Generate all outputs from a spec
Details
`verbose_level` is used to control how many messages are printed out. By default, `2` will show all filter messages and show output generation message. `1` will show output generation message only. `0` will display no message.
Examples
library(dplyr, warn.conflicts = FALSE)
data <- list(
adsl = eg_adsl,
adae = eg_adae
)
filters::load_filters(
yaml_file = system.file("filters.yml", package = "autoslider.core"),
overwrite = TRUE
)
spec_file <- system.file("spec.yml", package = "autoslider.core")
spec_file %>%
read_spec() %>%
filter_spec(output %in% c("t_dm_slide_FAS", "gt_t_dm_slide_FAS")) %>%
generate_outputs(datasets = data)
#> ✔ 3/51 outputs matched the filter condition `output %in% c("t_dm_slide_FAS", "gt_t_dm_slide_FAS")`.
#> ❯ Running program `t_dm_slide` with suffix 'FAS'.
#> Filter 'FAS' matched target ADSL.
#> 400/400 records matched the filter condition `FASFL == 'Y'`.
#> ❯ Running program `gt_t_dm_slide` with suffix 'FAS'.
#> Filter 'FAS' matched target ADSL.
#> 400/400 records matched the filter condition `FASFL == 'Y'`.
#> ❯ Running program `t_dm_slide` with suffix 'FAS'.
#> Filter 'FAS' matched target ADSL.
#> 400/400 records matched the filter condition `FASFL == 'Y'`.
#> $t_dm_slide_FAS
#> Demographic slide
#>
#> ———————————————————————————————————————————————————————————————————————————————————————————————————————
#> A: Drug X B: Placebo C: Combination All Patients
#> ———————————————————————————————————————————————————————————————————————————————————————————————————————
#> Sex
#> F 79 (59%) 82 (61.2%) 70 (53%) 231 (57.8%)
#> M 55 (41%) 52 (38.8%) 62 (47%) 169 (42.2%)
#> Age
#> Median 33.00 35.00 35.00 34.00
#> Min - Max 21.0 - 50.0 21.0 - 62.0 20.0 - 69.0 20.0 - 69.0
#> Race
#> ASIAN 68 (50.7%) 67 (50%) 73 (55.3%) 208 (52%)
#> BLACK OR AFRICAN AMERICAN 31 (23.1%) 28 (20.9%) 32 (24.2%) 91 (22.8%)
#> WHITE 27 (20.1%) 26 (19.4%) 21 (15.9%) 74 (18.5%)
#> AMERICAN INDIAN OR ALASKA NATIVE 8 (6%) 11 (8.2%) 6 (4.5%) 25 (6.2%)
#> MULTIPLE 0 1 (0.7%) 0 1 (0.2%)
#> NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER 0 1 (0.7%) 0 1 (0.2%)
#> OTHER 0 0 0 0
#> UNKNOWN 0 0 0 0
#> Ethnicity
#> NOT REPORTED 6 (4.5%) 10 (7.5%) 11 (8.3%) 27 (6.8%)
#> HISPANIC OR LATINO 15 (11.2%) 18 (13.4%) 15 (11.4%) 48 (12%)
#> NOT HISPANIC OR LATINO 104 (77.6%) 103 (76.9%) 101 (76.5%) 308 (77%)
#> UNKNOWN 9 (6.7%) 3 (2.2%) 5 (3.8%) 17 (4.2%)
#>
#> $gt_t_dm_slide_FAS
#> <div id="mwlefoodfi" style="padding-left:0px;padding-right:0px;padding-top:10px;padding-bottom:10px;overflow-x:auto;overflow-y:auto;width:auto;height:auto;">
#> <style>#mwlefoodfi table {
#> font-family: system-ui, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji';
#> -webkit-font-smoothing: antialiased;
#> -moz-osx-font-smoothing: grayscale;
#> }
#>
#> #mwlefoodfi thead, #mwlefoodfi tbody, #mwlefoodfi tfoot, #mwlefoodfi tr, #mwlefoodfi td, #mwlefoodfi th {
#> border-style: none;
#> }
#>
#> #mwlefoodfi p {
#> margin: 0;
#> padding: 0;
#> }
#>
#> #mwlefoodfi .gt_table {
#> display: table;
#> border-collapse: collapse;
#> line-height: normal;
#> margin-left: auto;
#> margin-right: auto;
#> color: #333333;
#> font-size: 16px;
#> font-weight: normal;
#> font-style: normal;
#> background-color: #FFFFFF;
#> width: auto;
#> border-top-style: solid;
