Penalized Nonparametric Scalar-On-Function Regression Via Principal Coordinates, 2016 New York University School of Medicine

#### Penalized Nonparametric Scalar-On-Function Regression Via Principal Coordinates, Philip T. Reiss, David L. Miller, Pei-Shien Wu, Wen-Yu Hua

*Philip T. Reiss*

Multilevel Models For Longitudinal Data, 2016 East Tennessee State University

#### Multilevel Models For Longitudinal Data, Aastha Khatiwada

*Electronic Theses and Dissertations*

Longitudinal data arise when individuals are measured several times during an ob- servation period and thus the data for each individual are not independent. There are several ways of analyzing longitudinal data when different treatments are com- pared. Multilevel models are used to analyze data that are clustered in some way. In this work, multilevel models are used to analyze longitudinal data from a case study. Results from other more commonly used methods are compared to multilevel models. Also, comparison in output between two software, SAS and R, is done. Finally a method consisting of fitting individual models for each ...

The Influence Of The Electric Supply Industry On Economic Growth In Less Developed Countries, 2016 University of Southern Mississippi

#### The Influence Of The Electric Supply Industry On Economic Growth In Less Developed Countries, Edward Richard Bee

*Dissertations*

This study measures the impact that electrical outages have on manufacturing production in 135 less developed countries using stochastic frontier analysis and data from World Bank’s Investment Climate surveys. Outages of electricity, for firms with and without backup power sources, are the most frequently cited constraint on manufacturing growth in these surveys.

Outages are shown to reduce output below the production frontier by almost five percent in Africa and by a lower percentage in South Asia, Southeast Asia and the Middle East and North Africa. Production response to outages is quadratic in form. Outages also increase labor cost, reduce ...

Using A Data Quality Framework To Clean Data Extracted From The Electronic Health Record: A Case Study., 2016 University of Colorado, College of Nursing, Anschutz Medical Campus

#### Using A Data Quality Framework To Clean Data Extracted From The Electronic Health Record: A Case Study., Oliwier Dziadkowiec, Tiffany Callahan, Mustafa Ozkaynak, Blaine Reeder, John Welton

*eGEMs (Generating Evidence & Methods to improve patient outcomes)*

**Objectives**: Examine (1) the appropriateness of using a data quality (DQ) framework developed for relational databases as a data-cleaning tool for a dataset extracted from two EPIC databases; and (2) the differences in statistical parameter estimates on a dataset cleaned with the DQ framework and dataset not cleaned with the DQ framework.

**Background:** The use of data contained within electronic health records (EHRs) has the potential to open doors for a new wave of innovative research. Without adequate preparation of such large datasets for analysis, the results might be erroneous, which might affect clinical decision making or results of Comparative ...

The Engineering Admissions Partnership Program: A Navigation Strategy For Community College Students Seeking A Pathway Into Engineering, 2016 University of Iowa

#### The Engineering Admissions Partnership Program: A Navigation Strategy For Community College Students Seeking A Pathway Into Engineering, Marcia R. Laugerman, Mack C. Shelley, Steven K. Mickelson, Diane T. Rover

*Steven K. Mickelson*

This paper presents the evaluation of a program designed to improve transfer outcomes for community college students pursuing an engineering degree. The program, the Engineering Admissions Partnership Program (E-APP), was designed to improve the navigational success of community college transfer students through connections to the university. These connections include coordinated academic advising, peer-mentoring, campus visits, and online social and professional networks. The objective of the study is to determine the efficacy of the E-APP and its interventions, which will be measured by increased participation rates and increased university retention rates for E-APP participants. Outcome data for the students are analyzed ...

Failure Of Surface Color Cues Under Natural Changes In Lighting, 2016 University of Manchester

#### Failure Of Surface Color Cues Under Natural Changes In Lighting, David H. Foster, Iván Marín-Franch

*MODVIS Workshop*

Color allows us to effortlessly discriminate and identify surfaces and objects by their reflected light. Although the reflected spectrum changes with the illumination spectrum, cone photoreceptor signals can be transformed to give useful cues for surface color. But what happens when both the spectrum and the geometry of the illumination change, as with lighting from the sun and sky? Is it possible, as a matter of principle, to obtain reliable cues by processing cone signals alone? This question was addressed here by estimating the information provided by cone signals from time-lapse hyperspectral radiance images of five outdoor scenes under natural ...

