book.bib

@Article{lumley2004,
    year = {2004},
    author = {Thomas Lumley},
    title = {Analysis of Complex Survey Samples},
    journal = {Journal of Statistical Software},
    volume = {9},
    number = {1},
    pages = {1-19},
    note = {R package verson 2.2},
  }
@Manual{lumleysvyvgam,
    title = {svyVGAM: Design-Based Inference in Vector Generalised Linear Models},
    author = {Thomas Lumley},
    year = {2021},
    note = {R package version 1.0},
    url = {https://CRAN.R-project.org/package=svyVGAM},
  }
@article{entwisle_2007,
	title = {Putting people into place},
	volume = {44},
	issn = {0070-3370, 1533-7790},
	url = {https://read.dukeupress.edu/demography/article/44/4/687/170005/Putting-people-into-place},
	doi = {10.1353/dem.2007.0045},
	abstract = {Abstract
            Over the past two decades, there has been an explosion of empirical research on neighborhoods and health. However, although the data and approaches owe much to the early contributions of demographers and population scientists, this debt is largely unrecognized. Likewise, challenges posed in the early literature remain largely unanswered. I argue that just as demographers and population scientists were pioneers in the study of neighborhoods and health, they are uniquely poised to lead the field again. Putting people into place means explaining behavior and outcomes in relation to a potentially changing local context. A more dynamic conceptualization is needed that fully incorporates human agency, integrates multiple dimensions of local social and spatial context, develops the necessary longitudinal data, and implements appropriate tools. Diverse approaches with complementary strengths will help surmount the many analytic challenges to studying the dynamics of neighborhoods and health, including agent-based microsimulation models.},
	language = {en},
	number = {4},
	urldate = {2022-03-07},
	journal = {Demography},
	author = {Entwisle, Barbara},
	month = nov,
	year = {2007},
	pages = {687--703},
	file = {Full Text:C\:\\Users\\ozd504\\Zotero\\storage\\3K3JLF2F\\Entwisle - 2007 - Putting people into place.pdf:application/pdf},
}

@Article{gamlss,
    title = {Generalized additive models for location, scale and shape,(with discussion)},
    journal = {Applied Statistics},
    volume = {54},
    part = {3},
    pages = {507-554},
    year = {2005},
    author = {R. A. Rigby and D. M. Stasinopoulos},
  }


@Book{venables_ripley,
    title = {Modern Applied Statistics with S},
    author = {W. N. Venables and B. D. Ripley},
    publisher = {Springer},
    edition = {Fourth},
    address = {New York},
    year = {2002},
    note = {ISBN 0-387-95457-0},
    url = {https://www.stats.ox.ac.uk/pub/MASS4/},
  }
@article{cribari-neto_beta_2010,
	title = {Beta {Regression} in \textit{{R}}},
	volume = {34},
	issn = {1548-7660},
	url = {http://www.jstatsoft.org/v34/i02/},
	doi = {10.18637/jss.v034.i02},
	language = {en},
	number = {2},
	urldate = {2022-02-25},
	journal = {Journal of Statistical Software},
	author = {Cribari-Neto, Francisco and Zeileis, Achim},
	year = {2010},
	file = {Full Text:C\:\\Users\\ozd504\\Zotero\\storage\\5VST95AV\\Cribari-Neto and Zeileis - 2010 - Beta Regression in R.pdf:application/pdf},
}

@Article{betareg,
    title = {Extended Beta Regression in {R}: Shaken, Stirred, Mixed, and Partitioned},
    author = {Bettina Gr\"un and Ioannis Kosmidis and Achim Zeileis},
    journal = {Journal of Statistical Software},
    year = {2012},
    volume = {48},
    number = {11},
    pages = {1--25},
    doi = {10.18637/jss.v048.i11},
  }
@article{breslow_extra-poisson_1984,
	title = {Extra-{Poisson} {Variation} in {Log}-{Linear} {Models}},
	volume = {33},
	issn = {00359254},
	url = {https://www.jstor.org/stable/2347661?origin=crossref},
	doi = {10.2307/2347661},
	number = {1},
	urldate = {2022-02-24},
	journal = {Applied Statistics},
	author = {Breslow, N. E.},
	year = {1984},
	pages = {38},
}