#> border-top-width: 2px;
#> border-top-color: #A8A8A8;
#> border-right-style: none;
#> border-right-width: 2px;
#> border-right-color: #D3D3D3;
#> border-bottom-style: solid;
#> border-bottom-width: 2px;
#> border-bottom-color: #A8A8A8;
#> border-left-style: none;
#> border-left-width: 2px;
#> border-left-color: #D3D3D3;
#> }
#>
#> #mwlefoodfi .gt_caption {
#> padding-top: 4px;
#> padding-bottom: 4px;
#> }
#>
#> #mwlefoodfi .gt_title {
#> color: #333333;
#> font-size: 125%;
#> font-weight: initial;
#> padding-top: 4px;
#> padding-bottom: 4px;
#> padding-left: 5px;
#> padding-right: 5px;
#> border-bottom-color: #FFFFFF;
#> border-bottom-width: 0;
#> }
#>
#> #mwlefoodfi .gt_subtitle {
#> color: #333333;
#> font-size: 85%;
#> font-weight: initial;
#> padding-top: 3px;
#> padding-bottom: 5px;
#> padding-left: 5px;
#> padding-right: 5px;
#> border-top-color: #FFFFFF;
#> border-top-width: 0;
#> }
#>
#> #mwlefoodfi .gt_heading {
#> background-color: #FFFFFF;
#> text-align: center;
#> border-bottom-color: #FFFFFF;
#> border-left-style: none;
#> border-left-width: 1px;
#> border-left-color: #D3D3D3;
#> border-right-style: none;
#> border-right-width: 1px;
#> border-right-color: #D3D3D3;
#> }
#>
#> #mwlefoodfi .gt_bottom_border {
#> border-bottom-style: solid;
#> border-bottom-width: 2px;
#> border-bottom-color: #D3D3D3;
#> }
#>
#> #mwlefoodfi .gt_col_headings {
#> border-top-style: solid;
#> border-top-width: 2px;
#> border-top-color: #D3D3D3;
#> border-bottom-style: solid;
#> border-bottom-width: 2px;
#> border-bottom-color: #D3D3D3;
#> border-left-style: none;
#> border-left-width: 1px;
#> border-left-color: #D3D3D3;
#> border-right-style: none;
#> border-right-width: 1px;
#> border-right-color: #D3D3D3;
#> }
#>
#> #mwlefoodfi .gt_col_heading {
#> color: #333333;
#> background-color: #FFFFFF;
#> font-size: 100%;
#> font-weight: normal;
#> text-transform: inherit;
#> border-left-style: none;
#> border-left-width: 1px;
#> border-left-color: #D3D3D3;
#> border-right-style: none;
#> border-right-width: 1px;
#> border-right-color: #D3D3D3;
#> vertical-align: bottom;
#> padding-top: 5px;
#> padding-bottom: 6px;
#> padding-left: 5px;
#> padding-right: 5px;
#> overflow-x: hidden;
#> }
#>
#> #mwlefoodfi .gt_column_spanner_outer {
#> color: #333333;
#> background-color: #FFFFFF;
#> font-size: 100%;
#> font-weight: normal;
#> text-transform: inherit;
#> padding-top: 0;
#> padding-bottom: 0;
#> padding-left: 4px;
#> padding-right: 4px;
#> }
#>
#> #mwlefoodfi .gt_column_spanner_outer:first-child {
#> padding-left: 0;
#> }
#>
#> #mwlefoodfi .gt_column_spanner_outer:last-child {
#> padding-right: 0;
#> }
#>
#> #mwlefoodfi .gt_column_spanner {
#> border-bottom-style: solid;
#> border-bottom-width: 2px;
#> border-bottom-color: #D3D3D3;
#> vertical-align: bottom;
#> padding-top: 5px;
#> padding-bottom: 5px;
#> overflow-x: hidden;
#> display: inline-block;
#> width: 100%;
#> }
#>
#> #mwlefoodfi .gt_spanner_row {
#> border-bottom-style: hidden;
#> }
#>
#> #mwlefoodfi .gt_group_heading {
#> padding-top: 8px;
#> padding-bottom: 8px;
#> padding-left: 5px;
#> padding-right: 5px;
#> color: #333333;
#> background-color: #FFFFFF;
#> font-size: 100%;
#> font-weight: initial;
#> text-transform: inherit;
#> border-top-style: solid;
#> border-top-width: 2px;
