diff --git a/NAMESPACE b/NAMESPACE index f4762eb..d88c789 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -39,7 +39,6 @@ export(plotly_legend) export(process_edish_data) export(process_event_analysis) export(process_tornado_data) -export(process_vx_bar_plot) export(process_vx_scatter_data) export(reverselog_trans) export(risk_stat) diff --git a/R/adsl_r001.R b/R/adsl_summary.R similarity index 100% rename from R/adsl_r001.R rename to R/adsl_summary.R diff --git a/man/process_vx_bar_plot.Rd b/man/process_vx_bar_plot.Rd deleted file mode 100644 index aea69c5..0000000 --- a/man/process_vx_bar_plot.Rd +++ /dev/null @@ -1,92 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/process_vx_bar_plot.R -\name{process_vx_bar_plot} -\alias{process_vx_bar_plot} -\title{Pre-Process data for Bar Plot} -\usage{ -process_vx_bar_plot( - dataset_adsl, - adsl_subset = "SAFFL=='Y'", - dataset_analysis, - analysis_subset = NA_character_, - overall_subset = NA_character_, - denom_subset = NA_character_, - split_by = NA_character_, - trtvar = "TRT01A", - trtsort = "TRT01AN", - xvar = "ATPTN", - yvar = "PCT", - pctdisp = "DPTVAR", - legendbign = "Y" -) -} -\arguments{ -\item{dataset_adsl}{(\code{data.frame}) ADSL dataset.} - -\item{adsl_subset}{(\code{string}) Subset condition to be applied on \code{dataset_adsl}.} - -\item{dataset_analysis}{(\code{data.frame}) Analysis Dataset.} - -\item{analysis_subset}{Subset conditions for analysis of dependent variable -Applicable only to numerator calculation for \%} - -\item{overall_subset}{Subset conditions for overall data.} - -\item{denom_subset}{Subset condition to be applied to data set for -calculating denominator.} - -\item{split_by}{(\code{string}) By variable for stratification.} - -\item{trtvar}{(\code{string}) Treatment Variable to be created for analysis.} - -\item{trtsort}{(\code{string}) Variable to sort treatment variable by.} - -\item{xvar}{Categorical Analysis variable for X axis} - -\item{yvar}{Y axis variable/statistic. Possible Values: "FREQ"/"PCT"} - -\item{pctdisp}{Method to calculate denominator (for \%) by -Possible values: "TRT","VAR","COL","SUBGRP","CAT","NONE","NO","DPTVAR"} - -\item{legendbign}{(\code{string}) Display count as (N = ..) in Treatment legend? Values: "Y"/"N"} -} -\value{ -mcatstat dataset as data frame. -} -\description{ -Pre-Process data for Bar Plot -} -\details{ -\itemize{ -\item Subset Processing -Applying population subset selected -Applying denominator/overall subset condition passed by the user -Applying analysis/numerator subset condition passed by the user. -\item pctdisp has possible