h_glm_negbin to h_glm_count to enable count data analysis using a negative binomial model.grade_groups_only to count_occurrences_by_grade to allow users to only display rows for specified grade groups.df2gg that converts data.frame objects to ggplot objects.control_surv_med_annot and control_coxph_annot to configure g_km annotation table sizes/positions.g_km to output a ggplot object instead of a grob object.g_forest to output a ggplot object instead of a grob object.mean_pval) updated from "xx.xx" to "x.xxxx | (<0.0001)".rtable2gg to clean up appearance of text labels.s_ancova causing incorrect difference calculations for arm variables with irregular levels.format_count_fraction_fixed_dp that did not have the same print when the fraction was 1 (100%).g_lineplot causing default labels not to update according to specified control settings.NA values.expect_snapshot_ggplot to test setup file to process plot snapshot tests and allow plot dimensions to be set.ggplot2 3.5.0.individual_patient_plot.R to g_ipp.R.time_unit_input, time_unit_output, na_level and indent_mod.summarize_vars, control_summarize_vars, a_compare, create_afun_summary, create_afun_compare, and summary_custom.vdiffr package from Suggests in DESCRIPTION file.strat, to be renamed to strata, within the variables argument to h_rsp_to_logistic_variables, h_logistic_mult_cont_df, h_odds_ratio_subgroups_df, h_coxreg_mult_cont_df, h_coxph_subgroups_df, h_tbl_coxph_pairwise, extract_rsp_biomarkers, extract_rsp_subgroups, extract_survival_biomarkers, and extract_survival_subgroups.strat argument to s_coxph_pairwise and replaced it with the strata argument.forest_grob, forest_dot_line, forest_viewport, vp_forest_table_part, and grid.forest functions.h_ggkm, h_decompose_gg, h_km_layout, h_grob_tbl_at_risk, h_grob_median_surv, h_grob_y_annot, and h_grob_coxph.grob/grid related functions stack_grobs, arrange_grobs, and draw_grob which are no longer used in tern.ref_group_position function to place the reference group facet last, first or at a certain position.keep_level_order split function to retain original order of levels in a split.level_order split function to reorder manually the levels.get_indents_from_stats to format and return indent modifiers for a given set of statistics.apply_auto_formatting to check for "auto" formats and replace them with implementation of format_auto in analyze functions.labels_use_control to modify labels with control specifications.tern_default_stats.count_occurrences analyze function, summarize_occurrences.surv_time for censored range observations, controlled via the ref_fn_censor parameter.h_adlb_abnormal_by_worst_grade to prepare ADLB data to use as input in count_abnormal_by_worst_grade.s_bland_altman function to assess agreement between two numerical vectors.rtable2gg that converts rtable objects to ggplot objects.na_str globally with set_default_na_str() and added default_na_str() for all interested functions.ref_group_coxph parameter to g_km to specify the reference group used for pairwise Cox-PH calculations when annot_coxph = TRUE.annot_coxph_ref_lbls parameter to g_km to enable printing the reference group in table labels when annot_coxph = TRUE.x_lab parameter to g_lineplot to customize x-axis label.g_lineplot.arm_y argument.count_by input in analyze_num_patients and summarize_num_patients.g_lineplot.decorate_grob preventing text wrapping from accounting for font size.na_str argument in all column-wise analysis and tabulation functions.to_string_matrix to take into account widths and other printing parameters.na_str argument to analyze & summarize_row_groups wrapper functions count_abnormal, count_abnormal_by_baseline, count_abnormal_by_marked, count_abnormal_by_worst_grade, count_abnormal_lab_worsen_by_baseline, count_cumulative, count_missed_doses, count_occurrences, count_occurrences_by_grade, summarize_occurrences_by_grade, summarize_patients_events_in_cols, count_patients_with_event, count_patients_with_flags, count_values, estimate_multinomial_response, estimate_proportion, h_tab_one_biomarker, estimate_incidence_rate, logistic_summary_by_flag, estimate_odds_ratio, estimate_proportion_diff, test_proportion_diff, summarize_ancova, summarize_change, summarize_glm_count, summarize_num_patients, analyze_num_patients, summarize_patients_exposure_in_cols, coxph_pairwise, tabulate_survival_subgroups, surv_time, and