Automated Sea State Classification From Parameterization Of Survey Observations And Wave-Generated Displacement Data, 2016 University of New Orleans, New Orleans

#### Automated Sea State Classification From Parameterization Of Survey Observations And Wave-Generated Displacement Data, Jason A. Teichman

*University of New Orleans Theses and Dissertations*

Sea state is a subjective quantity whose accuracy depends on an observer’s ability to translate local wind waves into numerical scales. It provides an analytical tool for estimating the impact of the sea on data quality and operational safety. Tasks dependent on the characteristics of local sea surface conditions often require accurate and immediate assessment. An attempt to automate sea state classification using eleven years of ship motion and sea state observation data is made using parametric modeling of distribution-based confidence and tolerance intervals and a probabilistic model using sea state frequencies. Models utilizing distribution intervals are not able ...

Nine Pseudo R^2 Indices For Binary Logistic Regression Models, 2016 Northern Illinois University

#### Nine Pseudo R^2 Indices For Binary Logistic Regression Models, David A. Walker, Thomas J. Smith

*Journal of Modern Applied Statistical Methods*

This syntax program is an applied complement to Veall and Zimmermann (1994), Menard (2000), and Smith and McKenna (2013) and produces nine pseudo *R*^{2} indices, not readily accessible in statistical software such as SPSS, which are used to describe the results from binary logistic regression analyses.

A Percentile-Based Power Method In Sas: Simulating Multivariate Non-Normal Continuous Distributions, 2016 Southern Illinois University Carbondale

#### A Percentile-Based Power Method In Sas: Simulating Multivariate Non-Normal Continuous Distributions, Jennifer Koran, Todd C. Headrick

*Journal of Modern Applied Statistical Methods*

The conventional power method transformation is a moment-matching technique that simulates non-normal distributions with controlled measures of skew and kurtosis. The percentile-based power method is an alternative that uses the percentiles of a distribution in lieu of moments. This article presents a SAS/IML macro that implements the percentile-based power method.

An Evaluation Of Pareto, Lognormal And Pps Distributions: The Size Distribution Of Cities In Kerala, India, 2016 S.R.M. Medical College and Research Centre, Kattankulathur, India

#### An Evaluation Of Pareto, Lognormal And Pps Distributions: The Size Distribution Of Cities In Kerala, India, Christopher A. Vallabados, Subbarayan A. Arumugam

*Journal of Modern Applied Statistical Methods*

The Pareto-Positive Stable (PPS) distribution is introduced as a new model for describing city size data of a region in a country. The PPS distribution provides a flexible model for fitting the entire range of a set of city size data and the classical Pareto and Zipf distributions are included as a particular case.

Simple Response Surface Methodology Using Rsreg (Sas), 2016 University Science Malaysia

#### Simple Response Surface Methodology Using Rsreg (Sas), Wan Muhamad Amir, Mohamad Shafiq, Kasypi Mokhtar, Nor Azlida Aleng, Hanafi A.Rahim, Zalila Ali

*Journal of Modern Applied Statistical Methods*

Response surface methodology (RSM) can be used when the response variable, *y*, is influenced by several variables, *x*’s. When treatments take the form of quantitative values, then the true relationship between response variables and independent variables might be known. Examples are given in SAS.

Confidence Intervals For Kendall's Tau With Small Samples, 2016 Northern Illinois University

#### Confidence Intervals For Kendall's Tau With Small Samples, David A. Walker

*Journal of Modern Applied Statistical Methods*

A syntax program, not readily expedient in statistical software such as SPSS, is provided for an application of confidence interval estimates with Kendall’s tau-b for small samples.

Generalized Linear Model Analyses For Treatment Group Equality When Data Are Non-Normal, 2016 University of Manitoba

#### Generalized Linear Model Analyses For Treatment Group Equality When Data Are Non-Normal, Harvey J. Kesleman, Abdul R. Othman, Rand R. Wilcox

*Journal of Modern Applied Statistical Methods*

One of the validity conditions of classical test statistics (e.g., Student’s *t*-test, the ANOVA and MANOVA *F*-tests) is that data be normally distributed in the populations. When this and/or other derivational assumptions do not hold the classical test statistic can be prone to too many Type I errors (i.e., falsely rejecting too often) and/or have low power (i.e., failing to reject when the null hypothesis is false) to detect treatment effects when they are present. However, alternative procedures are available for assessing equality of treatment group effects when data are non-normal. For ...

Construction Of Pair-Wise Balanced Design, 2016 Manonmaniam Sundaranar University

#### Construction Of Pair-Wise Balanced Design, Rajarathinam Arunachalam, Mahalakshmi Sivasubramanian, Dilip Kumar Ghosh

*Journal of Modern Applied Statistical Methods*

A new procedure for construction of pair wise balanced design with equal replication and un-equal block sizes based on factorial design have been evolved. Numerical illustration also provided. It was found that the constructed pair wise balanced design was found to be universal optimal.

