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01-Introduction.md

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 ## R Packages
 
-R is a statistical software language designed to be extended vis-à-vis packages. As of November 13, 2023, there are currently 20,017 packages available on [CRAN](https://cran.r-project.org). Given the ease by which R can be extended, it has become the tool of choice for conducting propensity score analysis. If you are new to R I highly recommend [*R for Data Science*](https://r4ds.had.co.nz) [@Wickham2016] as an excellent introduction to R. This book will make use of a number of R 
+R is a statistical software language designed to be extended vis-à-vis packages. As of November 14, 2023, there are currently 20,013 packages available on [CRAN](https://cran.r-project.org). Given the ease by which R can be extended, it has become the tool of choice for conducting propensity score analysis. If you are new to R I highly recommend [*R for Data Science*](https://r4ds.had.co.nz) [@Wickham2016] as an excellent introduction to R. This book will make use of a number of R 
 
 
 * [`MatchIt`](http://gking.harvard.edu/gking/matchit) [@R-MatchIt] Nonparametric Preprocessing for Parametric Causal Inference

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-    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-13.</p>
+    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-14.</p>
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appendix-psmodels.html

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-    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-13.</p>
+    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-14.</p>
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appendix-psranges.html

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-    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-13.</p>
+    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-14.</p>
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appendix-shiny.html

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-    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-13.</p>
+    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-14.</p>
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chapter-bootstrapping.html

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-    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-13.</p>
+    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-14.</p>
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chapter-introduction.html

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 <h2>
 <span class="header-section-number">1.4</span> R Packages<a class="anchor" aria-label="anchor" href="#r-packages"><i class="fas fa-link"></i></a>
 </h2>
-<p>R is a statistical software language designed to be extended vis-à-vis packages. As of November 13, 2023, there are currently 20,017 packages available on <a href="https://cran.r-project.org">CRAN</a>. Given the ease by which R can be extended, it has become the tool of choice for conducting propensity score analysis. If you are new to R I highly recommend <a href="https://r4ds.had.co.nz"><em>R for Data Science</em></a> <span class="citation">(Wickham and Grolemund 2016)</span> as an excellent introduction to R. This book will make use of a number of R</p>
+<p>R is a statistical software language designed to be extended vis-à-vis packages. As of November 14, 2023, there are currently 20,013 packages available on <a href="https://cran.r-project.org">CRAN</a>. Given the ease by which R can be extended, it has become the tool of choice for conducting propensity score analysis. If you are new to R I highly recommend <a href="https://r4ds.had.co.nz"><em>R for Data Science</em></a> <span class="citation">(Wickham and Grolemund 2016)</span> as an excellent introduction to R. This book will make use of a number of R</p>
 <ul>
 <li>
 <a href="http://gking.harvard.edu/gking/matchit"><code>MatchIt</code></a> <span class="citation">(Ho et al. 2023)</span> Nonparametric Preprocessing for Parametric Causal Inference</li>
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   <div class="col-12 col-md-6 mt-3">
-    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-13.</p>
+    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-14.</p>
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chapter-matching.html

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-    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-13.</p>
+    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-14.</p>
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chapter-missing.html

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-    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-13.</p>
+    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-14.</p>
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chapter-multilevelpsa.html

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-    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-13.</p>
+    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-14.</p>
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chapter-non-binary.html

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-    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-13.</p>
+    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-14.</p>
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chapter-sensitivity.html

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-    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-13.</p>
+    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-14.</p>
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chapter-stratification.html

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-    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-13.</p>
+    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-14.</p>
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chapter-weighting.html

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-    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-13.</p>
+    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-14.</p>
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index.html

