Choosing Prediction Over Explanation in Psychology: Lessons From Machine Learning
暂无分享,去创建一个
[1] A. K. Kurtz. A Research Test of the Rorschach Test , 1948 .
[2] R. Wherry. IV. Comparison of Cross-Validation with Statistical Inference of Betas and Multiple R From a Single Sample , 1951 .
[3] C. I. Mosier. I. Problems and Designs of Cross-Validation 1 , 1951 .
[4] Jacob Cohen,et al. The statistical power of abnormal-social psychological research: a review. , 1962, Journal of abnormal and social psychology.
[5] R. Wherry. Underprediction from Overfitting: 45 years of Shrinkage. , 1975 .
[6] Jacob Cohen,et al. Applied multiple regression/correlation analysis for the behavioral sciences , 1979 .
[7] Howard Wainer,et al. Estimating Coefficients in Linear Models: It Don't Make No Nevermind , 1976 .
[8] Neal Schmitt,et al. A Monte Carlo evaluation of three formula estimates of cross-validated multiple correlation. , 1977 .
[9] R. Dawes. Judgment under uncertainty: The robust beauty of improper linear models in decision making , 1979 .
[10] P. Meehl. Why Summaries of Research on Psychological Theories are Often Uninterpretable , 1990 .
[11] Michael R. Hagerty,et al. Comparing the predictive powers of alternative multiple regression models , 1991 .
[12] Jacob Cohen,et al. A power primer. , 1992, Psychological bulletin.
[13] P. Ekman. An argument for basic emotions , 1992 .
[14] J. Shao. Linear Model Selection by Cross-validation , 1993 .
[15] K. Lesch,et al. Association of Anxiety-Related Traits with a Polymorphism in the Serotonin Transporter Gene Regulatory Region , 1996, Science.
[16] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[17] R. Ebstein,et al. Dopamine D4 receptor (D4DR) exon III polymorphism associated with the human personality trait of Novelty Seeking , 1996, Nature Genetics.
[18] D. Rawlings,et al. Music Preference and the Five-Factor Model of the NEO Personality Inventory , 1997 .
[19] David H. Wolpert,et al. No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..
[20] C. Apte,et al. Data mining with decision trees and decision rules , 1997, Future Gener. Comput. Syst..
[21] J. Desmond,et al. Making memories: brain activity that predicts how well visual experience will be remembered. , 1998, Science.
[22] J. Pennebaker,et al. Linguistic styles: language use as an individual difference. , 1999, Journal of personality and social psychology.
[23] L. Arseneault,et al. Impulsivity predicts problem gambling in low SES adolescent males. , 1999, Addiction.
[24] Browne,et al. Cross-Validation Methods. , 2000, Journal of mathematical psychology.
[25] J. Friedman. Greedy function approximation: A gradient boosting machine. , 2001 .
[26] V. Carey,et al. Mixed-Effects Models in S and S-Plus , 2001 .
[27] Leo Breiman,et al. Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author) , 2001 .
[28] Leo Breiman,et al. Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author) , 2001, Statistical Science.
[29] R. L. Holbert,et al. Structural Equation Modeling in the Communication Sciences, 1995–2000 , 2002 .
[30] R. MacCallum,et al. When fit indices and residuals are incompatible. , 2002, Psychological methods.
[31] S. Gosling,et al. PERSONALITY PROCESSES AND INDIVIDUAL DIFFERENCES The Do Re Mi’s of Everyday Life: The Structure and Personality Correlates of Music Preferences , 2003 .
[32] Elizabeth A. Olson,et al. Eyewitness testimony. , 2003, Annual review of psychology.
[33] Eric R. Ziegel,et al. The Elements of Statistical Learning , 2003, Technometrics.
[34] Gerd Gigerenzer,et al. Do Studies of Statistical Power Have an Effect on the Power of Studies? , 2004 .
[35] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[36] S. Gosling,et al. Personality Processes and Individual Differences E-perceptions: Personality Impressions Based on Personal Websites , 2022 .
[37] Marc Brysbaert,et al. Lexique 2 : A new French lexical database , 2004, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.
[38] David R. Anderson,et al. Understanding AIC and BIC in Model Selection , 2004 .
[39] Richard Simon,et al. Bias in error estimation when using cross-validation for model selection , 2006, BMC Bioinformatics.
[40] Michael J Strube,et al. SNOOP: A program for demonstrating the consequences of premature and repeated null hypothesis testing , 2006, Behavior research methods.
[41] Alan Y. Chiang,et al. Generalized Additive Models: An Introduction With R , 2007, Technometrics.
[42] Rebecca Treiman,et al. The English Lexicon Project , 2007, Behavior research methods.