#> border-top-color: #D3D3D3;
#> border-bottom-style: solid;
#> border-bottom-width: 2px;
#> border-bottom-color: #D3D3D3;
#> border-left-style: none;
#> border-left-width: 1px;
#> border-left-color: #D3D3D3;
#> border-right-style: none;
#> border-right-width: 1px;
#> border-right-color: #D3D3D3;
#> vertical-align: middle;
#> text-align: left;
#> }
#>
#> #mwlefoodfi .gt_empty_group_heading {
#> padding: 0.5px;
#> color: #333333;
#> background-color: #FFFFFF;
#> font-size: 100%;
#> font-weight: initial;
#> border-top-style: solid;
#> border-top-width: 2px;
#> border-top-color: #D3D3D3;
#> border-bottom-style: solid;
#> border-bottom-width: 2px;
#> border-bottom-color: #D3D3D3;
#> vertical-align: middle;
#> }
#>
#> #mwlefoodfi .gt_from_md > :first-child {
#> margin-top: 0;
#> }
#>
#> #mwlefoodfi .gt_from_md > :last-child {
#> margin-bottom: 0;
#> }
#>
#> #mwlefoodfi .gt_row {
#> padding-top: 8px;
#> padding-bottom: 8px;
#> padding-left: 5px;
#> padding-right: 5px;
#> margin: 10px;
#> border-top-style: solid;
#> border-top-width: 1px;
#> border-top-color: #D3D3D3;
#> border-left-style: none;
#> border-left-width: 1px;
#> border-left-color: #D3D3D3;
#> border-right-style: none;
#> border-right-width: 1px;
#> border-right-color: #D3D3D3;
#> vertical-align: middle;
#> overflow-x: hidden;
#> }
#>
#> #mwlefoodfi .gt_stub {
#> color: #333333;
#> background-color: #FFFFFF;
#> font-size: 100%;
#> font-weight: initial;
#> text-transform: inherit;
#> border-right-style: solid;
#> border-right-width: 2px;
#> border-right-color: #D3D3D3;
#> padding-left: 5px;
#> padding-right: 5px;
#> }
#>
#> #mwlefoodfi .gt_stub_row_group {
#> color: #333333;
#> background-color: #FFFFFF;
#> font-size: 100%;
#> font-weight: initial;
#> text-transform: inherit;
#> border-right-style: solid;
#> border-right-width: 2px;
#> border-right-color: #D3D3D3;
#> padding-left: 5px;
#> padding-right: 5px;
#> vertical-align: top;
#> }
#>
#> #mwlefoodfi .gt_row_group_first td {
#> border-top-width: 2px;
#> }
#>
#> #mwlefoodfi .gt_row_group_first th {
#> border-top-width: 2px;
#> }
#>
#> #mwlefoodfi .gt_summary_row {
#> color: #333333;
#> background-color: #FFFFFF;
#> text-transform: inherit;
#> padding-top: 8px;
#> padding-bottom: 8px;
#> padding-left: 5px;
#> padding-right: 5px;
#> }
#>
#> #mwlefoodfi .gt_first_summary_row {
#> border-top-style: solid;
#> border-top-color: #D3D3D3;
#> }
#>
#> #mwlefoodfi .gt_first_summary_row.thick {
#> border-top-width: 2px;
#> }
#>
#> #mwlefoodfi .gt_last_summary_row {
#> padding-top: 8px;
#> padding-bottom: 8px;
#> padding-left: 5px;
#> padding-right: 5px;
#> border-bottom-style: solid;
#> border-bottom-width: 2px;
#> border-bottom-color: #D3D3D3;
#> }
#>
#> #mwlefoodfi .gt_grand_summary_row {
#> color: #333333;
#> background-color: #FFFFFF;
#> text-transform: inherit;
#> padding-top: 8px;
#> padding-bottom: 8px;
#> padding-left: 5px;
#> padding-right: 5px;
#> }
#>
#> #mwlefoodfi .gt_first_grand_summary_row {
#> padding-top: 8px;
#> padding-bottom: 8px;
#> padding-left: 5px;
#> padding-right: 5px;
#> border-top-style: double;
#> border-top-width: 6px;
#> border-top-color: #D3D3D3;
#> }
#>
#> #mwlefoodfi .gt_last_grand_summary_row_top {
#> padding-top: 8px;
#> padding-bottom: 8px;
#> padding-left: 5px;
#> padding-right: 5px;
#> border-bottom-style: double;
