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Resolving The Issue Of How Reliability Is Related To Statistical Power: Adhering To Mathematical Definitions, Donald W. Zimmerman, Bruno D. Zumbo

Journal of Modern Applied Statistical Methods

Reliability in classical test theory is a population-dependent concept, defined as a ratio of true-score variance and observed-score variance, where observed-score variance is a sum of true and error components. On the other hand, the power of a statistical significance test is a function of the total variance, irrespective of its decomposition into true and error components. For that reason, the reliability of a dependent variable is a function of the ratio of true-score variance and observed-score variance, whereas statistical power is a function of the sum of the same two variances. Controversies about how reliability is related to statistical …

In (Partial) Defense Of .05, Thomas R. Knapp

Journal of Modern Applied Statistical Methods

Researchers are frequently chided for choosing the .05 alpha level as the determiner of statistical significance (or non-significance). A partial justification is provided.

Vol. 14, No. 2 (Full Issue), Jmasm Editors

Journal of Modern Applied Statistical Methods

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Semi-Parametric Non-Proportional Hazard Model With Time Varying Covariate, Kazeem A. Adeleke, Alfred A. Abiodun, R. A. Ipinyomi

Journal of Modern Applied Statistical Methods

The application of survival analysis has extended the importance of statistical methods for time to event data that incorporate time dependent covariates. The Cox proportional hazards model is one such method that is widely used. An extension of the Cox model with time-dependent covariates was adopted when proportionality assumption are violated. The purpose of this study is to validate the model assumption when hazard rate varies with time. This approach is applied to model data on duration of infertility subject to time varying covariate. Validity is assessed by a set of simulation experiments and results indicate that a non proportional …

Bayesian Analysis Under Progressively Censored Rayleigh Data, Gyan Prakash

Journal of Modern Applied Statistical Methods

The one-parameter Rayleigh model is considered as an underlying model for evaluating the properties of Bayes estimator under Progressive Type-II right censored data. The One‑Sample Bayes prediction bound length (OSBPBL) is also measured. Based on two different asymmetric loss functions a comparative study presented for Bayes estimation. A simulation study was used to evaluate their comparative properties.

Statistical Modeling Of Migration Attractiveness Of The Eu Member States, Tatiana Tikhomirova, Yulia Lebedeva

Journal of Modern Applied Statistical Methods

Identifying the relationship between the migration attractiveness of the European Union countries and their level of socio-economic development is investigated. An approach is proposed identify influences on migration socio-economic characteristics, by aggregating and reducing their diversity, and substantiating the cause-and-effect relationships of the studied phenomenon. A stable classification of countries scheme is developed according to the attractiveness of migration on aggregate factors, and then an econometric model of a binary choice using panel data for 2008-2010 was applying, quantifying the impact of aggregate designed factors on immigration and emigration.

Audiovisual Processing Is Abnormal In Parkinson's Disease And Correlates With Freezing Of Gait And Disease Duration, Conor Fearon, John Butler, Louise Newman, Timothy Lynch, Richard B. Reilly

Articles

Background: Sensory and perceptual disturbances progress with disease duration in Parkinson’s disease (PD) and probably contribute to motor deficits such as bradykinesia and gait disturbances, including freezing of gait (FOG). Simple reaction time tests are ideal to explore sensory processing, as they require little cognitive processing. Multisensory integration is the ability of the brain to integrate sensory information from multiple modalities into a single coherent percept, which is crucial for complex motor tasks such as gait. 9 10 11 12 13 Objectives: The aims of this study were to: 1. Assess differences in unisensory (auditory and visual) and multisensory processing …

Peritumoral Tissue Compression Is Predictive Of Exudate Flux In A Rat Model Of Cerebral Tumor: An Mri Study In An Embedded Tumor, James R. Ewing, Tavarekere N. Nagaraja, Madhava P. Aryal, Kelly A. Keenan, Rasha Elmghirbi, Hassan Bagher-Ebadian, Swayamprava Panda, Mei Lu, Tom Mikkelsen, Glauber Cabral, Stephen L. Brown