surv_timepoint.format_count_fraction_lt10 for formatting count_fraction with special consideration when count is less than 10.s_summary.logical output for count_fraction when denominator is zero to display as NA instead of 0 in tables.analyze_vars_in_cols to allow character input to indicate whether nominal time point is post-dose or pre-dose when applying the 1/3 imputation rule.g_km causing an error when converting certain annotation width units.na_level argument in s_count_abnormal_by_baseline, a_summary, analyze_vars, analyze_vars_in_cols, compare_vars, h_map_for_count_abnormal, h_stack_by_baskets, summarize_colvars, a_coxreg, and summarize_coxreg and replaced it with the na_str argument.strata and cohort_id parameters renamed to group_var and subject_var respectively in g_lineplot and control_lineplot_vars .imputation_rule function to apply imputation rule to data.format_sigfig to allow for numeric value formatting by a specified number of significant figures.tern_default_formats and tern_default_labels, respectively.get_stats to return methods from given statistical method groups.get_formats_from_stats to return formats and get_labels_from_stats to return labels for a given set of statistics."auto" option for .formats. It uses format_auto to determine automatically the number of digits.title argument to h_grob_tbl_at_risk and annot_at_risk_title argument to g_km and h_km_layout which allows user to add “Patients at Risk” title to Kaplan-Meier at risk annotation table.tabulate_rsp_subgroups to pass sanitation checks by preventing creation of degenerate subtables.analyze_vars_in_cols to use caching, allow implementation of imputation rule via the imp_rule argument, and allow user to specify cell alignment via the .aligns argument.add_rowcounts to allow addition of row counts from alt_counts_df using the alt_counts argument.gp argument to g_forest to control graphical parameters such as font size.utils_defaults_handling.R.summary_custom() and a_summary() as a S3 method.p-value in the discrete case to pval_counts.a_summary_internal() in favor of only one main a_summary().stat_propdiff_ci function to calculate proportion/risk difference and CI.riskdiff argument to functions count_occurrences, count_occurrences_by_grade, count_patients_with_event, count_patients_with_flags, analyze_num_patients, and summarize_num_patients.a_summary to no longer use the helper function create_afun_summary.summarize_vars and compare_vars to use the refactored a_summary function.ungroup_stats to ungroup statistics calculated for factor variables, and a_summary_internal to perform calculations for a_summary.s_count_occurrences_by_grade so that “missing” grade always appears as the final level.analyze_vars_in_cols when categorical data was used.s_count_occurrences_by_grade so that levels are not relabeled when reordering to account for “missing” grades..N_row and .N_col parameters.df_explicit_na. Changes in NA values should happen externally to tern functions, depending on users’ needs.create_afun_summary and create_afun_compare.ylim argument to g_km to allow the user to set custom limits for the y-axis.g_km which checks whether there is one arm present in the data when annot_coxph is true.flag_labels argument to s_count_patients_with_flags to enable more label handling options in count_patients_by_flags.nested argument to analyze wrapper functions count_abnormal, count_abnormal_by_baseline, count_abnormal_by_marked, count_abnormal_by_worst_grade, count_abnormal_lab_worsen_by_baseline, count_cumulative, count_missed_doses, count_occurrences, count_occurrences_by_grade, count_patients_with_event, count_patients_with_flags, count_values, estimate_multinomial_response, estimate_proportion, estimate_incidence_rate, estimate_odds_ratio, estimate_proportion_diff, test_proportion_diff, summarize_ancova, summarize_change, summarize_glm_count, analyze_num_patients, coxph_pairwise, surv_time, and surv_timepoint.summarize_vars and control_summarize_vars. Renamed into analyze_vars and control_analyze_vars to reflect underlying rtables machinery while keeping backward compatibility with aliases.character class to h_coxreg_inter_effect enabling character covariates in summarize_coxreg.time_unit_input