[43] J. Ioannidis. Why Most Discovered True Associations Are Inflated , 2008, Epidemiology.
[44] D. Funder,et al. Personality as manifest in word use: correlations with self-report, acquaintance report, and behavior. , 2008, Journal of personality and social psychology.
[45] D. Balota,et al. Moving beyond Coltheart’s N: A new measure of orthographic similarity , 2008, Psychonomic bulletin & review.
[46] J. Ioannidis,et al. Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias , 2008, PloS one.
[47] Thomas J. Harris,et al. The use of simplified or misspecified models : Linear case , 2008 .
[48] Marc Brysbaert,et al. Moving beyond Kučera and Francis: A critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English , 2009, Behavior research methods.
[49] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[50] Joseph Hilbe,et al. Data Analysis Using Regression and Multilevel/Hierarchical Models , 2009 .
[51] A. Poropat. A meta-analysis of the five-factor model of personality and academic performance. , 2009, Psychological bulletin.
[52] Susan Goldin-Meadow,et al. Early gesture selectively predicts later language learning. , 2009, Developmental science.
[53] T. Yarkoni. Big Correlations in Little Studies: Inflated fMRI Correlations Reflect Low Statistical Power—Commentary on Vul et al. (2009) , 2009, Perspectives on psychological science : a journal of the Association for Psychological Science.
[54] A. Gelman,et al. Of Beauty, Sex and Power , 2009 .
[55] Marco Zorzi,et al. Beyond single syllables: Large-scale modeling of reading aloud with the Connectionist Dual Process (CDP++) model , 2010, Cognitive Psychology.
[56] Anthony D. Wagner,et al. Detecting individual memories through the neural decoding of memory states and past experience , 2010, Proceedings of the National Academy of Sciences.
[57] Christian Windischberger,et al. Toward discovery science of human brain function , 2010, Proceedings of the National Academy of Sciences.
[58] Tal Yarkoni. Personality in 100,000 Words: A large-scale analysis of personality and word use among bloggers. , 2010, Journal of research in personality.
[59] Juliane M. Stopfer,et al. Facebook Profiles Reflect Actual Personality, Not Self-Idealization , 2010, Psychological science.
[60] Gavin C. Cawley,et al. On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation , 2010, J. Mach. Learn. Res..
[61] Marcus R. Munafò,et al. Dissecting the genetic architecture of human personality , 2011, Trends in Cognitive Sciences.
[62] Dušica Filipović Đurđević,et al. An amorphous model for morphological processing in visual comprehension based on naive discriminative learning. , 2011, Psychological review.
[63] Samuel D. Gosling,et al. Manifestations of Personality in Online Social Networks: Self-Reported Facebook-Related Behaviors and Observable Profile Information , 2011, Cyberpsychology Behav. Soc. Netw..
[64] R. Tibshirani,et al. Regression shrinkage and selection via the lasso: a retrospective , 2011 .
[65] Galit Shmueli,et al. To Explain or To Predict? , 2010, 1101.0891.
[66] Hernando Ombao,et al. Penalized least squares regression methods and applications to neuroimaging , 2011, NeuroImage.
[67] Han L. J. van der Maas,et al. Science Perspectives on Psychological an Agenda for Purely Confirmatory Research on Behalf Of: Association for Psychological Science , 2022 .
[68] Cameron Marlow,et al. A 61-million-person experiment in social influence and political mobilization , 2012, Nature.
[69] Pedro M. Domingos. A few useful things to know about machine learning , 2012, Commun. ACM.
[70] Daragh E. Sibley,et al. Individual Differences in Visual Word Recognition: Insights from the English Lexicon Project , 2012 .
[71] G. Loewenstein,et al. Measuring the Prevalence of Questionable Research Practices With Incentives for Truth Telling , 2012, Psychological science.
[72] Jeffrey R. Spies,et al. Scientific Utopia: II. Restructuring incentives and practices to promote truth over publishability , 2012, 1205.4251.
[73] H. Beek. F1000Prime recommendation of False-positive psychology: undisclosed flexibility in data collection and analysis allows presenting anything as significant. , 2012 .
[74] A. Greenwald. PSS 7210 . 1177 / 1745691611434210 GreenwaldMethod – Theory Synergy There Is Nothing So Theoretical as a Good Method , 2012 .
[75] T. Yarkoni. Psychoinformatics: New Horizons at the Interface of the Psychological and Computing Sciences , 2012 .
[76] J. Wicherts,et al. The Rules of the Game Called Psychological Science , 2012, Perspectives on psychological science : a journal of the Association for Psychological Science.