Neurology Articles

MRI estimates of extracellular volume and tumor exudate flux in peritumoral tissue are demonstrated in an experimental model of cerebral tumor. Peritumoral extracellular volume predicted the tumor exudate flux. Eighteen RNU athymic rats were inoculated intracerebrally with U251MG tumor cells and studied with dynamic contrast enhanced MRI (DCE-MRI) approximately 18 days post implantation. Using a model selection paradigm and a novel application of Patlak and Logan plots to DCE-MRI data, the distribution volume (i.e. tissue porosity) in the leaky rim of the tumor and that in the tissue external to the rim (the outer rim) were estimated, as was the …

Challenges In Analyzing Software Documentation In Portuguese, Christoph Treude, Carlos A. Prolo, Fernando Figueira Filho

Research Collection School Of Computing and Information Systems

Many tools that automatically analyze, summarize, or transform software artifacts rely on natural language processing tooling for the interpretation of natural language text produced by software developers, such as documentation, code comments, commit messages, or bug reports. Processing natural language text produced by software developers is challenging because of unique characteristics not found in other texts, such as the presence of code terms and the systematic use of incomplete sentences. In addition, texts produced by Portuguese-speaking developers mix languages since many keywords and programming concepts are referred to by their English name. In this paper, we provide empirical insights into …

Lesinn: Detecting Anomalies By Identifying Least Similar Nearest Neighbours, Guansong Pang, Kai Ming Ting, David Albrecht

Research Collection School Of Computing and Information Systems

We introduce the concept of Least Similar Nearest Neighbours (LeSiNN) and use LeSiNN to detect anomalies directly. Although there is an existing method which is a special case of LeSiNN, this paper is the first to clearly articulate the underlying concept, as far as we know. LeSiNN is the first ensemble method which works well with models trained using samples of one instance. LeSiNN has linear time complexity with respect to data size and the number of dimensions, and it is one of the few anomaly detectors which can apply directly to both numeric and categorical data sets. Our extensive …

Whom Should We Sense In 'Social Sensing' - Analyzing Which Users Work Best For Social Media Now-Casting, Jisun An, Ingmar Weber

Research Collection School Of Computing and Information Systems

Given the ever increasing amount of publicly available social media data, there is growing interest in using online data to study and quantify phenomena in the offline 'real' world. As social media data can be obtained in near real-time and at low cost, it is often used for 'now-casting' indices such as levels of flu activity or unemployment. The term 'social sensing' is often used in this context to describe the idea that users act as 'sensors', publicly reporting their health status or job losses. Sensor activity during a time period is then typically aggregated in a 'one tweet, one …

Powerforecaster: Predicting Smartphone Power Impact Of Continuous Sensing Applications At Pre-Installation Time, Chulhong Min, Youngki Lee, Chungkuk Yoo, Seungwoo Kang, Sangwon Choi, Pillsoon Park, Inseok Hwang, Younghyun Ju, Seungpyo Choi, Junehwa Song

Research Collection School Of Computing and Information Systems

Today's smartphone application (hereinafter 'app') markets miss a key piece of information, power consumption of apps. This causes a severe problem for continuous sensing apps as they consume significant power without users' awareness. Users have no choice but to repeatedly install one app after another and experience their power use. To break such an exhaustive cycle, we propose PowerForecaster, a system that provides users with power use of sensing apps at pre-installation time. Such advanced power estimation is extremely challenging since the power cost of a sensing app largely varies with users' physical activities and phone use patterns. We observe …

Dictionary Pair Learning On Grassmann Manifolds For Image Denoising, Xianhua Zeng, Wei Bian, Wei Liu, Jialie Shen, Dacheng Tao

Research Collection School Of Computing and Information Systems

Image denoising is a fundamental problem in computer vision and image processing that holds considerable practical importance for real-world applications. The traditional patch-based and sparse coding-driven image denoising methods convert 2D image patches into 1D vectors for further processing. Thus, these methods inevitably break down the inherent 2D geometric structure of natural images. To overcome this limitation pertaining to the previous image denoising methods, we propose a 2D image denoising model, namely, the dictionary pair learning (DPL) model, and we design a corresponding algorithm called the DPL on the Grassmann-manifold (DPLG) algorithm. The DPLG algorithm first learns an initial dictionary …