#> border-bottom-width: 6px;
#> border-bottom-color: #D3D3D3;
#> }
#>
#> #mwlefoodfi .gt_striped {
#> background-color: rgba(128, 128, 128, 0.05);
#> }
#>
#> #mwlefoodfi .gt_table_body {
#> border-top-style: solid;
#> border-top-width: 2px;
#> border-top-color: #D3D3D3;
#> border-bottom-style: solid;
#> border-bottom-width: 2px;
#> border-bottom-color: #D3D3D3;
#> }
#>
#> #mwlefoodfi .gt_footnotes {
#> color: #333333;
#> background-color: #FFFFFF;
#> border-bottom-style: none;
#> border-bottom-width: 2px;
#> border-bottom-color: #D3D3D3;
#> border-left-style: none;
#> border-left-width: 2px;
#> border-left-color: #D3D3D3;
#> border-right-style: none;
#> border-right-width: 2px;
#> border-right-color: #D3D3D3;
#> }
#>
#> #mwlefoodfi .gt_footnote {
#> margin: 0px;
#> font-size: 90%;
#> padding-top: 4px;
#> padding-bottom: 4px;
#> padding-left: 5px;
#> padding-right: 5px;
#> }
#>
#> #mwlefoodfi .gt_sourcenotes {
#> color: #333333;
#> background-color: #FFFFFF;
#> border-bottom-style: none;
#> border-bottom-width: 2px;
#> border-bottom-color: #D3D3D3;
#> border-left-style: none;
#> border-left-width: 2px;
#> border-left-color: #D3D3D3;
#> border-right-style: none;
#> border-right-width: 2px;
#> border-right-color: #D3D3D3;
#> }
#>
#> #mwlefoodfi .gt_sourcenote {
#> font-size: 90%;
#> padding-top: 4px;
#> padding-bottom: 4px;
#> padding-left: 5px;
#> padding-right: 5px;
#> }
#>
#> #mwlefoodfi .gt_left {
#> text-align: left;
#> }
#>
#> #mwlefoodfi .gt_center {
#> text-align: center;
#> }
#>
#> #mwlefoodfi .gt_right {
#> text-align: right;
#> font-variant-numeric: tabular-nums;
#> }
#>
#> #mwlefoodfi .gt_font_normal {
#> font-weight: normal;
#> }
#>
#> #mwlefoodfi .gt_font_bold {
#> font-weight: bold;
#> }
#>
#> #mwlefoodfi .gt_font_italic {
#> font-style: italic;
#> }
#>
#> #mwlefoodfi .gt_super {
#> font-size: 65%;
#> }
#>
#> #mwlefoodfi .gt_footnote_marks {
#> font-size: 75%;
#> vertical-align: 0.4em;
#> position: initial;
#> }
#>
#> #mwlefoodfi .gt_asterisk {
#> font-size: 100%;
#> vertical-align: 0;
#> }
#>
#> #mwlefoodfi .gt_indent_1 {
#> text-indent: 5px;
#> }
#>
#> #mwlefoodfi .gt_indent_2 {
#> text-indent: 10px;
#> }
#>
#> #mwlefoodfi .gt_indent_3 {
#> text-indent: 15px;
#> }
#>
#> #mwlefoodfi .gt_indent_4 {
#> text-indent: 20px;
#> }
#>
#> #mwlefoodfi .gt_indent_5 {
#> text-indent: 25px;
#> }
#>
#> #mwlefoodfi .katex-display {
#> display: inline-flex !important;
#> margin-bottom: 0.75em !important;
#> }
#>
#> #mwlefoodfi div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after {
#> height: 0px !important;
#> }
#> </style>
#> <table class="gt_table" data-quarto-disable-processing="false" data-quarto-bootstrap="false">
#> <!--/html_preserve--><caption class='gt_caption'><span class='gt_from_md'>Demographic slide</span></caption><!--html_preserve-->
#> <thead>
#> <tr class="gt_col_headings">
#> <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1" scope="col" id="label"><span class='gt_from_md'><strong>Characteristic</strong></span></th>
#> <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1" scope="col" id="stat_1"><span class='gt_from_md'><strong>A: Drug X</strong><br />
#> N = 134</span><span class="gt_footnote_marks" style="white-space:nowrap;font-style:italic;font-weight:normal;line-height:0;"><sup>1</sup></span></th>