@book{pinheiro_mixed-effects_2000,
	address = {New York},
	series = {Statistics and computing},
	title = {Mixed-effects models in {S} and {S}-{PLUS}},
	isbn = {978-0-387-98957-0},
	publisher = {Springer},
	author = {Pinheiro, José C. and Bates, Douglas M.},
	year = {2000},
}

@Article{gtsummary,
    author = {Daniel D. Sjoberg and Karissa Whiting and Michael Curry and Jessica A. Lavery and Joseph Larmarange},
    title = {Reproducible Summary Tables with the gtsummary Package},
    journal = {{The R Journal}},
    year = {2021},
    url = {https://doi.org/10.32614/RJ-2021-053},
    doi = {10.32614/RJ-2021-053},
    volume = {13},
    issue = {1},
    pages = {570-580},
  }
@article{sparks_application_2010,
	title = {An application of spatially autoregressive models to the study of {US} county mortality rates: {An} {Application} of {Spatially} {Autoregressive} {Models}},
	volume = {16},
	issn = {15448444},
	shorttitle = {An application of spatially autoregressive models to the study of {US} county mortality rates},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/psp.564},
	doi = {10.1002/psp.564},
	language = {en},
	number = {6},
	urldate = {2022-02-02},
	journal = {Population, Space and Place},
	author = {Sparks, Patrice Johnelle and Sparks, Corey S.},
	month = nov,
	year = {2010},
	pages = {465--481},
}

@incollection{mclaughlin_differential_2007,
	title = {Differential mortality across the {United}    {States}: the influence of place-based inequality},
	isbn = {978-0-7914-7107-4},
	booktitle = {Sociology of {Spatial} {Inequality}},
	publisher = {State University of New York Press},
	author = {McLaughlin, Diane K. and Stokes, C. Shannon and Smith, P. Johnelle and Nonoyama, A},
	year = {2007},
	pages = {141--162},
}

@article{long_using_2000,
	title = {Using {Heteroscedasticity} {Consistent} {Standard} {Errors} in the {Linear} {Regression} {Model}},
	volume = {54},
	issn = {0003-1305, 1537-2731},
	url = {http://www.tandfonline.com/doi/abs/10.1080/00031305.2000.10474549},
	doi = {10.1080/00031305.2000.10474549},
	language = {en},
	number = {3},
	urldate = {2022-02-01},
	journal = {The American Statistician},
	author = {Long, J. Scott and Ervin, Laurie H.},
	month = aug,
	year = {2000},
	pages = {217--224},
}

@article{white_1980,
	title = {A {Heteroskedasticity}-{Consistent} {Covariance} {Matrix} {Estimator} and a {Direct} {Test} for {Heteroskedasticity}},
	volume = {48},
	issn = {00129682},
	url = {https://www.jstor.org/stable/1912934?origin=crossref},
	doi = {10.2307/1912934},
	number = {4},
	urldate = {2022-02-01},
	journal = {Econometrica},
	author = {White, Halbert},
	month = may,
	year = {1980},
	pages = {817},
}

@article{mackinnon_white_1985,
	title = {Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties},
	volume = {29},
	issn = {03044076},
	url = {https://linkinghub.elsevier.com/retrieve/pii/0304407685901587},
	doi = {10.1016/0304-4076(85)90158-7},
	language = {en},
	number = {3},
	urldate = {2022-02-01},
	journal = {Journal of Econometrics},
	author = {MacKinnon, James G and White, Halbert},
	month = sep,
	year = {1985},
	pages = {305--325},
	file = {Submitted Version:C\:\\Users\\ozd504\\Zotero\\storage\\H3I69J8W\\MacKinnon and White - 1985 - Some heteroskedasticity-consistent covariance matr.pdf:application/pdf},
}


