Statistics and Probability Commons^™

Direct Experience With Cervical Cancer Patient, Husband Support, And Self-Perception As Determinant Factors Of Women’S Desire To Take Via Screening Test, Nur Anisah Rahmawati, Linda Dewanti

Kesmas

Kanker serviks menyebabkan 10.3% kematian pada perempuan di Indonesia. Inspeksi visual asam asetat (IVA) telah digunakan untuk program skrining sejak tahun 2014 tetapi hanya 2,45 % perempuan yang melakukan pemeriksaan pada tahun 2015. Di tempat penelitian, cakupan skrining metode IVA kurang dari 1%. Penelitian sebelumnya menyebutkan faktor psikososial sebagai satu faktor penting, tetapi sedikit penelitian yang menganalisis peran dukungan suami dan pengalaman langsung dengan penderita kanker serviks. Penelitian ini bertujuan mempelajari hubungan antara pengalaman langsung dengan penderita kanker serviks, dukungan suami, persepsi diri dan keinginan perempuan melakukan skrining IVA. Penelitian potong lintang dilakukan secara acak pada perempuan berusia 25-55 tahun …

P-Value Histograms: Inference And Diagnostics, Patrick Breheny, Arnold Stromberg, Joshua Lambert

Statistics Faculty Publications

It is increasingly common for experiments in biology and medicine to involve large numbers of hypothesis tests. A natural graphical method for visualizing these tests is to construct a histogram from the p-values of these tests. In this article, we examine the shapes, both regular and irregular, that these histograms can take on, as well as present simple inferential procedures that help to interpret the shapes in terms of diagnosing potential problems with the experiment. We examine potential causes of these problems in detail, and discuss potential remedies. Throughout, examples of irregular-looking p-value histograms are provided and based …

Web-Based Application To Support Physical Fitness Information Of Elderly People, Yudhy Dharmawan, Suroto Suroto, Priguna Septia Putra

Kesmas

Penduduk lanjut usia (lansia) semakin banyak seiring meningkatnya usia harapan hidup. Banyak upaya yang harus dilakukan untuk mencegah kesakitan di lansia, salah satunya dari aspek preventif dengan menjaga kebugaran para lansia. Untuk memonitor status kebugaran lansia, maka diperlukan aplikasi pemantauan kebugaran jasmani berbasis teknologi web karena tidak ada sistem yang merekam data kebugaran para lansia. Aplikasi ini ditujukan untuk merekam data kebugaran jasmani para lansia untuk merekomendasikan gym yang sesuai berdasarkan kondisi kesehatan yang dapat diakses di mana saja. Aplikasi ini dibuat dengan bahasa pemrograman PHP dan MYSQL sebagai pengolahan basis data yang dilengkapi dengan grafik untuk memantau kebugaran jasmaninya. …

The Implementation Of Documentation By Midwives In Pekanbaru, Wan Anita

Kesmas

Dokumentasi kebidanan adalah suatu bukti pencatatan dan pelaporan yang dimiliki oleh bidan dalam melakukan catatan perawatan yang berguna untuk kepentingan pasien, bidan, dan tim kesehatan. Pendokumentasian dapat diterapkan dengan metode Subjektif, Objektif, Analisa dan Perencanaan (SOAP). Penelitian ini bertujuan mengetahui faktor-faktor yang berhubungan dengan pelaksanaan dokumentasi SOAP oleh bidan di Kota Pekanbaru tahun 2016. Penelitian bersifat kuantitatif analitik observasional dengan desain penelitian potong lintang analitik. Sampel penelitian adalah seluruh populasi bidan yang praktik mandiri atau di rumah bersalin di Kota Pekanbaru dengan jumlah sampel sebanyak 191 bidan yang diambil dengan prosedur systematic random sampling. Data dikumpulkan melalui wawancara langsung dengan …

Adolescent’S Knowledge And Skill To Refuse Drugs, Lucky Herawati, Johan Arief Budiman, Haryono Haryono