@@ -93,7 +93,7 @@ <h1>
   </header><main class="col-sm-12 col-md-9 col-lg-7" id="content"><!--bookdown:title:end--><!--bookdown:title:start--><div id="preface" class="section level1 unnumbered">
 <h1>Preface<a class="anchor" aria-label="anchor" href="#preface"><i class="fas fa-link"></i></a>
 </h1>
-<p>Last updated: November 13, 2023</p>
+<p>Last updated: November 14, 2023</p>
 <p><a href="https://psa.bryer.org" target="_blank"><img src="figures/cover.png" width="40%" style="float:right; padding:10px"></a></p>
 <p>I was first introduced to propensity score analysis (PSA) by my late dissertation advisor Robert Pruzek in 2006 when I entered graduate school. The notion that you could get reasonable causal estimates without the need of randomization was foreign to me and at first, I was skeptical. Many years later having used PSA for many projects, not only am I convinced it is possible, I believe there are instances where this may be preferred over the randomized control trial. I have been the Principal Investigator for two Federal grants to develop and test the <a href="https://daacs.net">Diagnostic Assessment and Achievement of College Skills (DAACS)</a> where have attempted to conduct large scale randomized control trials (RCT) involving thousands of students. I have found through my experiences conducting these large scale RCTs that there are numerous compromises made in delivering an intervention that compromise the generalizability of the results. Moreover, RCTs assume a single, homogenous, causal effect for everyone. In reality this is rarely true. Not all interventions are equally effective for everyone. With PSA, particularly in the stratification section, it is possible to tease out how an intervention may vary by the observed covariates.</p>
 <p>I have taught PSA many times over the years. This “book” is my attempt to collect my notes and experiences on conducting PSA. For the most part I will emphasize the applied and provide links to references if the reader wishes to explore the theoretical in more details. Additionally, the book will make extensive use of visualizations both to explain concepts as well their use for presenting results. The <code>psa</code> R package that accompanies this book is available on Github and can be installed using the <code>remotes</code> package with the command below. By setting the <code>dependencies = 'Enhances'</code> parameter will ensure that all the R packages used in this book are installed as well. The <code>psa</code> package contains a number of datasets and utility functions used throughout the book. But it also contains a <a href="https://shiny.rstudio.com">Shiny</a> application designed to conduct PSA using a graphical user interface. Details on using the application are provided in the <a href="#psa_shiny">appendix</a>.</p>
@@ -131,7 +131,7 @@ <h2>Colophon<a class="anchor" aria-label="anchor" href="#colophon"><i class="fas
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-##  date     2023-11-13
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 ##  pandoc   2.19.2 @ /usr/bin/ (via rmarkdown)
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 ## ─ Packages ───────────────────────────────────────────────────────────────────
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-##  granovaGG     * 1.4.0    2023-11-13 [1] Github (briandk/granovaGG@3b95715)
+##  granovaGG     * 1.4.0    2023-11-14 [1] Github (briandk/granovaGG@3b95715)
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-##  PSAboot       * 1.3.8    2023-11-13 [1] Github (jbryer/PSAboot@f5d73cd)
+##  PSAboot       * 1.3.8    2023-11-14 [1] Github (jbryer/PSAboot@f5d73cd)
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@@ -295,7 +295,7 @@ <h2>License<a class="anchor" aria-label="anchor" href="#license"><i class="fas f
 <footer class="bg-primary text-light mt-5"><div class="container"><div class="row">
 
   <div class="col-12 col-md-6 mt-3">
-    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-13.</p>
+    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-14.</p>
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index.md

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 --- 
 title: "Applied Propensity Score Analysis with R"
 author: "Jason Bryer, Ph.D."
-date: "2023-11-13"
+date: "2023-11-14"
 site: bookdown::bookdown_site
 documentclass: book
 url: https://psa.bryer.org
@@ -14,7 +14,7 @@ bibliography: [book.bib, packages.bib]
 
 # Preface {-}
 
-Last updated: November 13, 2023
+Last updated: November 14, 2023
 
 <a href="https://psa.bryer.org" target="_blank"><img src="figures/cover.png" width="40%" style="float:right; padding:10px" style="display: block; margin: auto 0 auto auto;" /></a>
 
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-##  date     2023-11-13
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 ## 
 ## ─ Packages ───────────────────────────────────────────────────────────────────
@@ -91,7 +91,7 @@ devtools::session_info()
 ##  ggthemes        4.2.4    2021-01-20 [1] RSPM (R 4.3.0)
 ##  glue            1.6.2    2022-02-24 [1] RSPM (R 4.3.0)
 ##  granova       * 2.2      2023-03-22 [1] RSPM (R 4.3.0)
-##  granovaGG     * 1.4.0    2023-11-13 [1] Github (briandk/granovaGG@3b95715)
+##  granovaGG     * 1.4.0    2023-11-14 [1] Github (briandk/granovaGG@3b95715)
 ##  gridExtra       2.3      2017-09-09 [1] RSPM (R 4.3.0)
 ##  gtable          0.3.4    2023-08-21 [1] RSPM (R 4.3.0)
 ##  highr           0.10     2022-12-22 [1] RSPM (R 4.3.0)
@@ -136,7 +136,7 @@ devtools::session_info()
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 ##  ps              1.7.5    2023-04-18 [1] RSPM (R 4.3.0)
-##  PSAboot       * 1.3.8    2023-11-13 [1] Github (jbryer/PSAboot@f5d73cd)
+##  PSAboot       * 1.3.8    2023-11-14 [1] Github (jbryer/PSAboot@f5d73cd)
 ##  PSAgraphics   * 2.1.2    2023-03-21 [1] RSPM (R 4.3.0)
 ##  psych           2.3.9    2023-09-26 [1] RSPM (R 4.3.0)
 ##  purrr           1.0.2    2023-08-10 [1] RSPM (R 4.3.0)
@@ -155,7 +155,7 @@ devtools::session_info()
 ##  scales        * 1.2.1    2022-08-20 [1] RSPM (R 4.3.0)
 ##  sessioninfo     1.2.2    2021-12-06 [1] RSPM (R 4.3.0)
 ##  shiny           1.7.5.1  2023-10-14 [1] RSPM (R 4.3.0)
-##  stringi         1.7.12   2023-01-11 [1] RSPM (R 4.3.0)
+##  stringi         1.8.1    2023-11-13 [1] RSPM (R 4.3.0)
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 ##  survival        3.5-7    2023-08-14 [2] CRAN (R 4.3.2)

references.html

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 <footer class="bg-primary text-light mt-5"><div class="container"><div class="row">
 
   <div class="col-12 col-md-6 mt-3">
-    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-13.</p>
+    <p>"<strong>Applied Propensity Score Analysis with R</strong>" was written by Jason Bryer, Ph.D.. It was last built on 2023-11-14.</p>
   </div>
 
   <div class="col-12 col-md-6 mt-3">