[77] S. Vrieze. Model selection and psychological theory: a discussion of the differences between the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). , 2012, Psychological methods.
[78] J. Ioannidis. Why Science Is Not Necessarily Self-Correcting , 2012, Perspectives on psychological science : a journal of the Association for Psychological Science.
[79] G. Miller,et al. Science Perspectives on Psychological the Smartphone Psychology Manifesto on Behalf Of: Association for Psychological Science the Smartphone Psychology Manifesto Previous Research Using Mobile Electronic Devices What Smartphones Can Do Now and Will Be Able to Do in the near Future , 2022 .
[80] C. Gamble,et al. Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias — An Updated Review , 2013, PloS one.
[81] Arthur W. Toga,et al. Human neuroimaging as a “Big Data” science , 2013, Brain Imaging and Behavior.
[82] Essa Yacoub,et al. The WU-Minn Human Connectome Project: An overview , 2013, NeuroImage.
[83] T. Graepel,et al. Private traits and attributes are predictable from digital records of human behavior , 2013, Proceedings of the National Academy of Sciences.
[84] N. Wray,et al. A mega-analysis of genome-wide association studies for major depressive disorder , 2013, Molecular Psychiatry.
[85] Rob Fergus,et al. Visualizing and Understanding Convolutional Networks , 2013, ECCV.
[86] Brian A. Nosek,et al. Registered Reports A Method to Increase the Credibility of Published Results , 2014 .
[87] Yong Tao,et al. Compound facial expressions of emotion , 2014, Proceedings of the National Academy of Sciences.
[88] David J. Fleet,et al. Computer Vision – ECCV 2014 , 2014, Lecture Notes in Computer Science.
[89] Anthony G. Greenwald,et al. Psychology data from the Race Implicit Association Test on the Project Implicit Demo website , 2014 .
[90] M. J. O’Brien,et al. Mapping collective behavior in the big-data era , 2014, Behavioral and Brain Sciences.
[91] D. A. Kenny,et al. Statistical power and optimal design in experiments in which samples of participants respond to samples of stimuli. , 2014, Journal of experimental psychology. General.
[92] M. Rietschel,et al. Neuropsychosocial profiles of current and future adolescent alcohol misusers , 2014, Nature.
[93] Ljubomir J. Buturovic,et al. Cross-validation pitfalls when selecting and assessing regression and classification models , 2014, Journal of Cheminformatics.
[94] Ross M. Fraser,et al. Defining the role of common variation in the genomic and biological architecture of adult human height , 2014, Nature Genetics.
[95] Reginald B. Adams,et al. Investigating Variation in Replicability: A “Many Labs” Replication Project , 2014 .
[96] J. Dana,et al. Comparing the accuracy of experimental estimates to guessing: a new perspective on replication and the “Crisis of Confidence” in psychology , 2013, Behavior Research Methods.
[97] Jürgen Schmidhuber,et al. Deep learning in neural networks: An overview , 2014, Neural Networks.
[98] Yoni K. Ashar,et al. Interactions between donor Agreeableness and recipient characteristics in predicting charitable donation and positive social evaluation , 2015, PeerJ.
[99] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[100] Daniel M McNeish,et al. Using Lasso for Predictor Selection and to Assuage Overfitting: A Method Long Overlooked in Behavioral Sciences , 2015, Multivariate behavioral research.
[101] Michael C. Frank,et al. Estimating the reproducibility of psychological science , 2015, Science.
[102] Tal Yarkoni,et al. Statistically Controlling for Confounding Constructs Is Harder than You Think , 2016, PloS one.
[103] Kai J. Jonas,et al. How can preregistration contribute to research in our field , 2016 .
[104] Stuart J. Ritchie,et al. Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci , 2015, Molecular Psychiatry.
[105] J. Pell,et al. Erratum: Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci , 2016, Molecular psychiatry.
[106] Brian A. Nosek,et al. Many Labs 3: Evaluating participant pool quality across the academic semester via replication , 2016 .
[107] D. A. Kenny,et al. Experiments with More Than One Random Factor: Designs, Analytic Models, and Statistical Power , 2017, Annual review of psychology.
[108] D. Donoho. 50 Years of Data Science , 2017 .
[109] Y. Watanabe,et al. IV , 2018, Out of the Shadow.
[110] A. Gelman,et al. The garden of forking paths : Why multiple comparisons can be a problem , even when there is no “ fishing expedition ” or “ p-hacking ” and the research hypothesis was posited ahead of time ∗ , 2019 .
[111] A. Gelman,et al. Of Beauty , Sex and Power Too little attention has been paid to the statistical challenges in estimating small effects , 2022 .