Bayesian Estimation Of P[Y < X] Based On Record Values From The Lomax Distribution And Mcmc Technique, 2016 Al-Azhar University, Cairo, Egypt

#### Bayesian Estimation Of P[Y < X] Based On Record Values From The Lomax Distribution And Mcmc Technique, Mohamed A. W Mahmoud, Rashad M. El-Sagheer, Ahmed A. Soliman, Ahmed H. Abd Ellah

*Journal of Modern Applied Statistical Methods*

Our interest is in estimating the stress-strength reliability *R* = P[*Y* < *X*], where* X* and *Y* follow the Lomax distribution with common scale parameter. We discuss the problem in the situation where the stress measurements and the strength measurements are both in terms of records. Firstly, we obtain the MLE of *R* in general case (the common scale parameter is unknown). The MLE of the three unknown parameters can be obtained by solving one non-linear equation. We provide a simple fixed point type algorithm to find the MLE. We propose percentile bootstrap confidence intervals of R. A Bayes point estimator ...

Factorial Invariance Testing Under Different Levels Of Partial Loading Invariance Within A Multiple Group Confirmatory Factor Analysis Model, 2016 washington State University

#### Factorial Invariance Testing Under Different Levels Of Partial Loading Invariance Within A Multiple Group Confirmatory Factor Analysis Model, Brian F. French, Holmes Finch

*Journal of Modern Applied Statistical Methods*

Scalar invariance in factor models is important for comparing latent means. Little work has focused on invariance testing for other model parameters under various conditions. This simulation study assesses how partial factorial invariance influences invariance testing for model parameters. Type I error inflation and parameter bias were observed.

A Comparison Of Estimation Methods For Nonlinear Mixed-Effects Models Under Model Misspecification And Data Sparseness: A Simulation Study, 2016 University of Maryland

#### A Comparison Of Estimation Methods For Nonlinear Mixed-Effects Models Under Model Misspecification And Data Sparseness: A Simulation Study, Jeffrey R. Harring, Junhui Liu

*Journal of Modern Applied Statistical Methods*

A Monte Carlo simulation is employed to investigate the performance of five estimation methods of nonlinear mixed effects models in terms of parameter recovery and efficiency of both regression coefficients and variance/covariance parameters under varying levels of data sparseness and model misspecification.

A Spatial Analytical Framework For Examining Road Traffic Crashes, 2016 UNIVERSITY OF IBADAN

#### A Spatial Analytical Framework For Examining Road Traffic Crashes, Grace O. Korter

*Journal of Modern Applied Statistical Methods*

A number of different modeling techniques have been used to examine road traffic crashes for analytic and predictive purposes. Map-based spatial analysis** **is introduced. Applications are given which show the power in a combination of existing exploratory and statistical methods.

Generalized Singular Value Decomposition With Additive Components, 2016 GfK

#### Generalized Singular Value Decomposition With Additive Components, Stan Lipovetsky

*Journal of Modern Applied Statistical Methods*

The singular value decomposition (SVD) technique is extended to incorporate the additive components for approximation of a rectangular matrix by the outer products of vectors. While dual vectors of the regular SVD can be expressed one via linear transformation of the other, the modified SVD corresponds to the general linear transformation with the additive part. The method obtained can be related to the family of principal component and correspondence analyses, and can be reduced to an eigenproblem of a specific transformation of a data matrix. This technique is applied to constructing dual eigenvectors for data visualizing in a two dimensional ...

Almost Unbiased Estimator Using Known Value Of Population Parameter(S) In Sample Surveys, 2016 Department of Statistics, Banaras Hindu University Varanasi

#### Almost Unbiased Estimator Using Known Value Of Population Parameter(S) In Sample Surveys, Rajesh Singh, S.B. Gupta, Sachin Malik

*Journal of Modern Applied Statistical Methods*

An almost unbiased estimator using known value of some population parameter(s) is proposed. A class of estimators is defined which includes Singh and Solanki (2012) and Sahai and Ray (1980), Sisodiya and Dwivedi (1981), Singh, Cauhan, Sawan, and Smarandache (2007), Upadhyaya and Singh (1984), Singh and Tailor (2003) estimators. Under simple random sampling without replacement (SRSWOR) scheme the expressions for bias and mean square error (MSE) are derived. Numerical illustrations are given.