scholarly journals SDFS: A Standardization Technique for Nonparametric Analysis

2021 ◽  
Vol 3 (1) ◽  
pp. 30-45
Author(s):  
Avimanyou K. Vatsa
Keyword(s):  
Data Analysis ◽  
Data Acquisition ◽  
Missing Values ◽  
Small Sample Size ◽  
Small Sample ◽  
Data Points ◽  
Standardization Process ◽  
Low Dimensional ◽  
Standardization Technique

Due to availability of computational tools for data acquisition, it is very easy to collect many dimensions from an object. Nevertheless, data acquisition from an object in an experiment may have a low number of dimensions. The analysis of low dimensional data has break-through role. But raw and sparse nature of dataset imposes new challenges and requirements for data analysis due to their special and unique characteristics. In the process of overall characterization of low-dimensional data, the data pre-processing plays crucial role. One of the first processes is normalization and standardization process. Therefore, in this paper, I would like to propose novel standardization technique called SDFS (Standardization for Distribution Free Statistics) for nonparametric data analysis. This technique is robust for small sample size with missing values of data points, which commonly exist in real time experiments lead to sparse low-dimensional data.  The comprehensive experimental evaluation shows that SDFS standardization is significantly outperforms on existing standardization methods.

scholarly journals The Discovery of Twenty-Eight New Encapsulin Sequences, Including Three in Anammox Bacteria

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
John C. Tracey ◽  
Maricela Coronado ◽  
Tobias W. Giessen ◽  
Maggie C. Y. Lau ◽  
Pamela A. Silver ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Phylogenetic Analysis ◽  
Sample Size ◽  
Small Sample Size ◽  
Small Sample ◽  
Anammox Bacteria ◽  
Freshwater Species ◽  
Cargo Protein

AbstractMany prokaryotes encode protein-based encapsulin nanocompartments, including anaerobic ammonium oxidizing (anammox) bacteria. This study expands the list of known anammox encapsulin systems from freshwater species to include the marine genus Scalindua. Two novel systems, identified in “Candidatus Scalindua rubra” and “Candidatus Scalindua sp. SCAELEC01 167” possess different architectures than previously studied freshwater anammox encapsulins. Characterization of the S. rubra encapsulin confirms that it can self-assemble to form compartments when heterologously expressed in Escherichia coli. BLASTp and HMMER searches of additional genomes and metagenomes spanning a range of environments returned 26 additional novel encapsulins, including a freshwater anammox encapsulin identified in “Candidatus Brocadia caroliniensis”. Phylogenetic analysis comparing these 28 new encapsulin sequences and cargo to that of their closest known relatives shows that encapsulins cluster by cargo protein type and therefore likely evolved together. Lastly, prokaryotic encapsulins may be more common and diverse than previously thought. Through searching a small sample size of all public metagenomes and genomes, many new encapsulin systems were unearthed by this study. This suggests that many additional encapsulins likely remain to be discovered.

scholarly journals MISSING VALUE IMPUTATION VIA GRAPH COMPLETION IN QUESTIONNAIRE SCORES FROM PERSONS WITH DEMENTIA

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S972-S972
Author(s):  
Chen Kan ◽  
Won Hwa Kim ◽  
Ling Xu ◽  
Noelle L Fields
Keyword(s):  
Missing Data ◽  
Statistical Power ◽  
Missing Values ◽  
Small Sample Size ◽  
Small Sample ◽  
Small Scale ◽  
Assessment And Treatment ◽  
Using Data ◽  
Small Sample Sizes ◽  
Clinical Conditions

Abstract Background: Questionnaires are widely used to evaluate cognitive functions, depression, and loneliness of persons with dementia (PWDs). Successful assessment and treatment of dementia hinge on effective analysis of PWDs’ answers. However, many studies, especially pilot ones, are with small sample sizes. Further, most of them contain missing data as PWDs skip some study sessions due to their clinical conditions. Conventional imputation strategies are not well-suited as bias will be introduced because of insufficient samples. Method: A novel machine learning framework was developed based on harmonic analysis on graphs to robustly handle missing values. Participants were first embedded as nodes in the graph with edges derived by their similarities based on demographic information, activities of daily living, etc. Then, questionnaire scores with missing values were regarded as a function on the nodes, and they were estimated based on spectral analysis of the graph with a smoothness constraint. The proposed approach was evaluated using data from our pilot study of dementia subjects (N=15) with 15% data missing. Result: A few complete variables (binary or ordinal) were available for all participants. For each variable, we randomly removed 5 scores to mimic missing values. With our approach, we could recover all missing values with 90% accuracy on average. We were also able to impute the actual missing values in the dataset within reasonable ranges. Conclusion: Our proposed approach imputes missing values with high accuracy despite the small sample size. The proposed approach will significantly boost statistical power of various small-scale studies with missing data.

