Uncovering Functional Relationships In Leukemia,
2017
Mathematical Biosciences Institute
Uncovering Functional Relationships In Leukemia, Reginald Mcgee
Biology and Medicine Through Mathematics Conference
No abstract provided.
Methods For Parameter Estimation Of A Stochastic Seir Model,
2017
Colorado School of Mines
Methods For Parameter Estimation Of A Stochastic Seir Model, Kaitlyn Martinez
Biology and Medicine Through Mathematics Conference
No abstract provided.
Using Mathematical Models Of Biological Processes In Genome-Wide Association Studies Of Psychiatric Disorders,
2017
University of Michigan-Ann Arbor
Using Mathematical Models Of Biological Processes In Genome-Wide Association Studies Of Psychiatric Disorders, Amy Cochran
Biology and Medicine Through Mathematics Conference
No abstract provided.
A Generalized Linear Model For Marital Disruption In Namibia,
2017
University of Namibia, Department of Statistics and Population Studies
A Generalized Linear Model For Marital Disruption In Namibia, Lillian Pazvakawambwa
Andrews Research Conference
Marital disruption has attracted wide attention among researchers. In recent years, the world has experienced reductions in marriage rates, along with significant increases in cohabiting unions, divorce and separation, leading to rising conjugal and family instability. While some have seen this as a sign of social and moral disruption with a potential to shatter the family institution and the foundations of society itself, others have embraced these trends as signaling increased individual liberty and the loosening of suffocating social mores. There is limited research on the factors influencing marital disruption in Namibia. This paper used the Namibia Demographic and Health …
Gilmore Girls And Instagram: A Statistical Look At The Popularity Of The Television Show Through The Lens Of An Instagram Page,
2017
Chapman University
Gilmore Girls And Instagram: A Statistical Look At The Popularity Of The Television Show Through The Lens Of An Instagram Page, Brittany Simmons
Student Scholar Symposium Abstracts and Posters
After going on the Warner Brothers Tour in December of 2015, I created a Gilmore Girls Instagram account. This account, which started off as a way for me to create edits of the show and post my photos from the tour turned into something bigger than I ever could have imagined. In just over a year I have over 55,000 followers. I post content including revival news, merchandise, and edits of the show that have been featured in Entertainment Weekly, Bustle, E! News, People Magazine, Yahoo News, & GilmoreNews.
I created a dataset of qualitative and quantitative outcomes from my …
Do You Know What Your Phone Is Doing To You? - Analysis On Usage Data Over An Entire Semester,
2017
Chapman University
Do You Know What Your Phone Is Doing To You? - Analysis On Usage Data Over An Entire Semester, Jawa El-Shanti
Student Scholar Symposium Abstracts and Posters
Like many teens today, I am a victim of cell phone addiction. Over the course of the spring 2017 semester I recorded my phone usage with the aim to quantify the degree of my addiction. I am using an iPhone application called Moment, which records the amount of time I spend on each application, the number of times I pick up my phone, and when I first and last used my phone during the day. I decided to keep track of the applications I want to minimize my time on which include Snapchat, Instagram, Netflix, YouTube and Messages. I am …
Using Multiple Imputation To Address Missing Values Of Hierarchical Data,
2017
Centers for Disease Control and Prevention, Atlanta
Using Multiple Imputation To Address Missing Values Of Hierarchical Data, Yujia Zhang, Sara Crawford, Sheree Boulet, Michael Monsour, Bruce Cohen, Patricia Mckane, Karen Freeman
Journal of Modern Applied Statistical Methods
Missing data may be a concern for data analysis. If it has a hierarchical or nested structure, the SUDAAN package can be used for multiple imputation. This is illustrated with birth certificate data that was linked to the Centers for Disease Control and Prevention’s National Assisted Reproductive Technology Surveillance System database. The Cox-Iannacchione weighted sequential hot deck method was used to conduct multiple imputation for missing/unknown values of covariates in a logistic model.