values for method to get denominator to calculate -percentage, passed to \code{mcatstat()}. The commonly passed value for vaccine -bar plot is: -DPTVAR: Percentage within each Treatment-By group(s)-Subgroup(s)-dptvar -combination. -} -} -\examples{ -data(vx_bar_data) - -process_vx_bar_plot( - dataset_adsl = vx_bar_data$adsl, - adsl_subset = "SAFFL=='Y'", - dataset_analysis = vx_bar_data$adfacevd, - analysis_subset = "ATPTN <= 14 & toupper(FAOBJ) == 'PAIN AT INJECTION SITE' & - !(AVAL \%in\% c(0, 0.5)) & FATESTCD != 'OCCUR' & !is.na(AVAL)", - denom_subset = "ATPTN <= 14 & toupper(FAOBJ) == 'PAIN AT INJECTION SITE' & - !(AVAL \%in\% c(0, 0.5))", - overall_subset = NA, - split_by = "SEX", - trtvar = "TRT01A", - trtsort = "TRT01AN", - xvar = "ATPTN", - yvar = "PCT", - pctdisp = "DPTVAR" -) - -} diff --git a/tests/testthat/_snaps/adsl_summary.md b/tests/testthat/_snaps/adsl_summary.md new file mode 100644 index 0000000..ee34625 --- /dev/null +++ b/tests/testthat/_snaps/adsl_summary.md @@ -0,0 +1,318 @@ +# adsl_summary works as expected + + Code + print(tibble::as_tibble(dataf), n = Inf, width = Inf) + Output + # A tibble: 21 x 9 + BYVAR1 DPTVAR DPTVAL DPTVARN DPTVALN CN + + 1 F Age Group <65 1 1 C + 2 F Age Group 65-80 1 2 C + 3 F Age Group >80 1 3 C + 4 F Age N 2 1 N + 5 F Age Range 2 2 N + 6 F Age Mean (SD) 2 3 N + 7 F Age Median 2 4 N + 8 F Age Interquartile Range 2 5 N + 9 F Race WHITE 3 1 C + 10 F Race BLACK OR AFRICAN AMERICAN 3 2 C + 11 M Age Group <65 1 1 C + 12 M Age Group 65-80 1 2 C + 13 M Age Group >80 1 3 C + 14 M Age N 2 1 N + 15 M Age Range 2 2 N + 16 M Age Mean (SD) 2 3 N + 17 M Age Median 2 4 N + 18 M Age Interquartile Range 2 5 N + 19 M Race WHITE 3 1 C + 20 M Race BLACK OR AFRICAN AMERICAN 3 2 C + 21 M Race AMERICAN INDIAN OR ALASKA NATIVE 3 6 C + `Placebo (N=86)` `Xanomeline Low Dose (N=84)` `Xanomeline High Dose (N=84)` + + 1 9 (10.47%) 5 ( 5.95%) 5 ( 5.95%) + 2 22 (25.58%) 28 (33.33%) 28 (33.33%) + 3 22 (25.58%) 17 (20.24%) 7 ( 8.33%) + 4 53 50 40 + 5 (59.00,89.00) (54.00,87.00) (56.00,88.00) + 6 76.36 (8.73) 75.68 (8.09) 74.67 (7.67) + 7 78.00 77.50 76.00 + 8 (70.00, 84.00) (72.00, 81.00) (72.00, 79.00) + 9 48 (55.81%) 44 (52.38%) 34 (40.48%) + 10 5 ( 5.81%) 6 ( 7.14%) 6 ( 7.14%) + 11 5 ( 5.81%) 3 ( 3.57%) 6 ( 7.14%) + 12 20 (23.26%) 19 (22.62%) 27 (32.14%) + 13 8 ( 9.30%) 12 (14.29%) 11 (13.10%) + 14 33 34 44 + 15 (52.00,85.00) (51.00,88.00) (56.00,86.00) + 16 73.36 (8.15) 75.65 (8.69) 74.11 (8.16) + 17 74.00 77.50 77.00 + 18 (69.00, 80.00) (68.00, 82.00) (69.00, 80.50) + 19 30 (34.88%) 34 (40.48%) 40 (47.62%) + 20 3 ( 3.49%) 0 3 ( 3.57%) + 