scholarly journals Soil Property Variation within Taxa of ST at University of Nigeria, Nsukka

2021 ◽  
Vol 15 (2) ◽  
pp. 36
Author(s):  
Emeka P. Ukaegbu ◽  
Frank O. R. Akamigbo
Keyword(s):  
Predictive Accuracy ◽  
Small Sample Size ◽  
Soil Classification ◽  
Small Sample ◽  
Soil Productivity ◽  
Progressive Reduction ◽  
Soil Taxonomy ◽  
Property Variation ◽  
Coefficients Of Variation

Study evaluated predictive accuracy of USDA Soil Taxonomy Classifications of Soils of University of Nigeria, Nsukka. Data from 0 – 20cm and 30 – 60cm depths of 9 profiles, each representing a map unit, were used to determine coefficients of variation (CV) of soil properties over whole area sampled (control), within Great group class and series. There was progressive reduction in CVs from high to low categories, with the properties doing so irregularly. Average CVs for the various levels were 59.58% (over whole area), 56.97% (Great group), 50.77% (series) at topsoil, while at subsoil they were 38.15% (whole area), 31.53% (Great group), 25.19% (series). At topsoil, predictions of K & OC improved by 36.16% on the average at Great group, while it did for Clay, K, OC by 43.71% at series. At subsoil Silt, Mg, CEC, OC, TN improved by 34.17% at Great group on the average, while Clay, Silt, Mg, CEC, OC, TN, av.P did by 47.49% at series. Predicted properties, which were found to correlate with others, influence soil productivity. Sand and pH were virtually unaffected by classification. Study highlights a technique for evaluating predictive accuracy of soil classification using small sample size as well as the essence of detailed characterization of the soils.

scholarly journals Classifying Incomplete Gene-Expression Data: Ensemble Learning with Non-Pre-Imputation Feature Filtering and Best-First Search Technique

2018 ◽  
Vol 19 (11) ◽  
pp. 3398
Author(s):  
Yuanting Yan ◽  
Tao Dai ◽  
Meili Yang ◽  
Xiuquan Du ◽  
Yiwen Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Incomplete Data ◽  
Missing Values ◽  
Small Sample Size ◽  
Heuristic Method ◽  
Small Sample ◽  
Expression Data ◽  
Best First Search ◽  
The Impact

(1) Background: Gene-expression data usually contain missing values (MVs). Numerous methods focused on how to estimate MVs have been proposed in the past few years. Recent studies show that those imputation algorithms made little difference in classification. Thus, some scholars believe that how to select the informative genes for downstream classification is more important than how to impute MVs. However, most feature-selection (FS) algorithms need beforehand imputation, and the impact of beforehand MV imputation on downstream FS performance is seldom considered. (2) Method: A modified chi-square test-based FS is introduced for gene-expression data. To deal with the challenge of a small sample size of gene-expression data, a heuristic method called recursive element aggregation is proposed in this study. Our approach can directly handle incomplete data without any imputation methods or missing-data assumptions. The most informative genes can be selected through a threshold. After that, the best-first search strategy is utilized to find optimal feature subsets for classification. (3) Results: We compare our method with several FS algorithms. Evaluation is performed on twelve original incomplete cancer gene-expression datasets. We demonstrate that MV imputation on an incomplete dataset impacts subsequent FS in terms of classification tasks. Through directly conducting FS on incomplete data, our method can avoid potential disturbances on subsequent FS procedures caused by MV imputation. An experiment on small, round blue cell tumor (SRBCT) dataset showed that our method found additional genes besides many common genes with the two compared existing methods.

