Journal ArticleDOI
Research Commentary---Too Big to Fail: Large Samples and the p-Value Problem
TLDR
This research commentary recommends a series of actions the researcher can take to mitigate the p-value problem in large samples and illustrates them with an example of over 300,000 camera sales on eBay.Abstract:
The Internet has provided IS researchers with the opportunity to conduct studies with extremely large samples, frequently well over 10,000 observations. There are many advantages to large samples, but researchers using statistical inference must be aware of the p-value problem associated with them. In very large samples, p-values go quickly to zero, and solely relying on p-values can lead the researcher to claim support for results of no practical significance. In a survey of large sample IS research, we found that a significant number of papers rely on a low p-value and the sign of a regression coefficient alone to support their hypotheses. This research commentary recommends a series of actions the researcher can take to mitigate the p-value problem in large samples and illustrates them with an example of over 300,000 camera sales on eBay. We believe that addressing the p-value problem will increase the credibility of large sample IS research as well as provide more insights for readers.read more
Citations
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Journal ArticleDOI
The value of political connections in the post-transition period: evidence from Czechia
TL;DR: The authors studied the relationship between political connections and reported profits using a newly compiled dataset on all corporate donations to political parties in Czechia during its post-transition period (between 1995 and 2014).
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Data Aggregation and Demand Prediction
TL;DR: This paper analytically shows that the DAC yields a consistent estimate along with improved asymptotic properties relative to the traditional ordinary least squares method that treats different items in a decentralized fashion.
Journal ArticleDOI
A Robust Approach for Identifying the Major Components of the Bribery Tolerance Index
TL;DR: A methodology for exploring and validating the most important predictors of the risk associated with bribery tolerance, and found the significant role of three influences corresponding to questions about attitudes towards the property, authority, and public services, and other people in terms of anti-cheating, anti-evasion, and anti-violence.
Journal ArticleDOI
Crystalline structure and grain boundary identification in nanocrystalline aluminum using K-means clustering
Journal ArticleDOI
Revisiting the T2 spectrum imaging inverse problem: Bayesian regularized non-negative least squares.
Erick J. Canales-Rodríguez,Marco Pizzolato,Marco Pizzolato,Thomas Yu,Thomas Yu,Gian Franco Piredda,Gian Franco Piredda,Gian Franco Piredda,Tom Hilbert,Tom Hilbert,Tom Hilbert,Joaquim Radua,Joaquim Radua,Tobias Kober,Tobias Kober,Tobias Kober,Jean-Philippe Thiran,Jean-Philippe Thiran +17 more
TL;DR: In this article, a new Bayesian regularized non-negative least squares (NNLS) method (BayesReg) was proposed to estimate the myelin water fraction (MWF) from multi-echo T2 magnetic resonance images.
References
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Journal ArticleDOI
Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets
TL;DR: In this paper, the authors used a unique data set based on both chronologically compiled ratings as well as reviewer characteristics for a given set of products and geographical location-based purchasing behavior from Amazon, and provided evidence that community norms are an antecedent to reviewer disclosure of identity-descriptive information.
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