Browse
Submit Data
Databases
API
Help

Dataset Information

10 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Hypothetical Outcome Plots Outperform Error Bars and Violin Plots for Inferences about Reliability of Variable Ordering.

ABSTRACT: Many visual depictions of probability distributions, such as error bars, are difficult for users to accurately interpret. We present and study an alternative representation, Hypothetical Outcome Plots (HOPs), that animates a finite set of individual draws. In contrast to the statistical background required to interpret many static representations of distributions, HOPs require relatively little background knowledge to interpret. Instead, HOPs enables viewers to infer properties of the distribution using mental processes like counting and integration. We conducted an experiment comparing HOPs to error bars and violin plots. With HOPs, people made much more accurate judgments about plots of two and three quantities. Accuracy was similar with all three representations for most questions about distributions of a single quantity.

SUBMITTER: Hullman J

PROVIDER: S-EPMC4646698 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Putting error bars on density functional theory.

Project description:Predicting the error in density functional theory (DFT) calculations due to the choice of exchange-correlation (XC) functional is crucial to the success of DFT, but currently, there are limited options to estimate this a priori. This is particularly important for high-throughput screening of new materials. In this work, the structure and elastic properties of binary and ternary oxides are computed using four XC functionals: LDA, PBE-GGA, PBEsol, and vdW-DF with C09 exchange. To analyze the systemic errors inherent to each XC functional, we employed materials informatics methods to predict the expected errors. The predicted errors were also used to better the DFT-predicted lattice parameters. Our results emphasize the link between the computed errors and the electron density and hybridization errors of a functional. In essence, these results provide "error bars" for choosing a functional for the creation of high-accuracy, high-throughput datasets as well as avenues for the development of XC functionals with enhanced performance, thereby enabling the accelerated discovery and design of new materials.

| S-EPMC11364665 | biostudies-literature

Error Bars Considered Harmful: Exploring Alternate Encodings for Mean and Error.

Project description:When making an inference or comparison with uncertain, noisy, or incomplete data, measurement error and confidence intervals can be as important for judgment as the actual mean values of different groups. These often misunderstood statistical quantities are frequently represented by bar charts with error bars. This paper investigates drawbacks with this standard encoding, and considers a set of alternatives designed to more effectively communicate the implications of mean and error data to a general audience, drawing from lessons learned from the use of visual statistics in the information visualization community. We present a series of crowd-sourced experiments that confirm that the encoding of mean and error significantly changes how viewers make decisions about uncertain data. Careful consideration of design tradeoffs in the visual presentation of data results in human reasoning that is more consistently aligned with statistical inferences. We suggest the use of gradient plots (which use transparency to encode uncertainty) and violin plots (which use width) as better alternatives for inferential tasks than bar charts with error bars.

| S-EPMC6214189 | biostudies-literature

Sensor-Based Balance Measures Outperform Modified Balance Error Scoring System in Identifying Acute Concussion.

Project description:Balance assessment is an integral component of concussion evaluation and management. Although the modified balance error scoring system (mBESS) is the conventional clinical tool, objective metrics derived from wearable inertial sensors during the mBESS may increase sensitivity in detecting subtle balance deficits post-concussion. The aim of this study was to identify which stance condition and postural sway metrics obtained from an inertial sensor placed on the lumbar spine during the mBESS best discriminate athletes with acute concussion. Fifty-two college athletes in the acute phase of concussion and seventy-six controls participated in this study. Inertial sensor-based measures objectively detected group differences in the acutely concussed group of athletes while the clinical mBESS did not (p < 0.001 and p = 0.06, respectively). Mediolateral postural sway during the simplest condition of the mBESS (double stance) best classified those with acute concussion. Inertial sensors provided a sensitive and objective measure of balance in acute concussion. These results may be developed into practical guidelines to improve and simplify postural sway analysis post-concussion.

| S-EPMC5714275 | biostudies-literature

High Dimensional Variable Selection with Error Control.

Project description:Background. The iterative sure independence screening (ISIS) is a popular method in selecting important variables while maintaining most of the informative variables relevant to the outcome in high throughput data. However, it not only is computationally intensive but also may cause high false discovery rate (FDR). We propose to use the FDR as a screening method to reduce the high dimension to a lower dimension as well as controlling the FDR with three popular variable selection methods: LASSO, SCAD, and MCP. Method. The three methods with the proposed screenings were applied to prostate cancer data with presence of metastasis as the outcome. Results. Simulations showed that the three variable selection methods with the proposed screenings controlled the predefined FDR and produced high area under the receiver operating characteristic curve (AUROC) scores. In applying these methods to the prostate cancer example, LASSO and MCP selected 12 and 8 genes and produced AUROC scores of 0.746 and 0.764, respectively. Conclusions. We demonstrated that the variable selection methods with the sequential use of FDR and ISIS not only controlled the predefined FDR in the final models but also had relatively high AUROC scores.

| S-EPMC5002494 | biostudies-literature

Between the Error Bars: How Modern Theory, Design, and Methodology Enrich the Personality-Health Tradition.