@techreport{us_census_bureau_worked_nodate,
	title = {Worked {Examples} for {Approximating} {Standard} {Errors} {Using} {American} {Community} {Survey} {Data}},
	url = {https://www2.census.gov/programs-surveys/acs/tech_docs/accuracy/2018_ACS_Accuracy_Document_Worked_Examples.pdf},
	author = {US Census Bureau},
	year = {2019},
}

@Manual{nhgis,
title = {IPUMS National Historical Geographic Information System: Version 16.0 [dataset]},
author = { Manson, Steven and Schroeder, Jonathan and Van Riper, David and Kugler, Tracy and Ruggles, Steven},
year= {2021},
doi = {http://doi.org/10.18128/D050.V16.0},
}

@Article{rdhs,
    title = {rdhs: an R package to interact with The Demographic and Health Surveys (DHS) Program datasets},
    author = {Oliver J Watson and Rich FitzJohn and Jeffrey W Eaton},
    journal = {Wellcome Open Research},
    year = {2019},
    volume = {4},
    pages = {103},
    url = {https://wellcomeopenresearch.org/articles/4-103/v1},
    doi = {10.12688/wellcomeopenres.15311.1},
  }
@Manual{tigris,
    title = {tigris: Load Census TIGER/Line Shapefiles},
    author = {Kyle Walker},
    year = {2021},
    note = {R package version 1.4.1},
    url = {https://CRAN.R-project.org/package=tigris},
  }

@book{elhorst_spatial_2014,
	address = {Berlin, Heidelberg},
	edition = {1st ed. 2014},
	series = {{SpringerBriefs} in {Regional} {Science}},
	title = {Spatial {Econometrics}: {From} {Cross}-{Sectional} {Data} to {Spatial} {Panels}},
	isbn = {978-3-642-40340-8},
	shorttitle = {Spatial {Econometrics}},
	abstract = {This book provides an overview of three generations of spatial econometric models: models based on cross-sectional data, static models based on spatial panels and dynamic spatial panel data models. The book not only presents different model specifications and their corresponding estimators, but also critically discusses the purposes for which these models can be used and how their results should be interpreted},
	publisher = {Springer Berlin Heidelberg : Imprint: Springer},
	author = {Elhorst, J. Paul},
	year = {2014},
	doi = {10.1007/978-3-642-40340-8},
	keywords = {Statistics, Econometrics, Regional economics, Regional/Spatial Science, Spatial economics, Statistics for Business, Management, Economics, Finance, Insurance},
	annote = {Contents -- 1 Introduction -- 2 Linear Spatial Dependence Models -- for Cross-Section Data -- 3 Spatial Panel Data Models -- 4 Dynamic Spatial Panels: Models, Methods and Inferences -- References},
}

@book{chi_spatial_2020,
	address = {Los Angeles},
	title = {Spatial regression models for the social sciences},
	isbn = {978-1-5443-0207-2},
	publisher = {SAGE},
	author = {Chi, Guangqing and Zhu, Jun},
	year = {2020},
	keywords = {Social sciences, Statistical methods, Spatial analysis (Statistics)},
}

@book{anselin_spatial_1988,
	address = {Dordrecht},
	title = {Spatial {Econometrics}: {Methods} and {Models}.},
	isbn = {978-94-015-7799-1},
	shorttitle = {Spatial {Econometrics}},
	language = {English},
	publisher = {Springer Netherlands},
	author = {Anselin, Luc},
	year = {1988},
	note = {OCLC: 958539753},
}

@book{lesage_introduction_2009,
	address = {Boca Raton},
	series = {Statistics, textbooks and monographs},
	title = {Introduction to spatial econometrics},
	isbn = {978-1-4200-6424-7},
	publisher = {CRC Press},
	author = {LeSage, James P. and Pace, R. Kelley},
	year = {2009},
	note = {OCLC: 166358420},
	keywords = {Econometric models, Mathematical models, Space in economics},
	annote = {"A Chapman \& Hall book."},
}

