfully fit a theoretical model to the Mrk 421 data light curve. The data appears to agree with the Wagner [1] and Salvati [2] models. These models appear to fit both broad and sharp flaring regions found in the measured light curve. Furthermore the Wagner model is used to …

The Utility Of Transient Sensitivity For Wildlife Management And Conservation: Bison As A Case Study, Michael Buhnerkempe, Nathanial Burch, Sarah J. Hamilton, Kerry M. Byrne, Eddie Childers, Kirstin A. Holfelder, Lindsay Mcmanus, Matthew I. Pyne, Greg Schroeder, Paul F. Doherty

Mathematics, Statistics and Computer Science Faculty Research and Publications

Developing effective management strategies is essential to conservation biology. Population models and sensitivity analyses on model parameters have provided a means to quantitatively compare different management strategies, allowing managers to objectively assess the resulting impacts. Inference from traditional sensitivity analyses (i.e., eigenvalue sensitivity methods) is only valid for a population at its stable age distribution, while more recent methods have relaxed this assumption and instead focused on transient population dynamics. However, very few case studies, especially in long-lived vertebrates where transient dynamics are potentially most relevant, have applied these transient sensitivity methods and compared them to eigenvalue sensitivity methods. We …

Stability And Change In Self-Reported Sexual Orientation Identity In Young People: Application Of Mobility Metrics, Miles Q. Ott, Heather L. Corliss, David Wypij, Margaret Rosario, S. Bryn Austin

Statistical and Data Sciences: Faculty Publications

This study investigated stability and change in self-reported sexual orientation identity over time in youth. We describe gender- and age-related changes in sexual orientation identity from early adolescence through emerging adulthood in 13,840 youth ages 12–25 employing mobility measure M, a measure we modified from its original application for econometrics. Using prospective data from a large, ongoing cohort of U.S. adolescents, we examined mobility in sexual orientation identity in youth with up to four waves of data. Ten percent of males and 20% of females at some point described themselves as a sexual minority, while 2% of both males and …

A Bayesian Approach To Missile Reliability, Taylor Hardison Redd

Theses and Dissertations

Each year, billions of dollars are spent on missiles and munitions by the United States government. It is therefore vital to have a dependable method to estimate the reliability of these missiles. It is important to take into account the age of the missile, the reliability of different components of the missile, and the impact of different launch phases on missile reliability. Additionally, it is of importance to estimate the missile performance under a variety of test conditions, or modalities. Bayesian logistic regression is utilized to accurately make these estimates. This project presents both previously proposed methods and ways to …

On Fractionally Integrated Logistic Smooth Transitions In Time Series, Olanrewaju I. Shittu, Yaya S. Olaolua

CBN Journal of Applied Statistics (JAS)

Long memory and nonlinearity are two key features of some macroeconomic time series which are characterized by persistent shocks that seem to rise faster during recession than it falls during expansion. A variant of nonlinear time series model together with long memory are used to examine these features in inflation series for three economies. The results which compares favourably with that of van Dijk et al. (2002) elicit some interesting attributes of inflation in the developed and developing economies.

Best Linear Unbiased Estimate Using Buys-Ballot Procedure When Trend-Cycle Component Is Linear, Ifeanyi S. Wueze, Nwogu C. Eleazar, Jude C. Ajaraogu

CBN Journal of Applied Statistics (JAS)

The Best linear unbiased estimate (BLUE) of Buys-Ballot estimates when trend-cycle component is linear are discussed in this paper. The estimates are those proposed by Iwueze and Nwogu (2004). Discussed are the Chain Based Estimation (CBE) method and the Fixed Based Estimation (FBE) method. The variates for the CBE method were found to have constant mean and variance but are correlated with only one significant autocorrelation coefficient at lag one. The variates for the FBE method were found to have constant mean, non-constant variance but with constant autocorrelation coefficient at all lags . Because the CBE variates exhibit stationarity, Best …

Global Financial Meltdown And The Reforms In The Nigerian Banking Sector, Sanusi L. Sanusi

CBN Journal of Applied Statistics (JAS)

The paper examined the global financial meltdown and the reforms in the Nigerian banking sector. It was a public speech by the formal Governor of the Central Bank of Nigeria that observed the extent and severity of the crisis that began with the bursting of the housing bubble in the United States in August 2007 reflects the confluence of myriad of factors some of which are familiar from previous crises, while others are new. As in previous times of financial turmoil, the pre-crisis period was characterized by (i) surging asset prices that proved unsustainable; (ii) a prolonged credit expansion leading …

Relationship Of Vitamin D Levels To Blood Pressure In A Biethnic Cohort, Rosario O. Sakamoto

Loma Linda University Electronic Theses, Dissertations & Projects

Background: Serum hydroxyvitamin D [25(OH)D] has been well-accepted as not an ordinary vitamin but a pro-hormone that has many benefits beyond its well-known effects on bone. Cardiovascular risk factors such as hypertension remain a huge health burden and Blacks have been recognized to have higher prevalence of hypertension compared to non-Hispanic Whites. Despite increasing evidence of the benefits of vitamin D on blood pressure control, there is much more to be learned about the relationship of serum 25(OH)D to blood pressure among different ethnicities.

Purpose: The goal of this study was to determine whether vitamin D serum 25(OH)D levels were …