and time_unit_output arguments and replaced them with the input_time_unit and num_pt_year, respectively, in control_incidence_rate.pairwise function.a_compare and replaced it with a_summary with argument compare = TRUE.create_afun_summary and create_afun_compare which are no longer used by a_summary and a_compare respectively.sum(weights) for M1mac installation.g_km plot “at risk” annotation tables.analyze_patients_exposure_in_cols..indent_mods argument in functions h_tab_one_biomarker, h_tab_rsp_one_biomarker, h_tab_surv_one_biomarker, summarize_logistic, logistic_summary_by_flag, tabulate_rsp_biomarkers, a_coxreg, summarize_coxreg, tabulate_survival_biomarkers, surv_time, surv_timepoint, and cfun_by_flag.summarize_coxreg to print covariates in data rows for univariate Cox regression with no interactions and content rows otherwise.d_count_abnormal_by_baseline labels.g_km and added dynamic scaling of the surv_med and coxph annotation tables, with customization via the width_annots argument.split_text_grob preventing titles and footnotes from being properly formatted and printed by decorate_grob.g_lineplot preventing the addition of lines to the plot when midpoint statistic calculations result in NA value(s).tern:::tidy.glm formals to respect broom:::tidy.default formals.README to include installation instructions for CRAN.has_count_in_cols, has_counts_difference, combine_counts, h_tab_rsp_one_biomarker, arrange_grobs, a_count_patients_sum_exposure, a_coxreg, groups_list_to_df, forest_viewport.README to include installation instructions for CRAN.indent_mod argument and replaced it with the .indent_mods argument in summarize_num_patients and analyze_num_patients.s_coxreg and summarize_coxregto work with new analysis function a_coxreg.section_div and na_level arguments to summarize_vars.median_range as a numeric variable statistic option for summarize_vars.d_onco_rsp_label.g_km function.a_count_patients_sum_exposure for summarize_patients_exposure_in_cols and new analyze function analyze_patients_exposure_in_cols.s_proportion_diff.s_summary and s_compare to allow NA values in input variables. For factor variables with NAs, if na.rm = FALSE an explicit NA level will be automatically added. na.rm = TRUE will also consider "<Missing>" values and exclude them.na_level parameter in s_summary and s_compare to align with other tern functions. Instead of being a string to consider as NA when setting na.rm = TRUE, it now defines a string to print in place of NA values in the output table.TRTEDTM in tern datasets.na_level argument in summarize_vars preventing it from having an effect.lubridate package for date variables in tern datasets..gitignore and .Rbuildignore files.footnotes functions and all related files.pairwise function.count_patients_with_flags functions from count_patients_with_event.R to count_patients_with_flags.R.summarize_glm_count function to analyze count data using a linear model.g_step.format_fraction_fixed_dp and format_count_fraction_fixed_dp with fixed single decimal place in percentages.na_level and labelstr arguments to summarize_vars_in_cols.analyze_num_patients to include summary at the beginning that does not repeat when paginating.h_row_first_values function as a more general helper function to retrieve first values from specific rows."(n)" suffix from unique_count labels for s_num_patients.g_km to annotate with statistics (annot_stats) and add corresponding vertical lines (annot_stats_lines).s_count_occurrences_by_grade.summarize_vars_in_cols to work with pagination machinery.conf_level argument to emmeans::contrast() in s_ancova.rtables_access.R caused by not checking for specific combinations (also the standard values that were never used) of column indices and names.count_abnormal_by_grade.add_rowcounts that caused all row count row values to count as zero.h_col_indices causing an error when pruning with combination columns.test_proportion_diff missing argument for var_labels.pkgdown reference..R files for logistic regression and cox regression helper functions.analyze_num_patients to generate an initial summary so there is no repetition when paginating.testthat 3rd edition and replaced applicable tests with snapshot testing.summarize_ancova examples to use iris dataset instead of scda data.data/ folder and generated