Fetching the paper…
Reading the bibliography…
There is abundant observational data in the software engineering domain, whereas running large-scale controlled experiments is often practically impossible.
Graphical criteria for efficient total effect estimation via adjustment in causal linear models
Leonard Henckel, Emilija Perković, and Marloes H. Maathuis · 1907
Earlier work this paper cites.
Estimating causal effects of treatments in randomized and nonrandomized studies
Donald B Rubin · 1974
Earlier work this paper cites.
The earth is round ( p < .05 p<.05 )
Jacob Cohen · 1994
Earlier work this paper cites.
The role of competitions in education
Tom Verhoeff · 1997
Earlier work this paper cites.
Toward evidence-based medical statistics. 1: The p p value fallacy
Steven N. Goodman · 1999
Earlier work this paper cites.
An empirical comparison of seven programming languages
Lutz Prechelt · 2000
Earlier work this paper cites.
Probability theory: The logic of science
Edwin T. Jaynes · 2003
Earlier work this paper cites.
Software engineering body of knowledge
Alain Abran, James W Moore, Pierre Bourque, Robert Dupuis, and L Tripp · 2004
Earlier work this paper cites.
Of beauty, sex and power
Andrew Gelman and David Weakliem · 2009
Earlier work this paper cites.
Causal inference in statistics: An overview
Judea Pearl · 2009
Earlier work this paper cites.
Causality
Judea Pearl · 2009
Earlier work this paper cites.
Causality: Models, reasoning and inference
Judea Pearl · 2009
Earlier work this paper cites.
Causal inference for statistical fault localization
George K Baah, Andy Podgurski, and Mary Jean Harrold · 2010
Earlier work this paper cites.
An experiment about static and dynamic type systems: Doubts about the positive impact of static type systems on development time
Stefan Hanenberg · 2010
Earlier work this paper cites.
Is transactional programming actually easier?
Christopher J. Rossbach, Owen S. Hofmann, and Emmett Witchel · 2010
Earlier work this paper cites.
Survey on informatics competitions: Developing tasks
Lasse Hakulinen · 2011
Earlier work this paper cites.
Design of an empirical study for comparing the usability of concurrent programming languages
Sebastian Nanz, Faraz Torshizi, Michela Pedroni, and Bertrand Meyer · 2011
Earlier work this paper cites.
The mathematics of causal inference
Judea Pearl · 2011
Earlier work this paper cites.
False-positive psychology
Joseph P. Simmons, Leif D. Nelson, and Uri Simonsohn · 2011
Earlier work this paper cites.
Empirical analysis of programming language adoption
Leo A. Meyerovich and Ariel S. Rabkin · 2013
Earlier work this paper cites.
A comparative study of programming languages in Rosetta Code
Sebastian Nanz and Carlo A. Furia · 2014
Earlier work this paper cites.
A large scale study of programming languages and code quality in Github
Baishakhi Ray, Daryl Posnett, Vladimir Filkov, and Premkumar Devanbu · 2014
Cited alongside, same era.
Programmers’ build errors: a case study (at Google)
Hyunmin Seo, Caitlin Sadowski, Sebastian G. Elbaum, Edward Aftandilian, and Robert W. Bowdidge · 2014
Cited alongside, same era.
Hip fracture in the elderly: a re-analysis of the epidos study with causal bayesian networks
Pascal Caillet, Sarah Klemm, Michel Ducher, Alexandre Aussem, and Anne-Marie Schott · 2015
Cited alongside, same era.
A modification of the halpern-pearl definition of causality
Joseph Halpern · 2015
Cited alongside, same era.
A comparative study of programming languages in Rosetta Code
Sebastian Nanz and Carlo A. Furia · 2015
Cited alongside, same era.
The problems with p p -values are not just with p p -values
Andrew Gelman · 2016
The seven tools of causal inference, with reflections on machine learning
Judea Pearl · 2019
Later among the works it cites.
Regression and other stories
Andrew Gelman, Jennifer Hill, and Aki Vehtari · 2020
Later among the works it cites.
Potential outcome and directed acyclic graph approaches to causality: Relevance for empirical practice in economics
Guido W. Imbens · 2020
Later among the works it cites.
Statistical rethinking: A Bayesian course with examples in R and Stan
Richard McElreath · 2020
Later among the works it cites.
Improving the accuracy of medical diagnosis with causal machine learning
Jonathan G Richens, Ciarán M Lee, and Saurabh Johri · 2020
Later among the works it cites.
We should be cautious about associations of patient characteristics with COVID-19 outcomes that are identified in hospitalised patients
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Why I prefer 50% rather than 95% intervals
Andrew Gelman · 2016
Cited alongside, same era.
Causal discovery and inference: concepts and recent methodological advances
Peter Spirtes and Kun Zhang · 2016
Cited alongside, same era.
The ASA statement on p p -values: Context, process, and purpose
Ronald L. Wasserstein and Nicole A. Lazar · 2016
Cited alongside, same era.
Comparing programming languages in Google Code Jam
Alexandra Back and Emma Westman · 2017
Cited alongside, same era.
Elements of causal inference: foundations and learning algorithms
Jonas Peters, Dominik Janzing, and Bernhard Schölkopf · 2017
Cited alongside, same era.
Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC
Aki Vehtari, Andrew Gelman, and Jonah Gabry · 2017
Cited alongside, same era.
Jonathan Sterne · 2020
Later among the works it cites.
Causal program dependence analysis
Seongmin Lee, Dave Binkley, Robert Feldt, Nicolas Gold, and Shin Yoo · 2021
Later among the works it cites.
An empirical study of linespots: A novel past-fault algorithm
Maximilian Scholz and Richard Torkar · 2021
Later among the works it cites.
A method to assess and argue for practical significance in software engineering
Richard Torkar, Carlo A. Furia, Robert Feldt, Francisco Gomes de Oliveira Neto, Lucas Gren, Per Lenberg, and Neil A. Ernst · 2021
Later among the works it cites.
A crash course in good and bad controls
Carlos Cinelli, Andrew Forney, and Judea Pearl · 2022
Later among the works it cites.
Testing causality in scientific modelling software
Andrew G Clark, Michael Foster, Benedikt Prifling, Neil Walkinshaw, Robert M Hierons, Volker Schmidt, and Robert D Turner · 2022
Later among the works it cites.
Causality in configurable software systems
Clemens Dubslaff, Kallistos Weis, Christel Baier, and Sven Apel · 2022
Later among the works it cites.
“This is damn slick!” Estimating the impact of tweets on open source project popularity and new contributors
Hongbo Fang, Hemank Lamba, James Herbsleb, and Bogdan Vasilescu · 2022
Later among the works it cites.
Applying Bayesian analysis guidelines to empirical software engineering data: The case of programming languages and code quality
Carlo A. Furia, Richard Torkar, and Robert Feldt · 2022
Later among the works it cites.
Structural causal models as boundary objects in ai system development
Hans-Martin Heyn and Eric Knauss · 2022
Later among the works it cites.
Bayesian causal inference in automotive software engineering and online evaluation
Yuchu Liu, David Issa Mattos, Jan Bosch, Helena Holmström Olsson, and Jonn Lantz · 2022
Later among the works it cites.
Maximilian Scholz and Paul-Christian Bürkner · 2022
Later among the works it cites.
Applications of statistical causal inference in software engineering
Julian Siebert · 2022
Later among the works it cites.
Replication package
Carlo A. Furia, Richard Torkar, and Robert Feldt · 2023
Closest in time.
Selection bias due to conditioning on a collider
Miguel A Hernán and Susana Monge · 2023
Closest in time.