Probing the ultrastructure of the mitotic and meiotic spindle in eggs: An expeditious approach based on semi-thin (0.25 μm) serial sections

1983 ◽  
Vol 41 ◽  
pp. 552-555
Author(s):  
Conly L. Rieder ◽  
S. Bowser ◽  
R. Nowogrodzki ◽  
K. Ross ◽  
G. Sluder
Keyword(s):  
Small Sample Size ◽  
Small Sample ◽  
Meiotic Spindle ◽  
Serial Sections ◽  
Mitotic Apparatus ◽  
Thin Sections ◽  
Cell Cycles ◽  
Ultrastructural Studies

Eggs have long been a favorite material for studying the mechanism of karyokinesis in-vivo and in-vitro. They can be obtained in great numbers and, when fertilized, divide synchronously over many cell cycles. However, they are not considered to be a practical system for ultrastructural studies on the mitotic apparatus (MA) for several reasons, the most obvious of which is that sectioning them is a formidable task: over 1000 ultra-thin sections need to be cut from a single 80-100 μm diameter egg and of these sections only a small percentage will contain the area or structure of interest. Thus it is difficult and time consuming to obtain reliable ultrastructural data concerning the MA of eggs; and when it is obtained it is necessarily based on a small sample size.We have recently developed a procedure which will facilitate many studies concerned with the ultrastructure of the MA in eggs. It is based on the availability of biological HVEM's and on the observation that 0.25 μm thick serial sections can be screened at high resolution for content (after mounting on slot grids and staining with uranyl and lead) by phase contrast light microscopy (LM; Figs 1-2).

Validating the Factor Structure of the Stigma of Suicide Scale–Short Form Spanish Version Among Healthcare Students

Crisis ◽  
2020 ◽  
pp. 1-5
Author(s):  
Ruthmarie Hernández-Torres ◽  
Paola Carminelli-Corretjer ◽  
Nelmit Tollinchi-Natali ◽  
Ernesto Rosario-Hernández ◽  
Yovanska Duarté-Vélez ◽  
...  
Keyword(s):  
Factor Structure ◽  
Structural Equation ◽  
Short Form ◽  
Small Sample Size ◽  
Small Sample ◽  
Spanish Version ◽  
Equation Modeling ◽  
Cross Sectional ◽  
Healthcare Students ◽  
Spanish Speaking

Abstract. Background: Suicide is a leading cause of death among Spanish-speaking individuals. Suicide stigma can be a risk factor for suicide. A widely used measure is the Stigma of Suicide Scale-Short Form (SOSS-SF; Batterham, Calear, & Christensen, 2013 ). Although the SOSS-SF has established psychometric properties and factor structure in other languages and cultural contexts, no evidence is available from Spanish-speaking populations. Aim: This study aims to validate a Spanish translation of the SOSS-SF among a sample of Spanish-speaking healthcare students ( N = 277). Method: We implemented a cross-sectional design with quantitative techniques. Results: Following a structural equation modeling approach, a confirmatory factor analysis (CFA) supported the three-factor model proposed by Batterham and colleagues (2013) . Limitations: The study was limited by the small sample size and recruitment by availability. Conclusion: Findings suggest that the Spanish version of the SOSS-SF is a valid and reliable tool with which to examine suicide stigma among Spanish-speaking populations.

An Initial Investigation of Suicide Attempt Disclosures Among US Veterans

Crisis ◽  
2020 ◽  
pp. 1-7
Author(s):  
Brooke A. Ammerman ◽  
Sarah P. Carter ◽  
Heather M. Gebhardt ◽  
Jonathan Buchholz ◽  
Mark A. Reger
Keyword(s):  
Suicide Attempt ◽  
Mental Health Professionals ◽  
Help Seeking ◽  
Psychiatric Treatment ◽  
Small Sample Size ◽  
Romantic Partners ◽  
Small Sample ◽  
Professional Care ◽  
Patient Disclosure ◽  
Previous Suicide Attempt