Kesmas

Berbagai upaya telah dilakukan untuk mencegah remaja dari penggunaan narkoba, kendatipun evaluasi pengetahuan dan keterampilan remaja menolak narkoba belum pernah dilakukan. Penelitian ini dilakukan pada 300 remaja, siswa kelas 7 atau setara usia 12-15 tahun di dua kota di Provinsi Daerah Istimewa Yogyakarta. Penelitian analitik bertujuan mengetahui gambaran pengetahuan, keterampilan remaja menolak narkoba, dan hubungan keduanya dengan karakteristik remaja. Variabel yang diteliti adalah pengetahuan remaja tentang narkoba, keterampilan menolak narkoba, dan karakteristik remaja, yang dikumpulkan dengan menggunakan kuesioner (self-reported questionnaire). Data dianalisis dengan uji korelasi Pearson dan Spearman rho, dengan tingkat signifikansi 95 persen. Hasil penelitian menunjukkan bahwa rata-rata nilai …

Overcoming Small Data Limitations In Heart Disease Prediction By Using Surrogate Data, Alfeo Sabay, Laurie Harris, Vivek Bejugama, Karen Jaceldo-Siegl

SMU Data Science Review

In this paper, we present a heart disease prediction use case showing how synthetic data can be used to address privacy concerns and overcome constraints inherent in small medical research data sets. While advanced machine learning algorithms, such as neural networks models, can be implemented to improve prediction accuracy, these require very large data sets which are often not available in medical or clinical research. We examine the use of surrogate data sets comprised of synthetic observations for modeling heart disease prediction. We generate surrogate data, based on the characteristics of original observations, and compare prediction accuracy results achieved from …

Random Forest Vs Logistic Regression: Binary Classification For Heterogeneous Datasets, Kaitlin Kirasich, Trace Smith, Bivin Sadler

SMU Data Science Review

Selecting a learning algorithm to implement for a particular application on the basis of performance still remains an ad-hoc process using fundamental benchmarks such as evaluating a classifier’s overall loss function and misclassification metrics. In this paper we address the difficulty of model selection by evaluating the overall classification performance between random forest and logistic regression for datasets comprised of various underlying structures: (1) increasing the variance in the explanatory and noise variables, (2) increasing the number of noise variables, (3) increasing the number of explanatory variables, (4) increasing the number of observations. We developed a model evaluation tool capable …

Predicting National Basketball Association Success: A Machine Learning Approach, Adarsh Kannan, Brian Kolovich, Brandon Lawrence, Sohail Rafiqi

SMU Data Science Review

In this paper, we present a machine learning based approach to projecting the success of National Basketball Association (NBA) draft prospects. With the proliferation of data, analytics have increasingly be- come a critical component in the assessment of professional and collegiate basketball players. We leverage player biometric data, college statistics, draft selection order, and positional breakdown as modelling features in our prediction algorithms. We found that a player's draft pick and their college statistics are the best predictors of their longevity in the National Basketball Association.

Minimizing The Perceived Financial Burden Due To Cancer, Hassan Azhar, Zoheb Allam, Gino Varghese, Daniel W. Engels, Sajiny John

SMU Data Science Review

In this paper, we present a regression model that predicts perceived financial burden that a cancer patient experiences in the treatment and management of the disease. Cancer patients do not fully understand the burden associated with the cost of cancer, and their lack of understanding can increase the difficulties associated with living with the disease, in particular coping with the cost. The relationship between demographic characteristics and financial burden were examined in order to better understand the characteristics of a cancer patient and their burden, while all subsets regression was used to determine the best predictors of financial burden. Age, …

Yelp’S Review Filtering Algorithm, Yao Yao, Ivelin Angelov, Jack Rasmus-Vorrath, Mooyoung Lee, Daniel W. Engels

