Achieving Statistical Significance with Control Variables and Without Transparency

[1]  Gary King,et al.  Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference , 2007, Political Analysis.

[2]  Christopher R. Taber,et al.  An Evaluation of Instrumental Variable Strategies for Estimating the Effects of Catholic Schooling , 2002, The Journal of Human Resources.

[3]  Jennifer Hill,et al.  Bias Amplification and Bias Unmasking , 2016, Political Analysis.

[4]  Jens Hainmueller,et al.  Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies , 2012, Political Analysis.

[5]  Nicholas J. L. Brown,et al.  Simpson’s Paradox is suppression, but Lord’s Paradox is neither: clarification of and correction to Tu, Gunnell, and Gilthorpe (2008) , 2019, Emerging Themes in Epidemiology.

[6]  Jasjeet S. Sekhon,et al.  Multivariate and Propensity Score Matching Software with Automated Balance Optimization: The Matching Package for R , 2008 .

[7]  Alan S. Gerber,et al.  Do Statistical Reporting Standards Affect What Is Published? Publication Bias in Two Leading Political Science Journals , 2008 .

[8]  Reginald B. Adams,et al.  Investigating Variation in Replicability: A “Many Labs” Replication Project , 2014 .

[9]  Larry M. Bartels Specification Uncertainty and Model Averaging , 1997 .

[10]  P. Bobko Correlation and Regression: Applications for Industrial Organizational Psychology and Management , 2001 .

[11]  J. Ioannidis Why Most Published Research Findings Are False , 2005, PLoS medicine.

[12]  Christopher H. Achen TOWARD A NEW POLITICAL METHODOLOGY: Microfoundations and ART , 2002 .

[13]  Jay Bhattacharya,et al.  Do Instrumental Variables Belong in Propensity Scores? , 2007 .

[14]  S. Cole,et al.  Illustrating bias due to conditioning on a collider. , 2010, International journal of epidemiology.

[15]  Avishai Henik,et al.  SUPPRESSION SITUATIONS IN PSYCHOLOGICAL RESEARCH : DEFINITIONS, IMPLICATIONS, AND APPLICATIONS , 1991 .

[16]  T. Davenport Policy‐Induced Risk and Responsive Participation: The Effect of a Son's Conscription Risk on the Voting Behavior of His Parents , 2015 .

[17]  J. Wooldridge Should Instrumental Variables be Used as Matching Variables , 2016 .

[18]  G. Imbens,et al.  Approximate residual balancing: debiased inference of average treatment effects in high dimensions , 2016, 1604.07125.

[19]  Abel Brodeur,et al.  Star Wars: The Empirics Strike Back , 2012, SSRN Electronic Journal.

[20]  Edward Miguel,et al.  Reshaping Institutions: Evidence on Aid Impacts Using a Pre-Analysis Plan , 2011 .

[21]  J. Pearl Invited commentary: understanding bias amplification. , 2011, American journal of epidemiology.

[22]  A. Gerber,et al.  Publication Bias in Two Political Behavior Literatures , 2010 .

[23]  David Gal,et al.  Abandon Statistical Significance , 2017, The American Statistician.

[24]  D. Mackinnon,et al.  Equivalence of the Mediation, Confounding and Suppression Effect , 2000, Prevention Science.

[25]  John P. A. Ioannidis,et al.  The Power of Bias in Economics Research , 2017 .

[26]  Kevin A. Clarke The Phantom Menace: Omitted Variable Bias in Econometric Research , 2005 .

[27]  Edward E. Leamer,et al.  Let's Take the Con Out of Econometrics , 1983 .

[28]  A. J. Conger A Revised Definition for Suppressor Variables: a Guide To Their Identification and Interpretation , 1974 .

[29]  H. Holling Suppressor Structures in the General Linear Model , 1983 .

[30]  Jacob M. Montgomery,et al.  Bayesian Model Averaging: Theoretical Developments and Practical Applications , 2010, Political Analysis.

[31]  Edward E. Leamer,et al.  S-values: Conventional context-minimal measures of the sturdiness of regression coefficients , 2016 .

[32]  K. Imai,et al.  Covariate balancing propensity score , 2014 .

[33]  R. Glynn,et al.  Reducing Bias Amplification in the Presence of Unmeasured Confounding through Out-of-Sample Estimation Strategies for the Disease Risk Score , 2014, Journal of causal inference.

[34]  E. Oster Unobservable Selection and Coefficient Stability: Theory and Evidence , 2019 .

[35]  Reginald B. Adams,et al.  Many Labs 2: Investigating Variation in Replicability Across Sample and Setting , 2018 .

[36]  Macartan Humphreys,et al.  Fishing, Commitment, and Communication: A Proposal for Comprehensive Nonbinding Research Registration , 2012, Political Analysis.