#> <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1" scope="col" id="stat_2"><span class='gt_from_md'><strong>B: Placebo</strong><br />
#> N = 134</span><span class="gt_footnote_marks" style="white-space:nowrap;font-style:italic;font-weight:normal;line-height:0;"><sup>1</sup></span></th>
#> <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1" scope="col" id="stat_3"><span class='gt_from_md'><strong>C: Combination</strong><br />
#> N = 132</span><span class="gt_footnote_marks" style="white-space:nowrap;font-style:italic;font-weight:normal;line-height:0;"><sup>1</sup></span></th>
#> </tr>
#> </thead>
#> <tbody class="gt_table_body">
#> <tr><td headers="label" class="gt_row gt_left">Sex</td>
#> <td headers="stat_1" class="gt_row gt_center"><br /></td>
#> <td headers="stat_2" class="gt_row gt_center"><br /></td>
#> <td headers="stat_3" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> F</td>
#> <td headers="stat_1" class="gt_row gt_center">79 (59%)</td>
#> <td headers="stat_2" class="gt_row gt_center">82 (61%)</td>
#> <td headers="stat_3" class="gt_row gt_center">70 (53%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> M</td>
#> <td headers="stat_1" class="gt_row gt_center">55 (41%)</td>
#> <td headers="stat_2" class="gt_row gt_center">52 (39%)</td>
#> <td headers="stat_3" class="gt_row gt_center">62 (47%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left">Age</td>
#> <td headers="stat_1" class="gt_row gt_center">33 (28, 39)</td>
#> <td headers="stat_2" class="gt_row gt_center">35 (30, 40)</td>
#> <td headers="stat_3" class="gt_row gt_center">35 (30, 40)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left">Race</td>
#> <td headers="stat_1" class="gt_row gt_center"><br /></td>
#> <td headers="stat_2" class="gt_row gt_center"><br /></td>
#> <td headers="stat_3" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> ASIAN</td>
#> <td headers="stat_1" class="gt_row gt_center">68 (51%)</td>
#> <td headers="stat_2" class="gt_row gt_center">67 (50%)</td>
#> <td headers="stat_3" class="gt_row gt_center">73 (55%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> BLACK OR AFRICAN AMERICAN</td>
#> <td headers="stat_1" class="gt_row gt_center">31 (23%)</td>
#> <td headers="stat_2" class="gt_row gt_center">28 (21%)</td>
#> <td headers="stat_3" class="gt_row gt_center">32 (24%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> WHITE</td>
#> <td headers="stat_1" class="gt_row gt_center">27 (20%)</td>
#> <td headers="stat_2" class="gt_row gt_center">26 (19%)</td>
#> <td headers="stat_3" class="gt_row gt_center">21 (16%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> AMERICAN INDIAN OR ALASKA NATIVE</td>
#> <td headers="stat_1" class="gt_row gt_center">8 (6.0%)</td>
#> <td headers="stat_2" class="gt_row gt_center">11 (8.2%)</td>
#> <td headers="stat_3" class="gt_row gt_center">6 (4.5%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> MULTIPLE</td>
#> <td headers="stat_1" class="gt_row gt_center">0 (0%)</td>
#> <td headers="stat_2" class="gt_row gt_center">1 (0.7%)</td>
#> <td headers="stat_3" class="gt_row gt_center">0 (0%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER</td>
#> <td headers="stat_1" class="gt_row gt_center">0 (0%)</td>
#> <td headers="stat_2" class="gt_row gt_center">1 (0.7%)</td>