@book{fox_applied_2016,
	address = {Los Angeles},
	edition = {Third Edition},
	title = {Applied regression analysis and generalized linear models},
	isbn = {978-1-4522-0566-3},
	publisher = {SAGE},
	author = {Fox, John},
	year = {2016},
	note = {OCLC: ocn894301740},
	keywords = {Linear models (Statistics), Regression analysis, Social sciences, Statistical methods},
	annote = {Rev. ed. of: Applied regression analysis, linear models, and related methods, c1997},
}

@article{nelder_generalized_1972,
	title = {Generalized {Linear} {Models}},
	volume = {135},
	issn = {2397-2327},
	url = {https://rss.onlinelibrary.wiley.com/doi/abs/10.2307/2344614},
	doi = {10.2307/2344614},
	abstract = {The technique of iterative weighted linear regression can be used to obtain maximum likelihood estimates of the parameters with observations distributed according to some exponential family and systematic effects that can be made linear by a suitable transformation. A generalization of the analysis of variance is given for these models using log-likelihoods. These generalized linear models are illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables) and gamma (variance components). The implications of the approach in designing statistics courses are discussed.},
	language = {en},
	number = {3},
	urldate = {2021-07-13},
	journal = {Journal of the Royal Statistical Society: Series A (General)},
	author = {Nelder, J. A. and Wedderburn, R. W. M.},
	year = {1972},
	note = {\_eprint: https://rss.onlinelibrary.wiley.com/doi/pdf/10.2307/2344614},
	keywords = {analysis of variance, contingency tables, exponential families, inverse polynomials, linear models, maximum likelihood, quantal response, regression, variance components, weighted least squares},
	pages = {370--384},
	file = {Snapshot:C\:\\Users\\ozd504\\Zotero\\storage\\S2EA45PL\\2344614.html:text/html},
}

@book{mccullagh_generalized_1998,
	address = {Boca Raton},
	edition = {2nd ed},
	series = {Monographs on statistics and applied probability},
	title = {Generalized linear models},
	isbn = {978-0-412-31760-6},
	language = {en},
	number = {37},
	publisher = {Chapman \& Hall/CRC},
	author = {McCullagh, P. and Nelder, John A.},
	year = {1998},
	keywords = {Linear models (Statistics)},
	file = {9780203753736_webpdf.pdf:C\:\\Users\\ozd504\\Downloads\\9780203753736_webpdf.pdf:application/pdf},
}

@article{Logan2012a,
	title = {Making a {Place} for {Space}: {Spatial} {Thinking} in {Social} {Science}},
	volume = {38},
	issn = {0360-0572},
	doi = {10.1146/annurev-soc-071811-145531},
	abstract = {New technologies and multilevel data sets that include geographic identifiers have heightened sociologists' interest in spatial analysis. I review several of the key concepts, measures, and methods that are brought into play in this work and offer examples of their application in a variety of substantive fields. I argue that the most effective use of the new tools requires greater emphasis on spatial thinking. A device as simple as an illustrative map requires some understanding of how people respond to visual cues; models as complex as hierarchical linear modeling with spatial lags require thoughtful measurement decisions and raise questions about what a spatial effect represents.},
	number = {1},
	author = {Logan, John R.},
	year = {2012},
	pmid = {24273374},
	note = {ISBN: 03600572 (ISSN)},
	keywords = {distance, exposure, mapping, segregation, spatial, spatial dependence},
	pages = {507--524},
	file = {PDF:C\:\\Users\\ozd504\\Zotero\\storage\\7PUT4IYI\\2012-Making_a_Place_for_Space_Spatial_Thinking_in_Social_Science.pdf:application/pdf},
}

@article{voss_demography_2007,
	title = {Demography as a {Spatial} {Social} {Science}},
	volume = {26},
	issn = {0167-5923, 1573-7829},
	url = {http://link.springer.com/10.1007/s11113-007-9047-4},
	doi = {10.1007/s11113-007-9047-4},
	language = {en},
	number = {5-6},
	urldate = {2021-06-28},
	journal = {Population Research and Policy Review},
	author = {Voss, Paul R.},
	month = nov,
	year = {2007},
	pages = {457--476},
}

