bibliography.bib

@book{sheather_modern_2009,
	address = {New York},
	series = {Springer {Texts} in {Statistics}},
	title = {A {Modern} {Approach} to {Regression} with {R}},
	isbn = {978-0-387-09607-0},
	url = {https://www.springer.com/gp/book/9780387096070},
	language = {en},
	publisher = {Springer-Verlag},
	author = {Sheather, Simon},
	year = {2009},
	doi = {10.1007/978-0-387-09608-7}
}

@article{cameron_practitioners_2013,
	title = {A {Practitioner}'s {Guide} to {Cluster}-{Robust} {Inference}},
	language = {en},
	author = {Cameron, A Colin and Miller, Douglas L},
	pages = {60},
	year = {2013},
	url = {http://cameron.econ.ucdavis.edu/research/Cameron_Miller_Cluster_Robust_October152013.pdf}
}

@article{zeileis_various_2020,
	title = {Various {Versatile} {Variances}: {An} {Object}-{Oriented} {Implementation} of {Clustered} {Covariances} in \textit{{R}}},
	volume = {95},
	issn = {1548-7660},
	shorttitle = {Various {Versatile} {Variances}},
	url = {http://www.jstatsoft.org/v95/i01/},
	doi = {10.18637/jss.v095.i01},
	abstract = {This introduction to the object-oriented implementation of clustered covariances in the R package sandwich is a (slightly) modified version of Zeileis, Köll, and Graham (2020), published in the Journal of Statistical Software.},
	language = {en},
	number = {1},
	urldate = {2021-03-30},
	journal = {Journal of Statistical Software},
	author = {Zeileis, Achim and Köll, Susanne and Graham, Nathaniel},
	year = {2020}
}

@misc{roberts_robust_2013,
	title = {Robust and {Clustered} {Standard} {Errors}},
	language = {en},
	author = {Roberts, Molly},
	year = {2013},
	url = {https://projects.iq.harvard.edu/files/gov2001/files/sesection_5.pdf},
}

@misc{sonnet_mathematical_2019,
	title = {Mathematical notes for estimatr},
	url = {https://declaredesign.org/r/estimatr/articles/mathematical-notes.html#cluster-robust-variance-and-degrees-of-freedom},
	author = {Sonnet, Luke},
	language = {en},
	urldate = {2021-04-19},
	year = {2019}
}


@article{blair_declaring_2019,
	title = {Declaring and {Diagnosing} {Research} {Designs}},
	volume = {113},
	issn = {0003-0554, 1537-5943},
	url = {https://www.cambridge.org/core/journals/american-political-science-review/article/declaring-and-diagnosing-research-designs/3CB0C0BB0810AEF8FF65446B3E2E4926},
	doi = {10.1017/S0003055419000194},
	abstract = {Researchers need to select high-quality research designs and communicate those designs clearly to readers. Both tasks are difficult. We provide a framework for formally “declaring” the analytically relevant features of a research design in a demonstrably complete manner, with applications to qualitative, quantitative, and mixed methods research. The approach to design declaration we describe requires defining a model of the world (M), an inquiry (I), a data strategy (D), and an answer strategy (A). Declaration of these features in code provides sufficient information for researchers and readers to use Monte Carlo techniques to diagnose properties such as power, bias, accuracy of qualitative causal inferences, and other “diagnosands.” Ex ante declarations can be used to improve designs and facilitate preregistration, analysis, and reconciliation of intended and actual analyses. Ex post declarations are useful for describing, sharing, reanalyzing, and critiquing existing designs. We provide open-source software, DeclareDesign, to implement the proposed approach.},
	language = {en},
	number = {3},
	urldate = {2021-04-30},
	journal = {American Political Science Review},
	author = {Blair, Graeme and Cooper, Jasper and Coppock, Alexander and Humphreys, Macartan},
	month = aug,
	year = {2019},
	note = {Publisher: Cambridge University Press},
	pages = {838--859},
	file = {Full Text PDF:/home/mkonrad/Zotero/storage/8WAJKGC8/Blair et al. - 2019 - Declaring and Diagnosing Research Designs.pdf:application/pdf;Snapshot:/home/mkonrad/Zotero/storage/H476BHIL/3CB0C0BB0810AEF8FF65446B3E2E4926.html:text/html}
}