Selection Of Statistical Software For Data Scientists And Teachers,
2017
Valparaiso University
Selection Of Statistical Software For Data Scientists And Teachers, Ceyhun Ozgur, Min Dou, Yang Li, Grace Rogers
Journal of Modern Applied Statistical Methods
The need for analysts with expertise in big data software is becoming more apparent in today’s society. Unfortunately, the demand for these analysts far exceeds the number available. A potential way to combat this shortage is to identify the software sought by employers and to align this with the software taught by universities. This paper will examine multiple data analysis software – Excel add-ins, SPSS, SAS, Minitab, and R – and it will outline the cost, training, statistical methods/tests/uses, and specific uses within industry for each of these software. It will further explain implications for universities and students.
An Unbiased Estimator Of The Greatest Lower Bound,
2017
Radboud University Nijmegen, Netherlands
An Unbiased Estimator Of The Greatest Lower Bound, Nol Bendermacher
Journal of Modern Applied Statistical Methods
The greatest lower bound to the reliability of a test, based on a single administration, is the Greatest Lower Bound (GLB). However the estimate is seriously biased. An algorithm is described that corrects this bias.
Monte Carlo Study Of Some Classification-Based Ridge Parameter Estimators,
2017
Ladoke Akintola University of Technology
Monte Carlo Study Of Some Classification-Based Ridge Parameter Estimators, Adewale Folaranmi Lukman, Kayode Ayinde, Adegoke S. Ajiboye
Journal of Modern Applied Statistical Methods
Ridge estimator in linear regression model requires a ridge parameter, K, of which many have been proposed. In this study, estimators based on Dorugade (2014) and Adnan et al. (2014) were classified into different forms and various types using the idea of Lukman and Ayinde (2015). Some new ridge estimators were proposed. Results shows that the proposed estimators based on Adnan et al. (2014) perform generally better than the existing ones.
Multivariate Multilevel Modeling Of Age Related Diseases,
2017
University of Colombo, Sri Lanka
Multivariate Multilevel Modeling Of Age Related Diseases, Kapuruge N. O. Ranathunga, Roshini Sooriyarachchi
Journal of Modern Applied Statistical Methods
The emerging role of modeling multivariate multilevel data in the context of analyzing the risk factors are examined for the severity of cardiovascular disease diabetes, and chronic respiratory conditions. The modeling phase results leads to some important interaction terms between blood glucose, blood pressure, obesity, smoking and alcohol to the mortality rates.
Analysis Of Robust Parameter Designs,
2017
Concordia University
Analysis Of Robust Parameter Designs, Tak K. Mak, Fassil Nebebe
Journal of Modern Applied Statistical Methods
The analysis of robust parameter design is discussed via a model incorporating mean-variance relationship which, when ignored as in the classical regression approach, can be problematic. The model is also capable of alleviating the difficulties of the regression approach in the search of the minimum variance occurring region.
Distribution Fits For Various Parameters In The Florida Public Hurricane Loss Model,
2017
JM Family Enterprises, Inc., Deerfield Beach, FL
Distribution Fits For Various Parameters In The Florida Public Hurricane Loss Model, Victoria Oxenyuk, Sneh Gulati, B. M. Golam Kibria, Shahid Hamid
Journal of Modern Applied Statistical Methods
The purpose of this study is to re-analyze the atmospheric science component of the Florida Public Hurricane Loss Model v. 5.0, in order to investigate if the distributional fits used for the model parameters could be improved upon. We consider alternate fits for annual hurricane occurrence, radius of maximum winds and the pressure profile parameter.
Stochastic Model For Cancer Cell Growth Through Single Forward Mutation,
2017
Pondicherry University
Stochastic Model For Cancer Cell Growth Through Single Forward Mutation, Jayabharathiraj Jayabalan
Journal of Modern Applied Statistical Methods
A stochastic model for cancer cell growth in any organ is presented, based on a single forward mutation. Cell growth is explained in a one-dimensional stochastic model, and statistical measures for the variable representing the number of malignant cells are derived. A numerical study is conducted to observe the behavior of the model.