Project description:The study of relationships between personality traits and health has a long history in psychosomatic research. However, personality science has evolved from an understanding of personality as fixed traits to one that acknowledges that personality is dynamic. Dynamic approaches to conceptualizing and measuring personality and individual differences can enrich personality-health research. In this Presidential Address (American Psychosomatic Society, 2018), I consider how different formulations of personality-stable traits, stable signals in a noisy or variable measure, within-person changes, and intraindividual variability-can be implemented to better understand how personality is related to health and particularly to immune function. These approaches recognize and, in some cases, capitalize on the fact that personality factors can display variability as well as stability over time. They also require repeated measurement and therefore greater methodological sophistication that considers reliability and generalizability, Simpson's paradox, and the difference between variability and flexibility. Dynamic qualities of personality and individual differences potentially influence health, and designs and methodology that incorporate them can illuminate the important processes that occur inside the error bars.

| S-EPMC6544503 | biostudies-literature

Towards theoretical spectroscopy with error bars: systematic quantification of the structural sensitivity of calculated spectra.

Project description:Molecular spectra calculated with quantum-chemical methods are subject to a number of uncertainties (e.g., errors introduced by the computational methodology) that hamper the direct comparison of experiment and computation. Judging these uncertainties is crucial for drawing reliable conclusions from the interplay of experimental and theoretical spectroscopy, but largely relies on subjective judgment. Here, we explore the application of methods from uncertainty quantification to theoretical spectroscopy, with the ultimate goal of providing systematic error bars for calculated spectra. As a first target, we consider distortions of the underlying molecular structure as one important source of uncertainty. We show that by performing a principal component analysis, the most influential collective distortions can be identified, which allows for the construction of surrogate models that are amenable to a statistical analysis of the propagation of uncertainties in the molecular structure to uncertainties in the calculated spectrum. This is applied to the calculation of X-ray emission spectra of iron carbonyl complexes, of the electronic excitation spectrum of a coumarin dye, and of the infrared spectrum of alanine. We show that with our approach it becomes possible to obtain error bars for calculated spectra that account for uncertainties in the molecular structure. This is an important first step towards systematically quantifying other relevant sources of uncertainty in theoretical spectroscopy.

| S-EPMC8148348 | biostudies-literature

The violin heart.

Project description:Left ventricular false tendons are thin, fibromuscular structures which traverse the left ventricular cavity. They are thought to be intracavitary radiations of the bundle of His. Usually these tendons span between the interventricular septum and the lateral wall or a papillary muscle. They have been known to be a source of innocent and musical murmurs.In this case report a peculiar left ventricular false tendon is shown-one extending between the two papillary muscles, giving the appearance of a musical note. During ventricular diastole the tendon is pulled taut between the two heads of the papillary muscles and during ventricular systole the tendon relaxes. The echocardiographic characteristics and possible long term implications are discussed.

| S-EPMC2941135 | biostudies-literature

Variable Ordering Selection for Cylindrical Algebraic Decomposition with Artificial Neural Networks

Project description:Cylindrical algebraic decomposition (CAD) is a fundamental tool in computational real algebraic geometry. Previous studies have shown that machine learning (ML) based approaches may outperform traditional heuristic ones on selecting the best variable ordering when the number of variables

| S-EPMC7340889 | biostudies-literature

Morrow Plots

Project description:Morrow Plots Raw sequence reads, 2015

| PRJNA789310 | ENA

High-dimensional variable selection for ordinal outcomes with error control.

Project description:Many high-throughput genomic applications involve a large set of potential covariates and a response which is frequently measured on an ordinal scale, and it is crucial to identify which variables are truly associated with the response. Effectively controlling the false discovery rate (FDR) without sacrificing power has been a major challenge in variable selection research. This study reviews two existing variable selection frameworks, model-X knockoffs and a modified version of reference distribution variable selection (RDVS), both of which utilize artificial variables as benchmarks for decision making. Model-X knockoffs constructs a 'knockoff' variable for each covariate to mimic the covariance structure, while RDVS generates only one null variable and forms a reference distribution by performing multiple runs of model fitting. Herein, we describe how different importance measures for ordinal responses can be constructed that fit into these two selection frameworks, using either penalized regression or machine learning techniques. We compared these measures in terms of the FDR and power using simulated data. Moreover, we applied these two frameworks to high-throughput methylation data for identifying features associated with the progression from normal liver tissue to hepatocellular carcinoma to further compare and contrast their performances.

| S-EPMC7820886 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data