@techreport{united_nations_population_division_manual_1983,
	address = {New York, NY},
	title = {Manual {X}: {Indirect} {Techniques} for {Demographic} {Estimation}},
	url = {https://www.un.org/en/development/desa/population/publications/manual/estimate/demographic-estimation.asp},
	author = {United Nations Population Division},
	year = {1983},
}
@book{keyfitz_introduction_1968,
	title = {Introduction to the {Mathematics} of {Population}},
	isbn = {978-0-201-03684-8},
	language = {en},
	publisher = {Addison-Wesley Publishing Company},
	author = {Keyfitz, Nathan},
	year = {1968},
	note = {Google-Books-ID: HnTtxgEACAAJ},
}

@Manual{Iannone2021,
    title = {gt: Easily Create Presentation-Ready Display Tables},
    author = {Richard Iannone and Joe Cheng and Barret Schloerke},
    year = {2021},
    note = {R package version 0.3.0},
    url = {https://CRAN.R-project.org/package=gt},
  }
@misc{us_census_bureau_american_2014,
	title = {American {Community} {Survey} {Design} and {Methodology} ({January} 2014)},
	url = {https://www2.census.gov/programs-surveys/acs/methodology/design_and_methodology/acs_design_methodology_report_2014.pdf},
	author = {US Census Bureau},
	year = {2014},
}
@Manual{stargazer,
    title = {stargazer: Well-Formatted Regression and Summary Statistics Tables},
    author = {Marek Hlavac},
    year = {2018},
    note = {R package version 5.2.2},
    organization = {Central European Labour Studies Institute (CELSI)},
    address = {Bratislava, Slovakia},
    url = {https://CRAN.R-project.org/package=stargazer},
  }
@article{ibragimov_inference_2016,
	title = {Inference with {Few} {Heterogeneous} {Clusters}},
	volume = {98},
	issn = {0034-6535},
	url = {https://doi.org/10.1162/REST_a_00545},
	doi = {10.1162/REST_a_00545},
	abstract = {Suppose estimating a model on each of a small number of potentially heterogeneous clusters yields approximately independent, unbiased, and Gaussian parameter estimators. We make two contributions in this setup. First, we show how to compare a scalar parameter of interest between treatment and control units using a two-sample t-statistic, extending previous results for the one-sample t-statistic. Second, we develop a test for the appropriate level of clustering; it tests the null hypothesis that clustered standard errors from a much finer partition are correct. We illustrate the approach by revisiting empirical studies involving clustered, time series, and spatially correlated data.},
	number = {1},
	urldate = {2021-06-25},
	journal = {The Review of Economics and Statistics},
	author = {Ibragimov, Rustam and Müller, Ulrich K.},
	month = mar,
	year = {2016},
	pages = {83--96},
	file = {Full Text PDF:C\:\\Users\\ozd504\\Zotero\\storage\\96FNCSLB\\Ibragimov and Müller - 2016 - Inference with Few Heterogeneous Clusters.pdf:application/pdf;Snapshot:C\:\\Users\\ozd504\\Zotero\\storage\\GA3CTDNS\\Inference-with-Few-Heterogeneous-Clusters.html:text/html},
}

