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index.html

@@ -277,13 +277,13 @@ <h2 id="toc-title">On this page</h2>
 <section id="unitdid" class="level1">
 <h1>unitdid</h1>
 <!-- badges: start -->
-<!-- badges: end -->
+<p><a href="https://kazuyanagimoto.r-universe.dev/unitdid"><img src="https://kazuyanagimoto.r-universe.dev/badges/unitdid.png" class="img-fluid" alt="unitdid status badge"></a> <a href="https://github.com/kazuyanagimoto/unitdid/blob/main/LICENSE.md" target="_blank"><img src="https://img.shields.io/badge/license-MIT-blue"></a> <a href="https://kazuyanagimoto.com/unitdid/index.html"><img src="https://img.shields.io/badge/docs-homepage-blue.svg" class="img-fluid" alt="Docs"></a> <!-- badges: end --></p>
 <p>The <code>unitdid</code> package provides a set of functions for the analysis of the unit-level difference-in-differences (<a href="https://arxiv.org/abs/2403.19563">Arkhangelsky, Yanagimoto, and Zohar 2024</a>).</p>
 <section id="installation" class="level2">
 <h2 class="anchored" data-anchor-id="installation">Installation</h2>
-<p>You can install the development version of unitdid from <a href="https://github.com/kazuyanagimoto/unitdid">GitHub</a> with:</p>
-<div class="sourceCode" id="cb1"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="co"># install.packages("remotes")</span></span>
-<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a>remotes<span class="sc">::</span><span class="fu">install_github</span>(<span class="st">"kazuyanagimoto/unitdid"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<p>You can install the development version of unitdid from R-universe with:</p>
+<div class="sourceCode" id="cb1"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="fu">install.packages</span>(<span class="st">'unitdid'</span>,</span>
+<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a>                 <span class="at">repos =</span> <span class="st">'https://kazuyanagimoto.r-universe.dev'</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </section>
 <section id="example" class="level2">
 <h2 class="anchored" data-anchor-id="example">Example</h2>