Genetic Algorithms For Cross-Calibration Of Categorical Data,
2017
Kuwait University
Genetic Algorithms For Cross-Calibration Of Categorical Data, Suja M. Aboukhamseen, Rym A. M'Hallah
Journal of Modern Applied Statistical Methods
The probabilistic problem of cross-calibration of two categorical variables is addressed. A probabilistic forecast of the categorical variables is obtained based on a sample of observed data. This forecast is the output of a genetic algorithm based approach, which makes no assumption on the type of relationship between the two variables and applies a scoring rule to assess the fitness of the chromosomes. It converges to a good-quality point probability forecast of the joint distribution of the two variables. The proposed approach is applied both at stationary points in time and across time. Its performance is enhanced when additional sampled …
A Schmid-Leiman-Based Transformation Resulting In Perfect Inter-Correlations Of Three Types Of Factor Score Predictors,
2017
Institute of Psychology, University of Bonn, Germany
A Schmid-Leiman-Based Transformation Resulting In Perfect Inter-Correlations Of Three Types Of Factor Score Predictors, André Beauducel
Journal of Modern Applied Statistical Methods
Factor score predictors are computed when individual factor scores are of interest. Conditions for a perfect inter-correlation of the best linear factor score predictor, the best linear conditionally unbiased predictor, and the determinant best linear correlation-preserving predictor are presented. A transformation resulting in perfect correlations of the three predictors is proposed.
Errors In A Program For Approximating Confidence Intervals,
2017
University of California Los Angeles
Errors In A Program For Approximating Confidence Intervals, Andrew V. Frane
Journal of Modern Applied Statistical Methods
An SPSS script previously presented in this journal contained nontrivial flaws. The script should not be used as written. A call is renewed for validation of new software.
An Empirical Comparison Between Robust Estimation And Robust Optimization To Mean-Variance Portfolio,
2017
State Islamic University, Sunan Kalijaga, Yogyakarta, Indonesia
An Empirical Comparison Between Robust Estimation And Robust Optimization To Mean-Variance Portfolio, Epha Diana Supandi, Dedi Rosadi, Abdurakhman
Journal of Modern Applied Statistical Methods
Mean-variance portfolios constructed using the sample mean and covariance matrix of asset returns perform poorly out-of-sample due to estimation error. Recently, there are two approaches designed to reduce the effect of estimation error: robust statistics and robust optimization. Two different robust portfolios were examined by assessing the out-of-sample performance and the stability of optimal portfolio compositions. The performance of the proposed robust portfolios was compared to classical portfolios via expected return, risk, and Sharpe Ratio. The aim is to shed light on the debate concerning the importance of the estimation error and weights stability in the portfolio allocation problem, and …
Guidelines For Generating Right-Censored Outcomes From A Cox Model Extended To Accommodate Time-Varying Covariates,
2017
Stanford University
Guidelines For Generating Right-Censored Outcomes From A Cox Model Extended To Accommodate Time-Varying Covariates, Maria E. Montez-Rath, Kristopher Kapphahn, Maya B. Mathur, Aya A. Mitani, David J. Hendry, Manisha Desai
Journal of Modern Applied Statistical Methods
Simulating studies with right-censored outcomes as functions of time-varying covariates is discussed. Guidelines on the use of an algorithm developed by Zhou and implemented by Hendry are provided. Through simulation studies, the sensitivity of the method to user inputs is considered.
A Reinterpretation And Extension Of Mcnemar’S Test,
2017
University of Maryland, College Park and BDS Data Analytics, LLC
A Reinterpretation And Extension Of Mcnemar’S Test, Chauncey M. Dayton
Journal of Modern Applied Statistical Methods
The McNemar test is extended to multiple groups based on a latent class model incorporating classes representing consistent responders and a single latent error rate. The method is illustrated with data from a CDC survey of immunizations for flu and pneumonia for which a part-heterogeneous model is selected for interpretation.