21 0 0 1 ( 1.19%) + +--- + + Code + print(tibble::as_tibble(dataf_), n = Inf, width = Inf) + Output + # A tibble: 74 x 9 + BYVAR1 DPTVAR DPTVAL DPTVARN DPTVALN CN + + 1 F Age Group <65 1 1 C + 2 F Age Group 65-80 1 2 C + 3 F Age Group >80 1 3 C + 4 F Age 54 2 3 C + 5 F Age 56 2 4 C + 6 F Age 57 2 5 C + 7 F Age 59 2 6 C + 8 F Age 60 2 7 C + 9 F Age 61 2 8 C + 10 F Age 62 2 9 C + 11 F Age 63 2 10 C + 12 F Age 64 2 11 C + 13 F Age 66 2 13 C + 14 F Age 67 2 14 C + 15 F Age 68 2 15 C + 16 F Age 69 2 16 C + 17 F Age 70 2 17 C + 18 F Age 71 2 18 C + 19 F Age 72 2 19 C + 20 F Age 73 2 20 C + 21 F Age 74 2 21 C + 22 F Age 75 2 22 C + 23 F Age 76 2 23 C + 24 F Age 77 2 24 C + 25 F Age 78 2 25 C + 26 F Age 79 2 26 C + 27 F Age 80 2 27 C + 28 F Age 81 2 28 C + 29 F Age 82 2 29 C + 30 F Age 83 2 30 C + 31 F Age 84 2 31 C + 32 F Age 85 2 32 C + 33 F Age 86 2 33 C + 34 F Age 87 2 34 C + 35 F Age 88 2 35 C + 36 F Age 89 2 36 C + 37 F Race WHITE 3 1 C + 38 F Race BLACK OR AFRICAN AMERICAN 3 2 C + 39 M Age Group <65 1 1 C + 40 M Age Group 65-80 1 2 C + 41 M Age Group >80 1 3 C + 42 M Age 51 2 1 C + 43 M Age 52 2 2 C + 44 M Age 56 2 4 C + 45 M Age 57 2 5 C + 46 M Age 61 2 8 C + 47 M Age 62 2 9 C + 48 M Age 63 2 10 C + 49 M Age 64 2 11 C + 50 M Age 65 2 12 C + 51 M Age 67 2 14 C + 52 M Age 68 2 15 C + 53 M Age 69 2 16 C + 54 M Age 70 2 17 C + 55 M Age 71 2 18 C + 56 M Age 72 2 19 C + 57 M Age 73 2 20 C + 58 M Age 74 2 21 C + 59 M Age 75 2 22 C + 60 M Age 77 2 24 C + 61 M Age 78 2 25 C + 62 M Age 79 2 26 C + 63 M Age 80 2 27 C + 64 M Age 81 2 28 C + 65 M Age 82 2 29 C + 66 M Age 83 2 30 C + 67 M Age 84 2 31 C + 68 M Age 85 2 32 C + 69 M Age 86 2 33 C + 70 M Age 87 2 34 C + 71 M Age 88 2 35 C + 72 M Race WHITE 3 1 C + 73 M Race BLACK OR AFRICAN AMERICAN 3 2 C + 74 M Race AMERICAN INDIAN OR ALASKA NATIVE 3 6 C + `Placebo (N=86)` `Xanomeline Low Dose (N=84)` `Xanomeline High Dose (N=84)` + + 1 9 (10.47%) 5 ( 5.95%) 5 ( 5.95%) + 2 22 (25.58%) 28 (33.33%) 28 (33.33%) + 3 22 (25.58%) 17 (20.24%) 7 ( 8.33%) + 4 0 1 (1.19%) 0 + 5 0 2 (2.38%) 2 (2.38%) + 6 0 1 (1.19%) 0 + 7 2 (2.33%) 0 0 + 8 1 (1.16%) 1 (1.19%) 1 (1.19%) + 9 0 0 1 (1.19%) + 10 1 (1.16%) 0 0 + 11 2 (2.33%) 0 1 (1.19%) + 12 3 (3.49%) 0 0 + 13 1 (1.16%) 0 0 + 14 1 (1.16%) 1 (1.19%) 2 (2.38%) + 15 1 (1.16%) 2 (2.38%) 0 + 16 1 (1.16%) 0 1 (1.19%) + 17 1 (1.16%) 0 0 + 18 1 (1.16%) 3 (3.57%) 1 (1.19%) + 19 1 (1.16%) 3 (3.57%) 3 (3.57%) + 20 2 (2.33%) 1 (1.19%) 2 (2.38%) + 21 2 (2.33%) 3 (3.57%) 2 (2.38%) + 22 0 2 (2.38%) 2 (2.38%) + 23 4 (4.65%) 4 (4.76%) 4 (4.76%) + 24 1 (1.16%) 1 (1.19%) 3 (3.57%) + 25 3 (3.49%) 2 (2.38%) 