SMU Data Science Review

In this paper, we present an analysis of features influencing Yelp's proprietary review filtering algorithm. Classifying or misclassifying reviews as recommended or non-recommended affects average ratings, consumer decisions, and ultimately, business revenue. Our analysis involves systematically sampling and scraping Yelp restaurant reviews. Features are extracted from review metadata and engineered from metrics and scores generated using text classifiers and sentiment analysis. The coefficients of a multivariate logistic regression model were interpreted as quantifications of the relative importance of features in classifying reviews as recommended or non-recommended. The model classified review recommendations with an accuracy of 78%. We found that reviews …

Cryptocurrency Price Prediction Using Tweet Volumes And Sentiment Analysis, Jethin Abraham, Daniel Higdon, John Nelson, Juan Ibarra

SMU Data Science Review

In this paper, we present a method for predicting changes in Bitcoin and Ethereum prices utilizing Twitter data and Google Trends data. Bitcoin and Ethereum, the two largest cryptocurrencies in terms of market capitalization represent over \$160 billion dollars in combined value. However, both Bitcoin and Ethereum have experienced significant price swings on both daily and long term valuations. Twitter is increasingly used as a news source influencing purchase decisions by informing users of the currency and its increasing popularity. As a result, quickly understanding the impact of tweets on price direction can provide a purchasing and selling advantage to …

Optimization For Lng Terminals Routing In North China, Shuting Wang

World Maritime University Dissertations

No abstract provided.

Study On The Fluctuation And Forecasting Of Capsize Bulk Carrier’S Freight, Kelun Wei

World Maritime University Dissertations

No abstract provided.

How Chinese Enterprises Evaluate The Investment Value Of Seaports Along The “One Belt One Road”, Ziyang Zhang

World Maritime University Dissertations

No abstract provided.

Study On The Efficiency Of China’S Main River Ports Based On Dea Model, Yunwu Cao

World Maritime University Dissertations

No abstract provided.

Of Typicality And Predictive Distributions In Discriminant Function Analysis, Lyle W. Konigsberg, Susan R. Frankenberg

Human Biology Open Access Pre-Prints

While discriminant function analysis is an inherently Bayesian method, researchers attempting to estimate ancestry in human skeletal samples often follow discriminant function analysis with the calculation of frequentist-based typicalities for assigning group membership. Such an approach is problematic in that it fails to account for admixture and for variation in why individuals may be classified as outliers, or non-members of particular groups. This paper presents an argument and methodology for employing a fully Bayesian approach in discriminant function analysis applied to cases of ancestry estimation. The approach requires adding the calculation, or estimation, of predictive distributions as the final step …

Secondary Data Analysis Project, Jonathan M. Gallimore

SF 420 PR - Gallimore - Fall 2018

This activity is designed to give students an opportunity to apply what they have learned in statistics to a real dataset.

This activity will help students apply what they have learned in statistics to real world data and answer their own research questions. Students will also practice reporting their results in a paper using APA format.

Quantitative Jeopardy Feud, Jonathan M. Gallimore

MSF 600 PR - Gallimore - Fall 2018

This activity - Quantitative Jeopardy Feud - is a method for using a game as a final exam.

The Transmuted Geometric-Quadratic Hazard Rate Distribution: Development, Properties, Characterizations And Applications, Fiaz Ahmad Bhatti, Gholamhossein Hamedani, Mustafa Ç. Korkmaz, Munir Ahmad

Mathematics, Statistics and Computer Science Faculty Research and Publications

We propose a five parameter transmuted geometric quadratic hazard rate (TG-QHR) distribution derived from mixture of quadratic hazard rate (QHR), geometric and transmuted distributions via the application of transmuted geometric-G (TG-G) family of Afify et al.(Pak J Statist 32(2), 139-160, 2016). Some of its structural properties are studied. Moments, incomplete moments, inequality measures, residual life functions and some other properties are theoretically taken up. The TG-QHR distribution is characterized via different techniques. Estimates of the parameters for TG-QHR distribution are obtained using maximum likelihood method. The simulation studies are performed on the basis of graphical results to illustrate the performance …