search.json

@@ -123,7 +123,7 @@
     "href": "index.html",
     "title": "unitdid",
     "section": "",
-    "text": "The unitdid package provides a set of functions for the analysis of the unit-level difference-in-differences (Arkhangelsky, Yanagimoto, and Zohar 2024).\n\n\nYou can install the development version of unitdid from GitHub with:\n# install.packages(\"remotes\")\nremotes::install_github(\"kazuyanagimoto/unitdid\")\n\n\n\nThis is a basic example with the simulated base_heterocp data set:\n\nlibrary(unitdid)\nlibrary(dplyr)\nlibrary(ggplot2)\n\nbase_heterocp |>\n  head()\n#> # A tibble: 6 × 5\n#>      id  year byear cyear      y\n#>   <int> <int> <int> <int>  <dbl>\n#> 1     1  1999  1955  1985 -0.848\n#> 2     1  2000  1955  1985  0.759\n#> 3     1  2001  1955  1985 -1.03 \n#> 4     1  2002  1955  1985  0.858\n#> 5     1  2003  1955  1985 -0.866\n#> 6     1  2004  1955  1985 -0.651\n\nIndividual-level child penalties are estimated by unitdid():\n\nmdl_base <- base_heterocp |>\n  unitdid(yname = \"y\",\n        iname = \"id\",\n        tname = \"year\",\n        ename = \"cyear\",\n        bname = \"byear\")\n\n# Estimated individual-level child penalties (y_tilde)\nget_unitdid(mdl_base)\n#> # A tibble: 32,257 × 6\n#>       id  year byear cyear      y    y_tilde\n#>    <int> <int> <int> <int>  <dbl>      <dbl>\n#>  1   705  2000  1957  2000 0.138  -0.0287   \n#>  2   997  2000  1958  2000 0.138   0.0849   \n#>  3   998  2000  1958  2000 0.119  -0.104    \n#>  4  1013  2000  1958  2000 0.115  -0.0000709\n#>  5  1082  2000  1958  2000 0.0362  0.00549  \n#>  6  1127  2000  1958  2000 0.386   0.125    \n#>  7  1225  2001  1959  2001 0.158  -0.118    \n#>  8  1228  2000  1959  2000 0.241  -0.0937   \n#>  9  1228  2001  1959  2000 0.443   0.0226   \n#> 10  1230  2000  1959  2000 0.143  -0.0266   \n#> # ℹ 32,247 more rows\n\n\n\nThey can be aggregated to the full, event (year at event (treatment). Mainly for staggered DiD design), event_age (age at event. Mainly for child penalties) levels:\n\nsummary(mdl_base) # default agg = \"full\"\n#> # A tibble: 6 × 3\n#>      mean rel_time     n\n#>     <dbl>    <int> <dbl>\n#> 1 -0.0653        0  4357\n#> 2 -0.193         1  4357\n#> 3 -0.307         2  4357\n#> 4 -0.310         3  4357\n#> 5 -0.350         4  4357\n#> 6 -0.349         5  4357\n\n\nsum_eage <- summary(mdl_base, agg = \"event_age\")\n\nsum_eage |>\n  filter(rel_time == 0) |>\n  mutate(rel_time = -1,\n         mean = 0) |>\n  bind_rows(sum_eage) |>\n  filter(between(event_age, 25, 34)) |>\n  mutate(lbl_facet = paste0(\"Age \", event_age)) |>\n  ggplot(aes(x = rel_time, y = mean)) +\n  geom_point() +\n  geom_line() +\n  geom_vline(xintercept = -1, linetype = \"dashed\") +\n  geom_hline(yintercept = 0) +\n  facet_wrap(~lbl_facet, ncol = 5) +\n  labs(x = \"Time to First Childbirth\",\n       y = \"Child Penalties on y\") +\n  theme_minimal() +\n  theme(panel.grid.major.x = element_blank(),\n        panel.grid.minor = element_blank())\n\n\n\n\n\n\n\n\n\n\n\nSince the individual-level child penalties are estimated with measurement errors, the variance of the y_tilde is not equal to the variance of the individual-level child penalties.\nThe compute_varcov = \"var\" option of the unitdid estimates the variance of the measurement errors and the variance of the individual-level child penalties by subtracting the variance of the measurement errors from the variance of y_tilde\n\nmdl_base <- base_heterocp |>\n  unitdid(yname = \"y\",\n        iname = \"id\",\n        tname = \"year\",\n        ename = \"cyear\",\n        bname = \"byear\",\n        compute_varcov = \"var\")\n\nsum_eage <- summary(mdl_base, agg = \"event_age\")\n\nsum_eage |>\n  filter(rel_time == 0) |>\n  mutate(rel_time = -1,\n         var = 0) |>\n  bind_rows(sum_eage) |>\n  filter(between(event_age, 25, 34)) |>\n  mutate(lbl_facet = paste0(\"Age \", event_age)) |>\n  ggplot(aes(x = rel_time, y = sqrt(var))) +\n  geom_point() +\n  geom_line() +\n  geom_vline(xintercept = -1, linetype = \"dashed\") +\n  geom_hline(yintercept = 0) +\n  facet_wrap(~lbl_facet, ncol = 5) +\n  labs(x = \"Time to First Childbirth\",\n       y = \"S.D. of Child Penalties\") +\n  theme_minimal() +\n  theme(panel.grid.major.x = element_blank(),\n        panel.grid.minor = element_blank())\n\n\n\n\n\n\n\n\n\n\n\n\nArkhangelsky, Dmitry, Kazuharu Yanagimoto, and Tom Zohar. 2024. “Flexible Analysis of Individual Heterogeneity in Event Studies: Application to the Child Penalty.” arXiv. https://arxiv.org/abs/2403.19563.",
+    "text": "The unitdid package provides a set of functions for the analysis of the unit-level difference-in-differences (Arkhangelsky, Yanagimoto, and Zohar 2024).\n\n\nYou can install the development version of unitdid from R-universe with:\ninstall.packages('unitdid',\n                 repos = 'https://kazuyanagimoto.r-universe.dev')\n\n\n\nThis is a basic example with the simulated base_heterocp data set:\n\nlibrary(unitdid)\nlibrary(dplyr)\nlibrary(ggplot2)\n\nbase_heterocp |>\n  head()\n#> # A tibble: 6 × 5\n#>      id  year byear cyear      y\n#>   <int> <int> <int> <int>  <dbl>\n#> 1     1  1999  1955  1985 -0.848\n#> 2     1  2000  1955  1985  0.759\n#> 3     1  2001  1955  1985 -1.03 \n#> 4     1  2002  1955  1985  0.858\n#> 5     1  2003  1955  1985 -0.866\n#> 6     1  2004  1955  1985 -0.651\n\nIndividual-level child penalties are estimated by unitdid():\n\nmdl_base <- base_heterocp |>\n  unitdid(yname = \"y\",\n        iname = \"id\",\n        tname = \"year\",\n        ename = \"cyear\",\n        bname = \"byear\")\n\n# Estimated individual-level child penalties (y_tilde)\nget_unitdid(mdl_base)\n#> # A tibble: 32,257 × 6\n#>       id  year byear cyear      y    y_tilde\n#>    <int> <int> <int> <int>  <dbl>      <dbl>\n#>  1   705  2000  1957  2000 0.138  -0.0287   \n#>  2   997  2000  1958  2000 0.138   0.0849   \n#>  3   998  2000  1958  2000 0.119  -0.104    \n#>  4  1013  2000  1958  2000 0.115  -0.0000709\n#>  5  1082  2000  1958  2000 0.0362  0.00549  \n#>  6  1127  2000  1958  2000 0.386   0.125    \n#>  7  1225  2001  1959  2001 0.158  -0.118    \n#>  8  1228  2000  1959  2000 0.241  -0.0937   \n#>  9  1228  2001  1959  2000 0.443   0.0226   \n#> 10  1230  2000  1959  2000 0.143  -0.0266   \n#> # ℹ 32,247 more rows\n\n\n\nThey can be aggregated to the full, event (year at event (treatment). Mainly for staggered DiD design), event_age (age at event. Mainly for child penalties) levels:\n\nsummary(mdl_base) # default agg = \"full\"\n#> # A tibble: 6 × 3\n#>      mean rel_time     n\n#>     <dbl>    <int> <dbl>\n#> 1 -0.0653        0  4357\n#> 2 -0.193         1  4357\n#> 3 -0.307         2  4357\n#> 4 -0.310         3  4357\n#> 5 -0.350         4  4357\n#> 6 -0.349         5  4357\n\n\nsum_eage <- summary(mdl_base, agg = \"event_age\")\n\nsum_eage |>\n  filter(rel_time == 0) |>\n  mutate(rel_time = -1,\n         mean = 0) |>\n  bind_rows(sum_eage) |>\n  filter(between(event_age, 25, 34)) |>\n  mutate(lbl_facet = paste0(\"Age \", event_age)) |>\n  ggplot(aes(x = rel_time, y = mean)) +\n  geom_point() +\n  geom_line() +\n  geom_vline(xintercept = -1, linetype = \"dashed\") +\n  geom_hline(yintercept = 0) +\n  facet_wrap(~lbl_facet, ncol = 5) +\n  labs(x = \"Time to First Childbirth\",\n       y = \"Child Penalties on y\") +\n  theme_minimal() +\n  theme(panel.grid.major.x = element_blank(),\n        panel.grid.minor = element_blank())\n\n\n\n\n\n\n\n\n\n\n\nSince the individual-level child penalties are estimated with measurement errors, the variance of the y_tilde is not equal to the variance of the individual-level child penalties.\nThe compute_varcov = \"var\" option of the unitdid estimates the variance of the measurement errors and the variance of the individual-level child penalties by subtracting the variance of the measurement errors from the variance of y_tilde\n\nmdl_base <- base_heterocp |>\n  unitdid(yname = \"y\",\n        iname = \"id\",\n        tname = \"year\",\n        ename = \"cyear\",\n        bname = \"byear\",\n        compute_varcov = \"var\")\n\nsum_eage <- summary(mdl_base, agg = \"event_age\")\n\nsum_eage |>\n  filter(rel_time == 0) |>\n  mutate(rel_time = -1,\n         var = 0) |>\n  bind_rows(sum_eage) |>\n  filter(between(event_age, 25, 34)) |>\n  mutate(lbl_facet = paste0(\"Age \", event_age)) |>\n  ggplot(aes(x = rel_time, y = sqrt(var))) +\n  geom_point() +\n  geom_line() +\n  geom_vline(xintercept = -1, linetype = \"dashed\") +\n  geom_hline(yintercept = 0) +\n  facet_wrap(~lbl_facet, ncol = 5) +\n  labs(x = \"Time to First Childbirth\",\n       y = \"S.D. of Child Penalties\") +\n  theme_minimal() +\n  theme(panel.grid.major.x = element_blank(),\n        panel.grid.minor = element_blank())\n\n\n\n\n\n\n\n\n\n\n\n\nArkhangelsky, Dmitry, Kazuharu Yanagimoto, and Tom Zohar. 2024. “Flexible Analysis of Individual Heterogeneity in Event Studies: Application to the Child Penalty.” arXiv. https://arxiv.org/abs/2403.19563.",
     "crumbs": [
       "Home"
     ]
@@ -133,7 +133,7 @@
     "href": "index.html#installation",
     "title": "unitdid",
     "section": "",
-    "text": "You can install the development version of unitdid from GitHub with:\n# install.packages(\"remotes\")\nremotes::install_github(\"kazuyanagimoto/unitdid\")",
+    "text": "You can install the development version of unitdid from R-universe with:\ninstall.packages('unitdid',\n                 repos = 'https://kazuyanagimoto.r-universe.dev')",
     "crumbs": [
       "Home"
     ]

