scholarly journals Expansion for moments of regression quantiles with applications to nonparametric testing

Bernoulli ◽  
2019 ◽  
Vol 25 (2) ◽  
pp. 793-827
Author(s):  
Enno Mammen ◽  
Ingrid Van Keilegom ◽  
Kyusang Yu
Keyword(s):  
Regression Quantiles ◽  
Nonparametric Testing

scholarly journals Nonparametric testing of the existence of modes

1997 ◽  
Vol 25 (4) ◽  
pp. 1646-1660 ◽  
Author(s):  
Michael C. Minnotte
Keyword(s):  
Nonparametric Testing

scholarly journals A Multi-Methodological Analysis of a Non-Clinical Healthcare Executive and Servant Leader: Attributes and Behaviour’s and their Associations with Reporting Relationships and Business Structures

2021 ◽  
pp. 7-17
Author(s):  
Dr. Harold Ray Griffin* ◽  
Ms. Dana Foster
Keyword(s):  
Leadership Style ◽  
Career Advancement ◽  
Methodological Approach ◽  
A Priori ◽  
Future Research ◽  
Servant Leader ◽  
Servant Leaders ◽  
Nonparametric Testing ◽  
Business Structures ◽  
Reporting Relationships

A multi-methodological approach was used to examine the personal and professional life of a well-respected, nonclinical, healthcare executive for purposes of determining if “Don” was a servant leader and, if so, uncover the antecedents contributing to his leadership style. The results provided the backdrop for examining linkages between servant leadership, reporting relationships, and business structures. Content analysis and Spears’ 10 constructs of servant leaders were used as a priori themes to affirm that Don is a servant leader. Nonparametric testing revealed moderate to strong associations between the reporting relationships of the respondents (x1) and the types of business structures (x2) where the respondents and our servant leader forged their initial relationship and the perceived behaviors and attributes of Don (y). We discovered that relationships, spiritual centeredness, and desire for career advancement served as antecedents in shaping Don’s leadership style. Implications for practice and future research are also addressed.

scholarly journals Bioconductor workflow for microbiome data analysis: from raw reads to community analyses

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 1492 ◽  
Author(s):  
Ben J. Callahan ◽  
Kris Sankaran ◽  
Julia A. Fukuyama ◽  
Paul J. McMurdie ◽  
Susan P. Holmes
Keyword(s):  
High Throughput Sequencing ◽  
Linear Models ◽  
Reference Database ◽  
Rrna Gene ◽  
Microbial Composition ◽  
Nonparametric Testing ◽  
Abundance Estimates ◽  
Taxonomic Markers ◽  
Microbiome Data ◽  
Microbiome Data Analysis

High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level of analysis of complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or microbial composition of communities in different conditions. The sequencing reads have to be denoised and assigned to the closest taxa from a reference database. Common approaches use a notion of 97% similarity and normalize the data by subsampling to equalize library sizes. In this paper, we show that statistical models allow more accurate abundance estimates. By providing a complete workflow in R, we enable the user to do sophisticated downstream statistical analyses, including both parameteric and nonparametric methods. We provide examples of using the R packages dada2, phyloseq, DESeq2, ggplot2 and vegan to filter, visualize and test microbiome data. We also provide examples of supervised analyses using random forests, partial least squares and linear models as well as nonparametric testing using community networks and the ggnetwork package.

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