Abstract. Background: Patient disclosure of prior suicidal behaviors is critical for effectively managing suicide risk; however, many attempts go undisclosed. Aims: The current study explored how responses following a suicide attempt disclosure may relate to help-seeking outcomes. Method: Participants included 37 veterans with a previous suicide attempt receiving inpatient psychiatric treatment. Veterans reported on their most and least helpful experiences disclosing their suicide attempt to others. Results: Veterans disclosed their suicide attempt to approximately eight individuals. Mental health professionals were the most cited recipient of their most helpful disclosure; romantic partners were the most common recipient of their least helpful disclosures. Positive reactions within the context of the least helpful disclosure experience were positively associated with a sense of connection with the disclosure recipient. Positive reactions within the most helpful disclosure experience were positively associated with the likelihood of future disclosure. No reactions were associated with having sought professional care or likelihood of seeking professional care. Limitations: The results are considered preliminary due to the small sample size. Conclusion: Findings suggest that while positive reactions may influence suicide attempt disclosure experiences broadly, additional research is needed to clarify factors that drive the decision to disclose a suicide attempt to a professional.

Investigating the Dynamics of Suicidal Ideation

Crisis ◽  
2018 ◽  
Vol 39 (1) ◽  
pp. 65-69 ◽  
Author(s):  
Nina Hallensleben ◽  
Lena Spangenberg ◽  
Thomas Forkmann ◽  
Dajana Rath ◽  
Ulrich Hegerl ◽  
...  
Keyword(s):  
Suicidal Ideation ◽  
Small Sample Size ◽  
Unipolar Depression ◽  
Small Sample ◽  
History Of ◽  
Severity Of Depression ◽  
Ecological Momentary ◽  
Depressive Episodes ◽  
Ema Method ◽  
Shed Light

Abstract. Background: Although the fluctuating nature of suicidal ideation (SI) has been described previously, longitudinal studies investigating the dynamics of SI are scarce. Aim: To demonstrate the fluctuation of SI across 6 days and up to 60 measurement points using smartphone-based ecological momentary assessments (EMA). Method: Twenty inpatients with unipolar depression and current and/or lifetime suicidal ideation rated their momentary SI 10 times per day over a 6-day period. Mean squared successive difference (MSSD) was calculated as a measure of variability. Correlations of MSSD with severity of depression, number of previous depressive episodes, and history of suicidal behavior were examined. Results: Individual trajectories of SI are shown to illustrate fluctuation. MSSD values ranged from 0.2 to 21.7. No significant correlations of MSSD with several clinical parameters were found, but there are hints of associations between fluctuation of SI and severity of depression and suicidality. Limitations: Main limitation of this study is the small sample size leading to low power and probably missing potential effects. Further research with larger samples is necessary to shed light on the dynamics of SI. Conclusion: The results illustrate the dynamic nature and the diversity of trajectories of SI across 6 days in psychiatric inpatients with unipolar depression. Prediction of the fluctuation of SI might be of high clinical relevance. Further research using EMA and sophisticated analyses with larger samples is necessary to shed light on the dynamics of SI.

Participant Reactions to Suicide-Focused Research

Crisis ◽  
2020 ◽  
Vol 41 (5) ◽  
pp. 367-374
Author(s):  
Sarah P. Carter ◽  
Brooke A. Ammerman ◽  
Heather M. Gebhardt ◽  
Jonathan Buchholz ◽  
Mark A. Reger
Keyword(s):  
Medical Records ◽  
Research Study ◽  
Small Sample Size ◽  
Psychiatric Inpatient ◽  
Small Sample ◽  
Inpatient Unit ◽  
Online Laboratory ◽  
Psychiatric Inpatient Unit ◽  
Before And After ◽  
Participant Reactions

Abstract. Background: Concerns exist regarding the perceived risks of conducting suicide-focused research among an acutely distressed population. Aims: The current study assessed changes in participant distress before and after participation in a suicide-focused research study conducted on a psychiatric inpatient unit. Method: Participants included 37 veterans who were receiving treatment on a psychiatric inpatient unit and completed a survey-based research study focused on suicide-related behaviors and experiences. Results: Participants reported no significant changes in self-reported distress. The majority of participants reported unchanged or decreased distress. Reviews of electronic medical records revealed no behavioral dysregulation and minimal use of as-needed medications or changes in mood following participation. Limitations: The study's small sample size and veteran population may limit generalizability. Conclusion: Findings add to research conducted across a variety of settings (i.e., outpatient, online, laboratory), indicating that participating in suicide-focused research is not significantly associated with increased distress or suicide risk.

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