Models as approximations-rejoinder

3Citations
Citations of this article
11Readers
Mendeley users who have this article in their library.

Abstract

We respond to the discussants of our articles emphasizing the importance of inference under misspecification in the context of the reproducibility/replicability crisis. Along the way, we discuss the roles of diagnostics and model building in regression as well as connections between our well-specification framework and semiparametric theory.

References Powered by Scopus

False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant

4788Citations
N/AReaders
Get full text

Strictly proper scoring rules, prediction, and estimation

3454Citations
N/AReaders
Get full text

Estimating optimal transformations for multiple regression and correlation

1259Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Assumption-lean inference for generalised linear model parameters

24Citations
N/AReaders
Get full text

Incorporating Machine Learning into Sociological Model-Building

1Citations
N/AReaders
Get full text

Doubly robust estimation under a possibly misspecified marginal structural Cox model

0Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Buja, A., Kuchibhotla, A. K., Berk, R., George, E., Tchetgen, E. T., & Zhao, L. (2019). Models as approximations-rejoinder. Statistical Science, 34(4), 606–620. https://doi.org/10.1214/19-STS762

Readers over time

‘20‘21‘23036912

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 5

56%

Professor / Associate Prof. 2

22%

Lecturer / Post doc 1

11%

Researcher 1

11%

Readers' Discipline

Tooltip

Medicine and Dentistry 3

50%

Physics and Astronomy 1

17%

Psychology 1

17%

Economics, Econometrics and Finance 1

17%

Save time finding and organizing research with Mendeley

Sign up for free
0