Statistics and Probability Commons^™

Sample Size Calculations And Normalization Methods For Rna-Seq Data., Xiaohong Li

Electronic Theses and Dissertations

High-throughput RNA sequencing (RNA-seq) has become the preferred choice for transcriptomics and gene expression studies. With the rapid growth of RNA-seq applications, sample size calculation methods for RNA-seq experiment design and data normalization methods for DEG analysis are important issues to be explored and discussed. The underlying theme of this dissertation is to develop novel sample size calculation methods in RNA-seq experiment design using test statistics. I have also proposed two novel normalization methods for analysis of RNA-seq data. In chapter one, I present the test statistical methods including Wald’s test, log-transformed Wald’s test and likelihood ratio test statistics for …

Outlier Impact And Accommodation On Power, Hongjing Liao, Yanju Li, Gordon P. Brooks

Journal of Modern Applied Statistical Methods

The outliers’ influence on power rates in ANOVA and Welch tests at various conditions was examined and compared with the effectiveness of nonparametric methods and Winsorizing in minimizing the impact of outliers. Results showed that, considering both power and Type I error, a nonparametric test is the safest choice to control the inflation of Type I error with a decent sample size and yield relatively high power.

Comparing The Structural Components Variance Estimator And U-Statistics Variance Estimator When Assessing The Difference Between Correlated Aucs With Finite Samples, Anna L. Bosse

Theses and Dissertations

Introduction: The structural components variance estimator proposed by DeLong et al. (1988) is a popular approach used when comparing two correlated AUCs. However, this variance estimator is biased and could be problematic with small sample sizes.

Methods: A U-statistics based variance estimator approach is presented and compared with the structural components variance estimator through a large-scale simulation study under different finite-sample size configurations.

Results: The U-statistics variance estimator was unbiased for the true variance of the difference between correlated AUCs regardless of the sample size and had lower RMSE than the structural components variance estimator, providing better type 1 error …

Robustness And Power Of The Student T, Welch-Aspin, Yuen, Tukey Quick, And Haga Tests, Dong Li

Wayne State University Dissertations

Classical parametric statistic procedures are widely used in the research community. However, for classical tests to produce accurate results, the assumptions underlying them must be sufficiently satisfied. When the assumptions are not met, the results of the analysis may be due to the violation of the assumptions, instead of the true pattern of the data. The assumptions are rarely met when analyzing real data. The use of classic parametric methods with violated assumptions may lead to substantive errors in the interpretation of data. As an alternative to normal theory statistics, nonparametric statistical procedures do not make assumptions about the underlying …