vignettes/base_heterocp.html

@@ -7,7 +7,7 @@
 <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
 
 <meta name="author" content="Kazuharu Yanagimoto">
-<meta name="dcterms.date" content="2024-03-29">
+<meta name="dcterms.date" content="2024-04-02">
 
 <title>unitdid - Data Generation Process of base_heterocp</title>
 <style>
@@ -323,7 +323,7 @@ <h1 class="title">Data Generation Process of base_heterocp</h1>
     <div>
     <div class="quarto-title-meta-heading">Published</div>
     <div class="quarto-title-meta-contents">
-      <p class="date">March 29, 2024</p>
+      <p class="date">April 2, 2024</p>
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   </div>
 

vignettes/example_psid.html

@@ -7,7 +7,7 @@
 <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
 
 <meta name="author" content="Kazuharu Yanagimoto">
-<meta name="dcterms.date" content="2024-03-29">
+<meta name="dcterms.date" content="2024-04-02">
 
 <title>unitdid - Individual-level Child Penalties with PSID</title>
 <style>
@@ -313,7 +313,7 @@ <h1 class="title">Individual-level Child Penalties with PSID</h1>
     <div>
     <div class="quarto-title-meta-heading">Published</div>
     <div class="quarto-title-meta-contents">
-      <p class="date">March 29, 2024</p>
+      <p class="date">April 2, 2024</p>
     </div>
   </div>