@article{cameron_practitioners_2015,
	title = {A {Practitioner}’s {Guide} to {Cluster}-{Robust} {Inference}},
	volume = {50},
	issn = {0022-166X, 1548-8004},
	url = {http://jhr.uwpress.org/content/50/2/317},
	doi = {10.3368/jhr.50.2.317},
	abstract = {We consider statistical inference for regression when data are grouped into clusters, with regression model errors independent across clusters but correlated within clusters. Examples include data on individuals with clustering on village or region or other category such as industry, and state-year differences-in-differences studies with clustering on state. In such settings, default standard errors can greatly overstate estimator precision. Instead, if the number of clusters is large, statistical inference after OLS should be based on cluster-robust standard errors. We outline the basic method as well as many complications that can arise in practice. These include cluster-specific fixed effects, few clusters, multiway clustering, and estimators other than OLS.},
	language = {en},
	number = {2},
	urldate = {2021-06-25},
	journal = {Journal of Human Resources},
	author = {Cameron, A. Colin and Miller, Douglas L.},
	month = mar,
	year = {2015},
	note = {Publisher: University of Wisconsin Press},
	pages = {317--372},
	file = {Submitted Version:C\:\\Users\\ozd504\\Zotero\\storage\\MFQVYW4J\\Cameron and Miller - 2015 - A Practitioner’s Guide to Cluster-Robust Inference.pdf:application/pdf},
}

@article{rao_chi-squared_1984,
	title = {On {Chi}-squared {Tests} {For} {Multiway} {Contigency} {Tables} with {Proportions} {Estimated} {From} {Survey} {Data}},
	volume = {12},
	journal = {Annals of Statistics},
	author = {Rao, JNK and Scott, AJ},
	year = {1984},
	pages = {46--60},
}
@article{Ruggles2021,
	title = {Integrated {Public} {Use} {Microdata} {Series}: {Version} 11.0 [machine-readable database]},
	doi = {https://doi.org/10.18128/D010.V8.0},
	abstract = {Steven Ruggles, J. Trent Alexander, Katie Genadek, Ronald Goeken, Matthew B. Schroeder, and Matthew Sobek. Integrated Public Use Microdata Series: Version 5.0 [Machine-readable database]. Minneapolis: University of Minnesota, 2010.},
	author = {Ruggles, S and Flood, S and Grover, Josiah and Foster, S and Goeken, R and Pacas, Jose and Schouweiler, Erin and Sobek, M},
	year = {2021},
}
@Manual{walker21,
    title = {tidycensus: Load US Census Boundary and Attribute Data as 'tidyverse' and
'sf'-Ready Data Frames},
    author = {Kyle Walker and Matt Herman},
    year = {2021},
    note = {R package version 1.0},
    url = {https://CRAN.R-project.org/package=tidycensus},
  }
@Book{Lohr2019,
  title ={Sampling: Design and Analysis},
  author={Shron Lohr},
  publisher={Routledg/CRC Press},
  year={2019},
  address={Boca Raton},
  edition={2nd},
  }
  @misc{cdc_weighting_2020,
	title = {Weighting the {BRFSS} {Data}},
	url = {https://www.cdc.gov/brfss/annual_data/2019/pdf/weighting-2019-508.pdf},
	author = {CDC},
	year = {2020},
}

@misc{international_demographic_2012,
	title = {Demographic and {Health} {Survey} {Sampling} and {Household} {Listing} {Manual}},
	publisher = {ICF International},
	author = {ICF International },
	year = {2012},
}

@Book{xie2015,
  title = {Dynamic Documents with {R} and knitr},
  author = {Yihui Xie},
  publisher = {Chapman and Hall/CRC},
  address = {Boca Raton, Florida},
  year = {2015},
  edition = {2nd},
  note = {ISBN 978-1498716963},
  url = {http://yihui.name/knitr/},
}

