{"repo":"mikenguyen13/data_analysis","free":true,"listed":false,"github":"https://github.com/mikenguyen13/data_analysis","clone":"git clone https://github.com/mikenguyen13/data_analysis.git","description":"Streamline a data analysis process. A book on data analysis, causal inference, and econometrics, written for readers with little to no prior background who want to develop both statistical intuition and practical R skills.","language":"Stata","stars":94,"topics":["causal-analysis","causal-inference","causal-models","causality","data-science","data-visualization","datascience","guide","guidebook","machine-learning"],"license":null,"category":"machine-learning","readme_excerpt":"A Guide on Data Analysis A book on data analysis, causal inference, and econometrics, written for readers with little to no prior background who want to develop both statistical intuition and practical R skills. The print edition is published by Springer Cham as a four-volume series, and this repository hosts the open online edition that the print volumes are drawn from. Read it online : What the book covers The online edition runs from descriptive statistics through inference, regression, and causal inference, with a strong emphasis on the methods that have come to define modern empirical practice. Foundations : descriptive statistics, basic inference, hypothesis testing, sampling, ANOVA. Regression : OLS, GLS, MLE, penalized, robust, partial least squares. Generalized linear and mixed models : logistic, count, hierarchical. Modeling workflow : variable transformation, imputation, model specification, variable selection. Effects and decomposition : marginal effects, moderation, mediation, prediction vs. estimation. Causal inference : difference-in-differences with the modern staggered estimators (Goodman-Bacon, Callaway-Sant'Anna, Sun-Abraham, de Chaisemartin-D'Haultfoeuille, Borusyak-Jaravel-Spiess), regression discontinuity (incl. rdrobust ), interrupted time series, synthetic control, synthetic DiD, changes-in-changes, event studies, instrumental variables (incl. examiner designs and proxies), matching, and DAGs. Sensitivity and robustness : specification curves, Oster co","default_branch":null,"files":null,"tree":[],"storefront":"/r/mikenguyen13","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/mikenguyen13/data_analysis/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}