scholarly journals Certification or Cash Prize: The Heterogeneous Effect of Venture Competitions

2020 ◽  
Author(s):  
Gaétan de Rassenfosse ◽  
Matthias van den Heuvel
Keyword(s):  
Cash Prize ◽  
Heterogeneous Effect

The Orchard Plot: Cultivating a Forest Plot for Use in Ecology, Evolution and Beyond

2019 ◽  
Author(s):  
Shinichi Nakagawa ◽  
Malgorzata Lagisz ◽  
Rose E O'Dea ◽  
Joanna Rutkowska ◽  
Yefeng Yang ◽  
...  
Keyword(s):  
Meta Analysis ◽  
R Package ◽  
Effect Sizes ◽  
Forest Plot ◽  
Point Estimates ◽  
Aggregate Effect ◽  
The Individual ◽  
Meta Analyses ◽  
Heterogeneous Effect ◽  
Intuitive Interpretation

‘Classic’ forest plots show the effect sizes from individual studies and the aggregate effect from a meta-analysis. However, in ecology and evolution meta-analyses routinely contain over 100 effect sizes, making the classic forest plot of limited use. We surveyed 102 meta-analyses in ecology and evolution, finding that only 11% use the classic forest plot. Instead, most used a ‘forest-like plot’, showing point estimates (with 95% confidence intervals; CIs) from a series of subgroups or categories in a meta-regression. We propose a modification of the forest-like plot, which we name the ‘orchard plot’. Orchard plots, in addition to showing overall mean effects and CIs from meta-analyses/regressions, also includes 95% prediction intervals (PIs), and the individual effect sizes scaled by their precision. The PI allows the user and reader to see the range in which an effect size from a future study may be expected to fall. The PI, therefore, provides an intuitive interpretation of any heterogeneity in the data. Supplementing the PI, the inclusion of underlying effect sizes also allows the user to see any influential or outlying effect sizes. We showcase the orchard plot with example datasets from ecology and evolution, using the R package, orchard, including several functions for visualizing meta-analytic data using forest-plot derivatives. We consider the orchard plot as a variant on the classic forest plot, cultivated to the needs of meta-analysts in ecology and evolution. Hopefully, the orchard plot will prove fruitful for visualizing large collections of heterogeneous effect sizes regardless of the field of study.

GINS: A Global intensifier-based N-Gram sentiment dictionary

2021 ◽  
pp. 1-14
Author(s):  
Hamed Zargari ◽  
Morteza Zahedi ◽  
Marziea Rahimi
Keyword(s):  
Sentiment Analysis ◽  
Essential Elements ◽  
Analysis Methods ◽  
Sentiment Dictionary ◽  
N Gram ◽  
Heterogeneous Effect ◽  
Sentiment Word

Words are one of the most essential elements of expressing sentiments in context although they are not the only ones. Also, syntactic relationships between words, morphology, punctuation, and linguistic phenomena are influential. Merely considering the concept of words as isolated phenomena causes a lot of mistakes in sentiment analysis systems. So far, a large amount of research has been conducted on generating sentiment dictionaries containing only sentiment words. A number of these dictionaries have addressed the role of combinations of sentiment words, negators, and intensifiers, while almost none of them considered the heterogeneous effect of the occurrence of multiple linguistic phenomena in sentiment compounds. Regarding the weaknesses of the existing sentiment dictionaries, in addressing the heterogeneous effect of the occurrence of multiple intensifiers, this research presents a sentiment dictionary based on the analysis of sentiment compounds including sentiment words, negators, and intensifiers by considering the multiple intensifiers relative to the sentiment word and assigning a location-based coefficient to the intensifier, which increases the covered sentiment phrase in the dictionary, and enhanced efficiency of proposed dictionary-based sentiment analysis methods up to 7% compared to the latest methods.

Heterogeneous effect of leucotriene CysLT1receptor antagonists on antigen-induced motor and inflammatory responses in guinea-pig airways

2007 ◽  
Vol 27 (1) ◽  
pp. 39-46 ◽  
Author(s):  
A. B. Alfieri ◽  
M. Tramontana ◽  
C. Cialdai ◽  
A. Lecci ◽  
S. Giuliani ◽  
...  
Keyword(s):  
Guinea Pig ◽  
Inflammatory Responses ◽  
Heterogeneous Effect

scholarly journals The Heterogeneous Effect of Affirmative Action on Performance

2018 ◽  
Author(s):  
Anat Bracha ◽  
Alma Cohen ◽  
Lynn Conell-Price
Keyword(s):  
Affirmative Action ◽  
Heterogeneous Effect

CHILD NUTRITIONAL STATUS IN EGYPT: A COMPREHENSIVE ANALYSIS OF SOCIOECONOMIC DETERMINANTS USING A QUANTILE REGRESSION APPROACH

2018 ◽  
Vol 51 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Mesbah Fathy Sharaf ◽  
Elhussien Ibrahim Mansour ◽  
Ahmed Shoukry Rashad
Keyword(s):  
Nutritional Status ◽  
Quantile Regression ◽  
Low Income ◽  
Child Growth ◽  
Social Characteristics ◽  
Socioeconomic Determinants ◽  
Socioeconomic Gradient ◽  
Regression Approach ◽  
Heterogeneous Effect ◽  
Child Nutritional Status

SummaryThis study examined the underlying demographic and socioeconomic determinants of child nutritional status in Egypt using data from the most recent round of the Demographic and Health Survey. The height-for-age Z-score (HAZ) was used as a measure of child growth. A quantile regression approach was used to allow for a heterogeneous effect of each determinant along different percentiles of the conditional distribution of the HAZ. A nationally representative sample of 13,682 children aged 0–4 years was drawn from the 2014 Egypt DHS. The multivariate analyses included a set of HAZ determinants commonly used in the literature. The conditional and unconditional analyses revealed a socioeconomic gradient in child nutritional status, in which children of low income/education households have a worse HAZ than those from high income/education households. The results also showed significant disparities in child nutritional status by demographic and social characteristics. The quantile regression results showed that the association between the demographic and socioeconomic factors and HAZ differed along the conditional HAZ distribution. Intervention measures need to consider the heterogeneous effect of the determinants of child nutritional status along the different percentiles of the HAZ distribution. There is no one-size-fits-all policy to combat child malnutrition; a multifaceted approach and targeted policy interventions are required to address this problem effectively.

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