Automatic Knowledge Extraction From Ocr Documents Using Hierarchical Document Analysis, Mohammad Masum, Sai Kosaraju, Tanju Bayramoglu, Girish Modgil, Mingon Kang

Published and Grey Literature from PhD Candidates

Industries can improve their business efficiency by analyzing and extracting relevant knowledge from large numbers of documents. Knowledge extraction manually from large volume of documents is labor intensive, unscalable and challenging. Consequently, there have been a number of attempts to develop intelligent systems to automatically extract relevant knowledge from OCR documents. Moreover, the automatic system can improve the capability of search engine by providing application-specific domain knowledge. However, extracting the efficient information from OCR documents is challenging due to highly unstructured format. In this paper, we propose an efficient framework for a knowledge extraction system that takes keywords based queries …

Confidence Intervals For The Area Under The Receiver Operating Characteristic Curve In The Presence Of Ignorable Missing Data, Hunyong Cho, Gregory J. Matthews, Ofer Harel

Mathematics and Statistics: Faculty Publications and Other Works

Receiver operating characteristic curves are widely used as a measure of accuracy of diagnostic tests and can be summarised using the area under the receiver operating characteristic curve (AUC). Often, it is useful to construct a confidence interval for the AUC; however, because there are a number of different proposed methods to measure variance of the AUC, there are thus many different resulting methods for constructing these intervals. In this article, we compare different methods of constructing Wald‐type confidence interval in the presence of missing data where the missingness mechanism is ignorable. We find that constructing confidence intervals using multiple …

Dietary Inflammatory Index And Biomarkers Of Lipoprotein Metabolism, Inflammation And Glucose Homeostasis In Adults, Catherine Phillips, Nitin Shivappa, James R. Hébert, Ivan Perry

Faculty Publications

Accumulating evidence identifies diet and inflammation as potential mechanisms contributing to cardiometabolic risk. However, inconsistent reports regarding dietary inflammatory potential, biomarkers of cardiometabolic health and metabolic syndrome (MetS) risk exist. Our objective was to examine the relationships between a food frequency questionnaire (FFQ)-derived dietary inflammatory index (DII®), biomarkers of lipoprotein metabolism, inflammation and glucose homeostasis and MetS risk in a cross-sectional sample of 1992 adults. Energy-adjusted DII (E-DII) scores derived from an FFQ were calculated. Lipoprotein particle size and subclass concentrations were measured using nuclear magnetic resonance (NMR) spectroscopy. Serum acute-phase reactants, adipocytokines, pro-inflammatory cytokines and white blood cell (WBC) …

Robust Inference For The Stepped Wedge Design, James P. Hughes, Patrick J. Heagerty, Fan Xia, Yuqi Ren

UW Biostatistics Working Paper Series

Based on a permutation argument, we derive a closed form expression for an estimate of the treatment effect, along with its standard error, in a stepped wedge design. We show that these estimates are robust to misspecification of both the mean and covariance structure of the underlying data-generating mechanism, thereby providing a robust approach to inference for the treatment effect in stepped wedge designs. We use simulations to evaluate the type I error and power of the proposed estimate and to compare the performance of the proposed estimate to the optimal estimate when the correct model specification is known. The …

Generalizing Multistage Partition Procedures For Two-Parameter Exponential Populations, Rui Wang

LSU New Orleans Theses and Dissertations

ANOVA analysis is a classic tool for multiple comparisons and has been widely used in numerous disciplines due to its simplicity and convenience. The ANOVA procedure is designed to test if a number of different populations are all different. This is followed by usual multiple comparison tests to rank the populations. However, the probability of selecting the best population via ANOVA procedure does not guarantee the probability to be larger than some desired prespecified level. This lack of desirability of the ANOVA procedure was overcome by researchers in early 1950's by designing experiments with the goal of selecting the best …

