• Community detection in censored hypergraph 

  Bin, Zhao (North Dakota State University, 2024)

  Network, or graph, represent relationships between entities in various applications, such as social networks, biological systems, and communication networks. A common feature in network data is the presence of community ...

• Graph two-sample test via empirical likelihood 

  Zou, Ting (North Dakota State University, 2024)

  In the past two decades, there has been a notable surge in network data. This proliferation has spurred significant advancements in methods for analyzing networks across various disciplines, including computer science, ...

• Comparing Tests for a Mixed Design with Block Effect 

  Zhao, Hui (North Dakota State University, 2009)

  Tests Comb and Comb II are used to test the equality of means in a mixed design which is a combination of randomized complete block design and completely randomized design. The powers of Comb and Comb II for a mixed ...

• Robust Tests for Cointegration with Application to Statistical Arbitrage Trading Strategies 

  Hanson, Thomas Alan (North Dakota State University, 2010)

  This study proposes two new cointegration tests that employ rank-based and least absolute deviation techniques to create a robust version of the Engle-Granger cointegration test. Critical values are generated through a ...

• A Pilot Study of Module Interconnectedness 

  Vanguru, Prasanth (North Dakota State University, 2010)

  Complexity plays an important role in understanding and working with a program, and has been measured in many different ways for software applications. The use of statistical analysis is one of the ways to predict the ...

• Factors Influencing Carbon Sequestration in Northern Great Plains Grasslands 

  Annam (North Dakota State University, 2011)

  Soil development is influenced by the five soil forming factors; parent material, climate, landscape, organisms and time. This study was designed to examine the effects of landscape and organisms (vegetation) on carbon ...

• A Comparison of the Ansari-Bradley Test and the Moses Test for the Variances 

  Yuni, Chen (North Dakota State University, 2011)

  This paper is aimed to compare the powers and significance levels of two well known nonparametric tests: the Ansari-Bradley test and the Moses test in both situations where the equal-median assumption is satisfied and ...

• Estimating the Number of Genes That Are Differentially Expressed in Two Dependent Experiments or Analyses 

  Lawal, Hammed (North Dakota State University, 2022)

  Many researchers have used the intersection method to compare the results of differential expression analysis between two or more gene expression experiments. Some methods have been proposed to estimate the number of genes ...

• Profile Matching in Observational Studies With Multilevel Data 

  McGrath, Brenda (North Dakota State University, 2022)

  Matching is a popular method to use with observational data to replicate desired features of a randomized control trial. A common problem encountered in observational studies is the lack of common support or the limited ...

• A Study of Locally D-optimal Designs for the Emax Model with Heteroscedasticity 

  Zhang, Xiao (North Dakota State University, 2022)

  The classic theory of locally optimal designs is developed on the center+error model assuming Gaussianity and homoscedasticity for random error, in which, the Maximum Likelihood Estimator (MLE) turns out to be the most ...

• An Analysis of the NBA Draft: Are Teams Drafting Better and Does College Experience Truly Matter 

  Wolfe, Kevin (North Dakota State University, 2022)

  This thesis attempts to answer two questions. Are NBA organizations doing a reasonable job at drafting players and getting better at the process, and does college experience play a significant role in a player’s performance ...

• Performance of Permutation Tests Using Simulated Genetic Data 

  Soumare, Ibrahim (North Dakota State University, 2022)

  Disease statuses and biological conditions are known to be greatly impacted by differences in gene expression levels. A common challenge in RNA-seq data analysis is to identify genes whose mean expression levels change ...

• Comparing Prediction Accuracies of Cancer Survival Using Machine Learning Techniques and Statistical Methods in Combination with Data Reduction Methods 

  Mostofa, Mohammad (North Dakota State University, 2022)

  This comparative study of five-year survival prediction for breast, lung, colon, and leukemia cancers using a large SEER dataset along with 10-fold cross-validation provided us with an insight into the relative prediction ...

• Proposed Nonparametric Tests for the Umbrella Alternative in a Mixed Design Testing for Location and Location-Scale 

  Alotaibi, Eid Sadun (North Dakota State University, 2022)

  Researchers sometimes use the umbrella alternative when testing for differences in treatment effects, where the parameters increase up to a point and decrease after that point. Sometimes different treatment effects may ...

• Optimizing Prediction Power of RNA-seq on Intrinsic Characteristics in Breast Cancer 

  Liu, Yuan (North Dakota State University, 2022)

  Breast cancer is the most common cancer in women worldwide, and accurate and early detection of breast cancer is vital in characterizing the disease. Transcriptomic expression is embedded abundant tumor and cell state ...

• Comparing Prediction Methods of Wheat Grain Quality With the Area Under the Receiver Operating Characteristic Curves 

  Lin, Ying (North Dakota State University, 2021)

  A widely used breeding method is genomic selection, which uses genome-wide marker coverage to predict genotypic values for quantitative traits. Genomic selection combines molecular and phenotypic data in a training population ...

• A Comparative Multiple Simulation Study for Parametric and Nonparametric Methods in the Identification of Differentially Expressed Genes 

  Palmer, Daniel Grant (North Dakota State University, 2021)

  RNA-seq data simulated from a negative binomial distribution, sampled without replacement, or modified from read counts were analyzed to compare differential gene expression analysis methods in terms of false discovery ...

• A Simulation Study Using a Mixed Model Framework to Analyze the Impact of Sample Size and Variability on Type I Error and Power 

  Gu, Xiaoxue (North Dakota State University, 2021)

  Repeated measures design (or longitudinal study) are commonly seen in many research fields, especially in pharmaceutical clinical trials, agricultural research, and psychology. PROC MIXED (SAS Inc.) is a well-known standard ...

• Robustness of the Eigenvalue Test for Community Structure 

  Rose, Matthew Allan (North Dakota State University, 2021)

  Networks can take on many different forms, such as the people from the University you attend. Within these networks, community structure may exist. This "community structure" refers to the clustering of nodes by a common ...

• On Lasso Estimation of Linear Mixed Model for High Dimensional Longitudinal Data 

  Wen, Qian (North Dakota State University, 2021)

  With the advancement of technology in data collection, repeated measurements with high dimensional covariates have become increasingly common. The classical statistics approach for modeling the data of this kind is via the ...

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