@Book{kleinman,
  title = {SAS and R: Data Management, Statistical Analysis, and Graphics, 2nd Edition},
  author = {Kleinman, Ken and Horton, Nicholas J.},
  publisher = {Chapman and Hall/CRC},
  address = {Boca Raton, Florida},
  year = {2014},
  edition = {2nd},
  note = {ISBN 978-1466584495},
  url = {https://nhorton.people.amherst.edu/sasr2/},
}
@book{Wickham,
author = {Wickham, Hadley},
edition = {1st},
publisher = {O'Reily},
title = {{R Packages}},
url = {https://r-pkgs.org/}
}
@Manual{GT,
    title = {gt: Easily Create Presentation-Ready Display Tables},
    author = {Richard Iannone and Joe Cheng and Barret Schloerke},
    year = {2020},
    note = {R package version 0.2.2},
    url = {https://CRAN.R-project.org/package=gt},
  }
@Manual{haven,
    title = {haven: Import and Export 'SPSS', 'Stata' and 'SAS' Files},
    author = {Hadley Wickham and Evan Miller},
    year = {2020},
    note = {R package version 2.3.1},
    url = {https://CRAN.R-project.org/package=haven},
  }
@book{lumley2010,
	title = {Complex {Surveys}: {A} {Guide} to {Analysis} {Using} {R}: {A} {Guide} to {Analysis} {Using} {R}},
	publisher = {John Wiley and Sons},
	author = {Lumley, Thomas},
	year = {2010},
}

 @Article{tidyverse,
    title = {Welcome to the {tidyverse}},
    author = {Hadley Wickham and Mara Averick and Jennifer Bryan and Winston Chang and Lucy D'Agostino McGowan and Romain François and Garrett Grolemund and Alex Hayes and Lionel Henry and Jim Hester and Max Kuhn and Thomas Lin Pedersen and Evan Miller and Stephan Milton Bache and Kirill Müller and Jeroen Ooms and David Robinson and Dana Paige Seidel and Vitalie Spinu and Kohske Takahashi and Davis Vaughan and Claus Wilke and Kara Woo and Hiroaki Yutani},
    year = {2019},
    journal = {Journal of Open Source Software},
    volume = {4},
    number = {43},
    pages = {1686},
    doi = {10.21105/joss.01686},
  }
@Manual{dplyr,
    title = {dplyr: A Grammar of Data Manipulation},
    author = {Hadley Wickham and Romain François and Lionel {
             Henry} and Kirill Müller},
    year = {2020},
    note = {R package version 1.0.2},
    url = {https://CRAN.R-project.org/package=dplyr},
  }
  @Book{ggplot2,
    author = {Hadley Wickham},
    title = {ggplot2: Elegant Graphics for Data Analysis},
    publisher = {Springer-Verlag New York},
    year = {2016},
    isbn = {978-3-319-24277-4},
    url = {https://ggplot2.tidyverse.org},
  }
@book{Wickham2017R,
  abstract = {Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.

Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way.

You'll learn how to:

    Wrangle—transform your datasets into a form convenient for analysis
    Program—learn powerful R tools for solving data problems with greater clarity and ease
    Explore—examine your data, generate hypotheses, and quickly test them
    Model—provide a low-dimensional summary that captures true "signals" in your dataset
    Communicate—learn R Markdown for integrating prose, code, and results},
  added-at = {2018-06-18T21:23:34.000+0200},
  author = {Wickham, Hadley and Grolemund, Garrett},
  biburl = {https://www.bibsonomy.org/bibtex/22e6e5a8bda4b8020e3b4e90c5accf9a8/pbett},
  citeulike-article-id = {14263839},
  citeulike-linkout-0 = {http://r4ds.had.co.nz/},
  citeulike-linkout-1 = {http://www.amazon.ca/exec/obidos/redirect?tag=citeulike09-20&path=ASIN/1491910399},
  citeulike-linkout-10 = {http://www.librarything.com/isbn/1491910399},
  citeulike-linkout-11 = {http://www.worldcat.org/oclc/979415716},
  citeulike-linkout-2 = {http://www.amazon.de/exec/obidos/redirect?tag=citeulike01-21&path=ASIN/1491910399},
  citeulike-linkout-3 = {http://www.amazon.fr/exec/obidos/redirect?tag=citeulike06-21&path=ASIN/1491910399},
  citeulike-linkout-4 = {http://www.amazon.jp/exec/obidos/ASIN/1491910399},
  citeulike-linkout-5 = {http://www.amazon.co.uk/exec/obidos/ASIN/1491910399/citeulike00-21},
  citeulike-linkout-6 = {http://www.amazon.com/exec/obidos/redirect?tag=citeulike07-20&path=ASIN/1491910399},
  citeulike-linkout-7 = {http://www.worldcat.org/isbn/1491910399},
  citeulike-linkout-8 = {http://books.google.com/books?vid=ISBN1491910399},
  citeulike-linkout-9 = {http://www.amazon.com/gp/search?keywords=1491910399&index=books&linkCode=qs},
  comment = {Available (section-by-section) online from http://r4ds.had.co.nz/},
  day = 05,
  edition = 1,
  howpublished = {Paperback},
  interhash = {660059a5b6b582a913488afb63e66907},
  intrahash = {2e6e5a8bda4b8020e3b4e90c5accf9a8},
  isbn = {1491910399},
  keywords = {visualisation textbook computing rpackage},
  month = jan,
  posted-at = {2017-04-03 14:44:51},
  priority = {2},
  publisher = {O'Reilly Media},
  timestamp = {2018-06-22T18:36:55.000+0200},
  title = {R for Data Science: Import, Tidy, Transform, Visualize, and Model Data},
  url = {http://r4ds.had.co.nz/},
  year = 2017
}