Bubble Stream Production By Belugas (Delphinapterus Leucas), Megan Slack

Theses

Bubble stream production in belugas has been poorly characterized and its function is not well understood. I examined behavioral states when producing bubble streams (“bubbling”), and when bubbling calls, to determine whether bubbling was significantly associated with a particular call category or behavioral state. Using 19 hours of video and audio recordings collected over a two-day period, I quantified bubble streams of a 4-month old calf and an unrelated adult female housed together. Based on the overall activity budgets and pool of vocalizations for both animals, I calculated the expected counts of bubble streams with and without vocalizations, assuming that …

Deep Machine Learning For Mechanical Performance And Failure Prediction, Elijah Reber, Nickolas D. Winovich, Guang Lin

The Summer Undergraduate Research Fellowship (SURF) Symposium

Deep learning has provided opportunities for advancement in many fields. One such opportunity is being able to accurately predict real world events. Ensuring proper motor function and being able to predict energy output is a valuable asset for owners of wind turbines. In this paper, we look at how effective a deep neural network is at predicting the failure or energy output of a wind turbine. A data set was obtained that contained sensor data from 17 wind turbines over 13 months, measuring numerous variables, such as spindle speed and blade position and whether or not the wind turbine experienced …

Efvs Effects On Pilot Performance, Michael Campbell, Nsikak Udo-Imeh, Steven J. Landry

The Summer Undergraduate Research Fellowship (SURF) Symposium

Flight tests have been conducted at Purdue University using a computer-based flying simulator in an attempt to determine and measure the effects of Enhanced Flight Vision Systems (EFVS) on the performance of pilots during landing. Knowledge of these effects could help guide future design and implementation of EFVS in modern commercial aircraft, and further increase pilots’ ability to control the aircraft in low-visibility conditions. The problem that has faced researchers in the past has revolved around the difficulty in interpreting the data which is generated by these tests. The difficulty in making a generalized conclusion based on the large amount …

Scale-Invariant Geometric Data Analysis (Sigda), Marina Girgis, Max Robinson

STAR Program Research Presentations

The purpose of this research is to introduce a new data analysis method called Scale Invariant Geometric Data Analysis (SIGDA). SIGDA has been shown to be more informative than more common data analysis methods, such as Principal Component Analysis (PCA). SIGDA is used to visualize complex data sets in a way that accurately preserves data patterns and behavior. SIGDA is designed to preserve relative ratios in a numerical matrix, and the number of entries has to be more than the total number of rows and columns. Our research involved providing a simple explanation of SIGDA's mathematical process—simple enough for the …

Development Of A Statistical Model For Discrimination Of Rupture Status In Posterior Communicating Artery Aneurysms, Felicitas J. Detmer, Bong Jae Chung, Fernando Mut, Michael Pritz, Martin Slawski, Farid Hamzei-Sichani, David Kallmes, Christopher Putman, Carlos Jimenez, Juan R. Cebral

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

Background: Intracranial aneurysms at the posterior communicating artery (PCOM) are known to have high rupture rates compared to other locations. We developed and internally validated a statistical model discriminating between ruptured and unruptured PCOM aneurysms based on hemodynamic and geometric parameters, angio-architectures, and patient age with the objective of its future use for aneurysm risk assessment. Methods: A total of 289 PCOM aneurysms in 272 patients modeled with image-based computational fluid dynamics (CFD) were used to construct statistical models using logistic group lasso regression. These models were evaluated with respect to discrimination power and goodness of fit using tenfold nested …

Feature Screening Of Ultrahigh Dimensional Feature Spaces With Applications In Interaction Screening, Randall D. Reese

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Data for which the number of predictors exponentially exceeds the number of observations is becoming increasingly prevalent in fields such as bioinformatics, medical imaging, computer vision, And social network analysis. One of the leading questions statisticians must answer when confronted with such “big data” is how to reduce a set of exponentially many predictors down to a set of a mere few predictors which have a truly causative effect on the response being modelled. This process is often referred to as feature screening. In this work we propose three new methods for feature screening. The first method we propose (TC-SIS) …