#> <td headers="stat_3" class="gt_row gt_center">0 (0%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> OTHER</td>
#> <td headers="stat_1" class="gt_row gt_center">0 (0%)</td>
#> <td headers="stat_2" class="gt_row gt_center">0 (0%)</td>
#> <td headers="stat_3" class="gt_row gt_center">0 (0%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> UNKNOWN</td>
#> <td headers="stat_1" class="gt_row gt_center">0 (0%)</td>
#> <td headers="stat_2" class="gt_row gt_center">0 (0%)</td>
#> <td headers="stat_3" class="gt_row gt_center">0 (0%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left">Ethnicity</td>
#> <td headers="stat_1" class="gt_row gt_center"><br /></td>
#> <td headers="stat_2" class="gt_row gt_center"><br /></td>
#> <td headers="stat_3" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> NOT REPORTED</td>
#> <td headers="stat_1" class="gt_row gt_center">6 (4.5%)</td>
#> <td headers="stat_2" class="gt_row gt_center">10 (7.5%)</td>
#> <td headers="stat_3" class="gt_row gt_center">11 (8.3%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> HISPANIC OR LATINO</td>
#> <td headers="stat_1" class="gt_row gt_center">15 (11%)</td>
#> <td headers="stat_2" class="gt_row gt_center">18 (13%)</td>
#> <td headers="stat_3" class="gt_row gt_center">15 (11%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> NOT HISPANIC OR LATINO</td>
#> <td headers="stat_1" class="gt_row gt_center">104 (78%)</td>
#> <td headers="stat_2" class="gt_row gt_center">103 (77%)</td>
#> <td headers="stat_3" class="gt_row gt_center">101 (77%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> UNKNOWN</td>
#> <td headers="stat_1" class="gt_row gt_center">9 (6.7%)</td>
#> <td headers="stat_2" class="gt_row gt_center">3 (2.2%)</td>
#> <td headers="stat_3" class="gt_row gt_center">5 (3.8%)</td></tr>
#> </tbody>
#> <tfoot>
#> <tr class="gt_footnotes">
#> <td class="gt_footnote" colspan="4"><span class="gt_footnote_marks" style="white-space:nowrap;font-style:italic;font-weight:normal;line-height:0;"><sup>1</sup></span> <span class='gt_from_md'>n (%); Median (Q1, Q3)</span></td>
#> </tr>
#> </tfoot>
#> </table>
#> </div>
#>
#> $t_dm_slide_FAS
#> Demographic slide
#>
#> ———————————————————————————————————————————————————————————————————————————————————————————————————————
#> Global
#> A: Drug X B: Placebo C: Combination All Patients
#> ———————————————————————————————————————————————————————————————————————————————————————————————————————
#> Sex
#> F 79 (59%) 82 (61.2%) 70 (53%) 231 (57.8%)
#> M 55 (41%) 52 (38.8%) 62 (47%) 169 (42.2%)
#> Age
#> Median 33.00 35.00 35.00 34.00
#> Min - Max 21.0 - 50.0 21.0 - 62.0 20.0 - 69.0 20.0 - 69.0
#> Race
#> ASIAN 68 (50.7%) 67 (50%) 73 (55.3%) 208 (52%)
#> BLACK OR AFRICAN AMERICAN 31 (23.1%) 28 (20.9%) 32 (24.2%) 91 (22.8%)
#> WHITE 27 (20.1%) 26 (19.4%) 21 (15.9%) 74 (18.5%)
#> AMERICAN INDIAN OR ALASKA NATIVE 8 (6%) 11 (8.2%) 6 (4.5%) 25 (6.2%)
#> MULTIPLE 0 1 (0.7%) 0 1 (0.2%)
#> NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER 0 1 (0.7%) 0 1 (0.2%)
#> OTHER 0 0 0 0
#> UNKNOWN 0 0 0 0
#> Ethnicity
#> NOT REPORTED 6 (4.5%) 10 (7.5%) 11 (8.3%) 27 (6.8%)
#> HISPANIC OR LATINO 15 (11.2%) 18 (13.4%) 15 (11.4%) 48 (12%)
#> NOT HISPANIC OR LATINO 104 (77.6%) 103 (76.9%) 101 (76.5%) 308 (77%)
#> UNKNOWN 9 (6.7%) 3 (2.2%) 5 (3.8%) 17 (4.2%)
#>