@article{cdc2020,
	title = {Weighting the BRFSS Data},
	author = {{CDC}, {}},
	year = {2020},
	date = {2020},
	url = {https://www.cdc.gov/brfss/annual_data/2019/pdf/weighting-2019-508.pdf}
}

@article{uscensusbureau2014,
	title = {American Community Survey Design and Methodology (January 2014)},
	author = {{US Census Bureau}, {}},
	year = {2014},
	date = {2014},
	url = {https://www2.census.gov/programs-surveys/acs/methodology/design_and_methodology/acs_design_methodology_report_2014.pdf}
}

@article{soni2017,
	title = {Medicaid Expansion Under the Affordable Care Act and Insurance Coverage in Rural and Urban Areas},
	author = {{Soni}, {Aparna} and {Hendryx}, {Michael} and {Simon}, {Kosali}},
	year = {2017},
	date = {2017},
	journal = {The Journal of Rural Health},
	pages = {217--226},
	volume = {33},
	number = {2},
	doi = {10.1111/jrh.12234},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/jrh.12234},
	note = {{\_}eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/jrh.12234},
	langid = {en}
}

@article{courtemanche2019,
	title = {Effects of the Affordable Care Act on Health Behaviors After 3 Years},
	author = {{Courtemanche}, {Charles} and {Marton}, {James} and {Ukert}, {Benjamin} and {Yelowitz}, {Aaron} and {Zapata}, {Daniela}},
	year = {2019},
	month = {01},
	date = {2019-01-01},
	journal = {Eastern Economic Journal},
	pages = {7--33},
	volume = {45},
	number = {1},
	doi = {10.1057/s41302-018-0119-4},
	url = {https://doi.org/10.1057/s41302-018-0119-4},
	langid = {en}
}

@article{soni2017a,
	title = {Medicaid Expansion Under the Affordable Care Act and Insurance Coverage in Rural and Urban Areas},
	author = {{Soni}, {Aparna} and {Hendryx}, {Michael} and {Simon}, {Kosali}},
	year = {2017},
	date = {2017},
	journal = {The Journal of Rural Health},
	pages = {217--226},
	volume = {33},
	number = {2},
	doi = {10.1111/jrh.12234},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/jrh.12234},
	note = {{\_}eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/jrh.12234},
	langid = {en}
}

@article{courtemanche2019a,
	title = {Effects of the Affordable Care Act on Health Behaviors After 3 Years},
	author = {{Courtemanche}, {Charles} and {Marton}, {James} and {Ukert}, {Benjamin} and {Yelowitz}, {Aaron} and {Zapata}, {Daniela}},
	year = {2019},
	month = {01},
	date = {2019-01-01},
	journal = {Eastern Economic Journal},
	pages = {7--33},
	volume = {45},
	number = {1},
	doi = {10.1057/s41302-018-0119-4},
	url = {https://doi.org/10.1057/s41302-018-0119-4},
	langid = {en}
}