Where Are The Passengers? A Grid-Based Gaussian Mixture Model For Taxi Bookings, Meng-Fen Chiang, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Taxi bookings are events where requests for taxis are made by passengers either over voice calls or mobile apps. As the demand for taxis changes with space and time, it is important to model both the space and temporal dimensions in dynamic booking data. Several applications can benefit from a good taxi booking model. These include the prediction of number of bookings at certain location and time of the day, and the detection of anomalous booking events. In this paper, we propose a Grid-based Gaussian Mixture Model (GGMM) with spatio-temporal dimensions that groups booking data into a number of spatio-temporal …

Intelligshop: Enabling Intelligent Shopping In Malls Through Location-Based Augmented Reality, Aditi Adhikari, Vincent W. Zheng, Hong Cao, Miao Lin, Yuan Fang, Kevin Chen-Chuan Chang

Research Collection School Of Computing and Information Systems

Shopping experience is important for both citizens and tourists. We present IntelligShop, a novel location-based augmented reality application that supports intelligent shopping experience in malls. As the key functionality, IntelligShop provides an augmented reality interface-people can simply use ubiquitous smartphones to face mall retailers, then IntelligShop will automatically recognize the retailers and fetch their online reviews from various sources (including blogs, forums and publicly accessible social media) to display on the phones. Technically, IntelligShop addresses two challenging data mining problems, including robust feature learning to support heterogeneous smartphones in localization and learning to query for automatically gathering the retailer content …

Codehow: Effective Code Search Based On Api Understanding And Extended Boolean Model (E), Fei Lv, Jian-Guang Lou, Shaowei Wang, Dongmei Zhang, Jainjun Zhao

Research Collection School Of Computing and Information Systems

Over the years of software development, a vast amount of source code has been accumulated. Many code search tools were proposed to help programmers reuse previously-written code by performing free-text queries over a large-scale codebase. Our experience shows that the accuracy of these code search tools are often unsatisfactory. One major reason is that existing tools lack of query understanding ability. In this paper, we propose CodeHow, a code search technique that can recognize potential APIs a user query refers to. Having understood the potentially relevant APIs, CodeHow expands the query with the APIs and performs code retrieval by applying …

Qualitative Phenomenological Study Exploring Instructional Practices That Contribute To Academic Success For Public Elementary School English Language Learners, Mechelle Champion

Doctoral Dissertations and Projects

The purpose of this transcendental phenomenological study was to explore effective instructional strategies of mainstream classroom teachers working with English Language Learners (ELLs). Many teachers feel unprepared to adequately educate English Language Learners. School systems have attempted to rectify this situation by providing teachers with professional development that provides instructional strategies which may or may not be effective. This study answered the questions: What teaching strategies do teachers and administrators perceive to have the most positive impact on learning for ELLs?; How does the culture of the classroom and school impact ELLs’ academic success?; and What are building level administrators’ …

An Exploration Of The Implementation Of Continuous Assessment In Mathemetics Education At Primary Teachers’ Colleges In Uganda, Kirabo Esther

Master of Education

Improvement in the teaching and learning process for the benefit of both teachers and students is always at the centre of continuous assessment. It therefore follows from this view that continuous assessment in particular has been hailed to de-emphasize the hitherto terminal assessment because of various advantages it has over terminal assessment (Brown, 2004; Webb & Jones, 2009). This study was designed to explore the progress of the implementation of continuous assessment in mathematics education at Primary Teachers’ Colleges in Uganda, a component explicitly introduced in the curriculum and assessment since 2012. The study was conducted in a public Primary …

Expected Occupation Growth In El Paso And Doña Ana Counties, Manuel Reyes-Loya, Jesus Mendoza, Hunt Institute For Global Competitiveness

Technical Reports

No abstract provided.