3 (3.57%) + 26 1 (1.16%) 3 (3.57%) 3 (3.57%) + 27 2 (2.33%) 3 (3.57%) 2 (2.38%) + 28 6 (6.98%) 6 (7.14%) 1 (1.19%) + 29 0 1 (1.19%) 0 + 30 2 (2.33%) 3 (3.57%) 1 (1.19%) + 31 3 (3.49%) 5 (5.95%) 2 (2.38%) + 32 2 (2.33%) 0 1 (1.19%) + 33 3 (3.49%) 1 (1.19%) 1 (1.19%) + 34 3 (3.49%) 1 (1.19%) 0 + 35 2 (2.33%) 0 1 (1.19%) + 36 1 (1.16%) 0 0 + 37 48 (55.81%) 44 (52.38%) 34 (40.48%) + 38 5 ( 5.81%) 6 ( 7.14%) 6 ( 7.14%) + 39 5 ( 5.81%) 3 ( 3.57%) 6 ( 7.14%) + 40 20 (23.26%) 19 (22.62%) 27 (32.14%) + 41 8 ( 9.30%) 12 (14.29%) 11 (13.10%) + 42 0 1 (1.19%) 0 + 43 1 (1.16%) 0 0 + 44 0 0 2 (2.38%) + 45 1 (1.16%) 0 1 (1.19%) + 46 1 (1.16%) 1 (1.19%) 2 (2.38%) + 47 0 1 (1.19%) 0 + 48 0 0 1 (1.19%) + 49 2 (2.33%) 0 0 + 50 1 (1.16%) 1 (1.19%) 2 (2.38%) + 51 1 (1.16%) 1 (1.19%) 2 (2.38%) + 52 0 4 (4.76%) 0 + 53 2 (2.33%) 1 (1.19%) 2 (2.38%) + 54 3 (3.49%) 0 1 (1.19%) + 55 1 (1.16%) 2 (2.38%) 1 (1.19%) + 56 1 (1.16%) 0 1 (1.19%) + 57 1 (1.16%) 0 3 (3.57%) + 58 3 (3.49%) 1 (1.19%) 2 (2.38%) + 59 2 (2.33%) 1 (1.19%) 1 (1.19%) + 60 1 (1.16%) 3 (3.57%) 5 (5.95%) + 61 2 (2.33%) 2 (2.38%) 1 (1.19%) + 62 1 (1.16%) 2 (2.38%) 4 (4.76%) + 63 1 (1.16%) 1 (1.19%) 2 (2.38%) + 64 2 (2.33%) 1 (1.19%) 3 (3.57%) + 65 2 (2.33%) 3 (3.57%) 4 (4.76%) + 66 1 (1.16%) 1 (1.19%) 0 + 67 1 (1.16%) 3 (3.57%) 2 (2.38%) + 68 2 (2.33%) 1 (1.19%) 0 + 69 0 0 2 (2.38%) + 70 0 2 (2.38%) 0 + 71 0 1 (1.19%) 0 + 72 30 (34.88%) 34 (40.48%) 40 (47.62%) + 73 3 ( 3.49%) 0 3 ( 3.57%) + 74 0 0 1 ( 1.19%) + +# adsl_summary works with subsets + + Code + print(actual, n = Inf, width = Inf) + Output + # A tibble: 19 x 9 + BYVAR1 DPTVAR DPTVAL DPTVARN DPTVALN CN + + 1 F Age Group <65 1 1 C + 2 F Age N 2 1 N + 3 F Age Range 2 2 N + 4 F Age Meansd 2 3 N + 5 F Age Median 2 4 N + 6 F Age IQR 2 5 N + 7 F Sex F 3 1 C + 8 F Race WHITE 4 1 C + 9 F Race BLACK OR AFRICAN AMERICAN 4 2 C + 10 M Age Group <65 1 1 C + 11 M Age N 2 1 N + 12 M Age Range 2 2 N + 13 M Age Meansd 2 3 N + 14 M Age Median 2 4 N + 15 M Age IQR 2 5 N + 16 M Sex M 3 2 C + 17 M Race WHITE 4 1 C + 18 M Race BLACK OR AFRICAN AMERICAN 4 2 C + 19 M Race AMERICAN INDIAN OR ALASKA NATIVE 4 6 C + `Placebo (N=86)` `Xanomeline Low Dose (N=84)` `Xanomeline High Dose (N=84)` + + 1 9 (10.47%) 5 ( 5.95%) 5 ( 5.95%) + 2 22 17 7 + 3 (81.00,89.00) (81.00,87.00) (81.00,88.00) + 4 84.45 (2.67) 82.94 (1.85) 84.43 (2.23) + 5 84.50 83.00 84.00 + 6 (81.00, 87.00) (81.00, 84.00) (83.00, 86.00) + 7 53 (61.63%) 50 (59.52%) 40 (47.62%) + 8 48 (55.81%) 44 (52.38%) 34 (40.48%) + 9 5 ( 5.81%) 6 ( 7.14%) 6 ( 7.14%) + 10 5 ( 5.81%) 3 ( 3.57%) 6 ( 7.14%) + 11 8 12 11 + 12 (81.00,85.00) (81.00,88.00) (81.00,86.00) + 13 82.88 (1.64) 84.08 (2.27) 82.82 (1.89) + 14 82.50 84.00 82.00 + 15 (81.50, 84.50) (82.00, 86.00) (81.00, 84.00) + 16 33 (38.37%) 34 (40.48%) 44 (52.38%) + 17 30 (34.88%) 34 (40.48%) 40 (47.62%) + 18 3 ( 3.49%) 0 3 ( 3.57%) + 19 0 0 1 ( 1.19%) + +--- + + Code + print(tibble::as_tibble(actual_), n = Inf, width = Inf) + Output + # A tibble: 23 x 9 + BYVAR1 DPTVAR DPTVAL DPTVARN DPTVALN CN + + 1 F Age Group <65 1 1 C + 2 F Age Group 65-80 1 2 C + 3 F Age Group >80 1 3 C + 4 F Age N 2 1 N + 5 F Age Range 2 2 N + 6 F Age Meansd 2 3 N + 7 F Age Median 2 4 N + 8 F Age IQR 2 5 N + 9 F Sex F 3 1 C + 10 F Race WHITE 4 1 C + 11 F Race BLACK OR AFRICAN AMERICAN 4 2 C + 12 M Age Group <65 1 1 C + 13 M Age Group 65-80 1 2 C + 14 M Age Group >80 1 3 C + 15 M Age N 2 1 N + 16 M Age Range 2 2 N + 17 M Age Meansd 2 3 N + 18 M Age Median 2 4 N + 19 M Age IQR 2 5 N + 20 M Sex M 3 2 C + 21 M Race WHITE 4 1 C + 22 M Race BLACK OR AFRICAN AMERICAN 4 2 C + 23 M Race AMERICAN INDIAN OR ALASKA NATIVE 4 6 C + `Placebo (N=86)` `Xanomeline Low Dose (N=84)` `Xanomeline High Dose (N=84)` + + 1 9 (11.54%) 5 ( 6.41%) 5 ( 6.76%) + 2 22 (28.21%) 28 (35.90%) 28 (37.84%) + 3 22 (28.21%) 17 (21.79%) 7 ( 9.46%) + 4 53 50 40 + 5 (59.00,89.00) (54.00,87.00) (56.00,88.00) + 6 76.36 (8.73) 75.68 (8.09) 74.67 (7.67) + 7 78.00 77.50 76.00 + 8 (70.00, 84.00) (72.00, 81.00) (72.00, 79.00) + 9 53 (61.63%) 50 (59.52%) 40 (47.62%) + 10 48 (55.81%) 44 (52.38%) 34 (40.48%) + 11 5 ( 5.81%) 6 ( 7.14%) 6 ( 7.14%) + 12 5 ( 6.41%) 3 ( 3.85%) 6 ( 8.11%) + 13 20 (25.64%) 19 (24.36%) 27 (36.49%) + 14 8 (10.26%) 12 (15.38%) 11 (14.86%) + 15 33 34 44 + 16 (52.00,85.00) (51.00,88.00) (56.00,86.00) + 17 73.36 (8.15) 75.65 (8.69) 74.11 (8.16) + 18 74.00 77.50 77.00 + 19 (69.00, 80.00) (68.00, 82.00) (69.00, 80.50) + 20 33 (38.37%) 34 (40.48%) 44 (52.38%) + 21 30 (34.88%) 34 (40.48%) 40 (47.62%) + 22 3 ( 3.49%) 0 3 ( 3.57%) + 23 0 0 1 ( 1.19%) + diff --git a/tests/testthat/_snaps/tbl_display.md b/tests/testthat/_snaps/tbl_display.md new file mode 100644 index 0000000..46c5c32 --- /dev/null +++ b/tests/testthat/_snaps/tbl_display.md @@ -0,0 +1,114 @@ +# tbl_processor works standard + + Code + print(tbl_data, n = Inf, width = Inf) + Output + # A tibble: 26 x 9 + BYVAR1 DPTVAL DPTVARN DPTVALN + + 1 HISPANIC OR LATINO "Age (Years), n (%)" 1 0 + 2 HISPANIC OR LATINO "\t\t<65" 1 1 + 3 HISPANIC OR LATINO "\t\t65-80" 1 2 + 4 HISPANIC OR LATINO "\t\t>80" 1 3 + 5 HISPANIC OR LATINO "NONE" 2 0 + 6 HISPANIC OR LATINO "\t\tn" 2 1 + 7 HISPANIC OR LATINO "\t\tMean (SD)" 2 2 + 8 HISPANIC OR LATINO "Gender, n (%)" 3 0 + 9 HISPANIC OR LATINO "\t\tF" 3 1 + 10 HISPANIC OR LATINO "\t\tM" 3 2 + 11 HISPANIC OR LATINO "Race, n (%)" 4 0 + 12 HISPANIC OR LATINO "\t\tWHITE" 4 1 + 13 NOT HISPANIC OR LATINO "Age (Years), n (%)" 1 0 + 14 NOT HISPANIC OR LATINO "\t\t<65" 1 1 + 15 NOT HISPANIC OR LATINO "\t\t65-80" 1 2 + 16 NOT HISPANIC OR LATINO "\t\t>80" 1 3 + 17 NOT HISPANIC OR LATINO "NONE" 2 0 + 18 NOT HISPANIC OR LATINO "\t\tn" 2 1 + 19 NOT HISPANIC OR LATINO "\t\tMean (SD)" 2 2 + 20 NOT HISPANIC OR LATINO "Gender, n (%)" 3 0 + 21 NOT HISPANIC OR LATINO "\t\tF" 3 1 + 22 NOT HISPANIC OR LATINO "\t\tM" 3 2 + 23 NOT HISPANIC OR LATINO "Race, n (%)" 4 0 + 24 NOT HISPANIC OR LATINO "\t\tWHITE" 4 1 + 25 NOT HISPANIC OR LATINO "\t\tBLACK OR AFRICAN AMERICAN" 4 2 + 26 NOT HISPANIC OR LATINO "\t\tAMERICAN INDIAN OR ALASKA NATIVE" 4 6 + CN `Placebo (N=86)` `Xanomeline Low Dose (N=84)` + + 1 + 2 C 2 ( 2.33%) 2 ( 2.38%) + 3 C 0 2 ( 2.38%) + 4 C 1 ( 1.16%) 2 ( 2.38%) + 5 + 6 N 3 6 + 7 N 71.00 (13.00) 70.67 (12.63) + 8 + 9 C 2 ( 2.33%) 4 ( 4.76%) + 10 C 1 ( 1.16%) 2 ( 2.38%) + 11 + 12 C 3 ( 3.49%) 6 ( 7.14%) + 13 + 14 C 12 (13.95%) 6 ( 7.14%) + 15 C 42 (48.84%) 45 (53.57%) + 16 C 29 (33.72%) 27 (32.14%) + 17 + 18 N 83 78 + 19 N 75.36 (8.47) 76.05 (7.85) + 20 + 21 C 51 (59.30%) 46 (54.76%) + 22 C 32 (37.21%) 32 (38.10%) + 23 + 24 C 75 (87.21%) 72 (85.71%) + 25 C 8 ( 9.30%) 6 ( 7.14%) + 26 C 0 0 + `Xanomeline High Dose (N=84)` `Total (N=254)` + + 1 + 2 3 ( 3.57%) 7 ( 2.76%) + 3 0 2 ( 0.79%) + 4 0 3 ( 1.18%) + 5 + 6 3 12 + 7 58.33 (4.04) 67.67 (11.74) + 8 + 9 1 ( 1.19%) 7 ( 2.76%) + 10 2 ( 2.38%) 5 ( 1.97%) + 11 + 12 3 ( 3.57%) 12 ( 4.72%) + 13 + 14 8 ( 9.52%) 26 (10.24%) + 15 55 (65.48%) 142 (55.91%) + 16 18 (21.43%) 74 (29.13%) + 17 + 18 81 242 + 19 74.98 (7.36) 75.45 (7.89) + 20 + 21 39 (46.43%) 136 (53.54%) + 22 42 (50.00%) 106 (41.73%) + 23 + 24 71 (84.52%) 218 (85.83%) + 25 9 (10.71%) 23 ( 9.06%) + 26 1 ( 1.19%) 1 ( 0.39%) + +# tbl_processor works without trt/dpt + + Code + print(tbl_data1, n = Inf, width = Inf) + Output + # A tibble: 2 x 5 + BYVAR1 DPTVALN DPTVARN CN `Participants, n (%) (N = 254)` + + 1 HISPANIC OR LATINO 1 1 C 12 ( 4.72%) + 2 NOT HISPANIC OR LATINO 1 1 C 242 (95.28%) + +# Empty_tbl works + + Code + tbl_empty + Output + a flextable object. + col_keys: `X` + header has 1 row(s) + body has 1 row(s) + original dataset sample: + [1] "No participant meets the reporting criteria" + diff --git a/tests/testthat/test-adsl_r001.R b/tests/testthat/test-adsl_summary.R similarity index 100% rename from tests/testthat/test-adsl_r001.R rename to tests/testthat/test-adsl_summary.R