The Distribution Of The Inverse Square Root Transformed Error Component Of The Multiplicative Time Series Model, Bright F. Ajibade, Chinwe R. Nwosu, J. I. Mbegdu

Journal of Modern Applied Statistical Methods

The probability density function, mean and variance of the inverse square-root transformed left-truncated N(1,σ²) error component e^*_t(=1/ √e_t) of the multiplicative time series model were established. A comparison of key-statistical properties of e^*_t and e_t confirmed normality with mean 1 but with Var(e^*_t) ≈1/4Var(e_t) when σ≤0.14. Hence σ≤0.14 is the required condition for successful transformation.

Approaches For Detection Of Unstable Processes: A Comparative Study, Yerriswamy Wooluru, D. R. Swamy, P. Nagesh

Journal of Modern Applied Statistical Methods

A process is stable only when parameters of the distribution of a process or product characteristic remain same over time. Only a stable process has the ability to perform in a predictable manner over time. Statistical analysis of process data usually assume that data are obtained from stable process. In the absence of control charts, the hypothesis of process stability is usually assessed by visual examination of the pattern in the run chart. In this paper appropriate statistical approaches have been adopted to detect instability in the process and compared their performance with the run chart of considerably shorter length …

A Robust Panel Unit Root Test In The Presence Of Cross Sectional Dependence, Nurul Sima Mohamad Shariff, Nor Aishah Hamzah

Journal of Modern Applied Statistical Methods

Problems arise in testing the stationarity of the panel in the presence of cross sectional dependence and outliers. The currently available panel unit root tests are very much affected by the presence of outliers. As such, this article introduces an alternative test which is robust to outliers and cross sectional dependence. The performance and robustness of the proposed test is discussed and comparisons are made to the existing tests via simulation studies.

Detection Of Acute Nervous System Injury With Advanced Diffusion-Weighted Mri: A Simulation And Sensitivity Analysis, Nathan P. Skinner, Shekar N. Kurpad, Brian D. Schmit, Matthew D. Budde

Biomedical Engineering Faculty Research and Publications

Diffusion-weighted imaging (DWI) is a powerful tool to investigate the microscopic structure of the central nervous system (CNS). Diffusion tensor imaging (DTI), a common model of the DWI signal, has a demonstrated sensitivity to detect microscopic changes as a result of injury or disease. However, DTI and other similar models have inherent limitations that reduce their specificity for certain pathological features, particularly in tissues with complex fiber arrangements. Methods such as double pulsed field gradient (dPFG) and q-vector magic angle spinning (qMAS) have been proposed to specifically probe the underlying microscopic anisotropy without interference from the macroscopic tissue organization. …

New Transitions And Feeding Of The JΠ=(8+) Isomer In 186Re, David A. Matters, Nikolaos Fotiades, James J. Carroll, Christopher J. Chiara, John W. Mcclory, Toshihiko Kawano, Ronald O. Nelson, Matthew Devlin

Faculty Publications

The spallation neutron source at the Los Alamos Neutron Science Center Weapons Neutron Research facility was used to populate excited states in ¹⁸⁶Re via (n,2nγ) reactions on an enriched ¹⁸⁷Re target. Gamma rays were detected with the GErmanium Array for Neutron Induced Excitations spectrometer, a Compton-suppressed array of 18 HPGe detectors. Incident neutron energies were determined by the time-of-flight technique and used to obtain γ-ray excitation functions for the purpose of identifying γ rays by reaction channel. Analysis of the singles γ-ray spectrum gated on the neutron energy range 10≤E_n≤25MeV resulted in five transitions and one …

A Catalog Of Visual-Like Morphologies In The 5 Candels Fields Using Deep Learning, M. Huertas-Company, R. Gravet, G. Cabrera-Vives, Pablo G. Pérez-González, J. Kartaltepe, Guillermo Barro, M. Bernardi, S. Mei, F. Shankar, P. Dimauro, E. F. Bell, Dale D. Kocevski, David C. Koo, Sandra M. Faber, Daniel H. Mcintosh

Physics and Astronomy Faculty Publications

We present a catalog of visual-like H-band morphologies of ~50.000 galaxies (H_f160w < 24.5) in the 5 CANDELS fields (GOODS-N, GOODS-S, UDS, EGS, and COSMOS). Morphologies are estimated using Convolutional Neural Networks (ConvNets). The median redshift of the sample is 〈z〉 ~ 1.25. The algorithm is trained on GOODS-S, for which visual classifications are publicly available, and then applied to the other 4 fields. Following the CANDELS main morphology classification scheme, our model retrieves for each galaxy the probabilities of having a spheroid or a disk, presenting an irregularity, being compact or a point source, and being unclassifiable. ConvNets are able to predict the fractions of votes given to a galaxy image with zero bias and ~10% scatter. The fraction of mis-classifications is …

Filters And Matrix Factorization, Myung-Sin Song, Palle E. T. Jorgensen

SIUE Faculty Research, Scholarship, and Creative Activity

We give a number of explicit matrix-algorithms for analysis/synthesis

in multi-phase filtering; i.e., the operation on discrete-time signals which

allow a separation into frequency-band components, one for each of the

ranges of bands, say N , starting with low-pass, and then corresponding

filtering in the other band-ranges. If there are N bands, the individual

filters will be combined into a single matrix action; so a representation of

the combined operation on all N bands by an N x N matrix, where the

corresponding matrix-entries are periodic functions; or their extensions to

functions of a complex variable. Hence our setting entails …

Computer Simulation For Teaching The Structure Of Atoms And Periodic Table In Secondary Schools In Kenya: An Action Research, Ondoro Julius Okomo

Master of Education

Student engagement with learning is beneficial in improving conceptual understanding in chemistry. However, teaching and learning chemistry in Kenya reveals inadequate opportunity for secondary students to amply engage with learning. Traditional, teacher-centered, pedagogy is cited as the main cause of learner disengagement with abstract concepts in chemistry. This action research studied how Computer Simulation (CS) can be used to enhance teaching and learning the structure atoms and periodic table in secondary schools in Kenya through meaningful learner engagement. The study is guided by the question: How can I learn to teach the atomic structure of elements and periodic table using …

To Explore How Science Teachers Use Practical Activities In A Lesson: A Case Of A Community Based Secondary School In Western Tanzania, Madinda Mlimandoke

Master of Education

The research study was conducted to explore how teachers in a community-based secondary school in Kigoma region used practical activities in a science lesson. The qualitative case study design used to study a single community school namely Tudigite (pseudo name) by involving 3 science teachers (who were teaching physics, chemistry and biology in form one by that time of data collection) and 12 students (6 girls and 6 boys) from the 3 form 1 streams. Purposive sampling was employed to select the 3 science teachers while stratifies random sampling used to get the 12 students from form 1 streams. Data …

To Explore How Physics Teachers Use Instructional Materials In Teaching And Learning Of Physics In Secondary Schools: A Case Of One Secondary School In Taita Sub County, Kenya., Jackson Mwikamba Mwawongo

Master of Education

It is the desire any educator to help students meet their fullest potential by providing an environment that supports students to exercise independence of thought and encourage sharing of ideas. When the teacher acts as a guide, providing access to information rather than acting as the primary source of information, the students’ search for knowledge is met as they learn to construct knowledge for themselves and practice skills through hands on activities that reinforce the lesson being studied. Instructional materials help students in enhancing retention, stimulating and sustaining interest in learning by providing firsthand experience with realities of the physical …

The Role Of Schools In Promoting A Reading Habit Among The Lower Secondary School Students In A Town Council In Northwestern Uganda, Zubair Data Ismail

Master of Education

Many studies have reported that recreational reading among students, that is, the habit of reading beyond the academic demands leads to development of language skills necessary for improving educational outcomes essential for national development. This study was designed to establish the extent to which students were involved in recreational reading, the level of support the schools were giving to them, challenges faced in doing that, as well as suggested solutions to address the challenges. Two government schools were chosen for this study on the role of schools in promoting a reading habit among the lower secondary school students in a …