cached synthetic datasets.data/ folder instead of scda datasets.tern. These tests are in internal repo scda.test.summarize_vars_in_cols to analyze_vars_in_cols to reflect the appropriate analyze logic.summary_in_cols helper functions.format_xx.ggplot2 functions/arguments to fix warnings.forcats::fct_explicit_na with forcats::fct_na_value_to_level.wrap_text function and related files.footnotes functions.estimate_proportion and estimate_proportion_diff with relative tests.stat_mean_pval, a new summary statistic to calculate the p-value of the mean.mean_se (mean with standard error) for summarize_variables and related functions.Rdpack for references.DescTools::BinomDiffCI function within tern.summarize_logistic to specify which pivoted value to use during analysis.s_coxph_pairwise to generate log-rank p-value using original log-rank test instead of Cox Proportional-Hazards Model.nestcolor in all examples by adapting g_km, g_ipp, g_waterfall, g_step, g_lineplot, and g_forest.interaction_y and interaction_item in ANCOVA to make the interaction calculations available.footnotes to add footnotes to g_km.assertthat to checkmatecheckmate::assert_vector, checkmate::assert_set_equal, and checkmate::assert_int to check vector type, length, and values.checkmate the following functions: all_elements_in_ref, is_df_with_nlevels_factor, is_df_with_no_na_level, is_proportion_vector, is_quantiles_vector, is_character_or_factor, is_nonnegative_count, is_valid_character, assert_character_or_factor, assert_equal_length and has_tabletree_colnames.is_proportion, is_equal_length, is_df_with_no_na_level, is_df_with_nlevels_factor, is_variables, is_df_with_variables, is_df_with_factors, is_valid_factor to use assertion logic.as_factor_keep_attributes.assert_df_with_factors and assert_proportion_value internal functions.assertthat.R and test-assertthat.R to utils_checkmate.R and test-utils_checkmate.R.count_abnormal_by_marked (reference to abnormal_by_marked), count_abnormal_lab_worsen_by_baseline and h_adlb_worsen (reference to abnormal_by_worst_grade_worsen_from_baseline), count_abnormal_by_worst_grade (reference to abnormal_by_worst_grade), to_string_matrix, tidy.summary.coxph, tidy.step, surv_timepoint, (reference to survival_timepoint), surv_time (reference to survival_time), coxph_pairwise (reference to survival_coxph_pairwise), extract_survival_subgroups and tabulate_survival_subgroups (reference to survival_duration_subgroups), extract_survival_biomarkers and tabulate_survival_biomarkers (reference to survival_biomarkers_subgroups), control_summarize_vars, s_summary and a_summary (reference to summarize_variables) and kept the S3 method tree.summarize_patients_exposure_in_cols, summarize_num_patients with s_num_patients, s_num_patients_content, summarize_num_patients.count_cumulative, count_missed_doses, count_patients_events_in_cols, summarize_colvars, summarize_change, summarize_ancova,as.rtable, color_palette, add_footnotes.control_coxreg, control_coxph, control_incidence_rate, control_lineplot_vars, control_surv_time, control_surv_timepoint, control_logisitic, control_step.stat_mean_ci, stat_median_ci, split_cols_by_groups, explicit_na, sas_na, extract_rsp_subgroups, tabulate_rsp_subgroups, extract_rsp_biomarkers, tabulate_rsp_biomarkers, keep_rows, keep_content_rows, has_count_in_any_col, has_fraction_in_cols, has_fraction_in_any_col, has_fractions_difference, test_proportion_diff, pairwise, logistic_regression, estimate_incidence_rate, control_incidence_rate (reference to incidence_rate), cut_quantile_bins, estimate_multinomial_rsp, decorate_grob_set, extreme_format, fit_rsp_step, fit_survival_step, footnotes, footnotes-set, format_count_fraction, format_fraction_threshold, formatting_functions, format_fraction, combination_function (S4 method), compare_variables (S3 method), kaplan_meier._pkgdown.yml updated, and tern::: added for tests/examples/vignettes where present for the following functions:
abnormal_by_marked) s_count_abnormal_by_marked, a_count_abnormal_by_marked.abnormal_by_worst_grade_worsen_from_baseline) a_count_abnormal_lab_worsen_by_baseline, s_count_abnormal_lab_worsen_by_baseline.abnormal_by_worst_grade) s_count_abnormal_by_worst_grade, a_count_abnormal_by_worst_grade.survival_timepoint) s_surv_timepoint, s_surv_timepoint_diff, a_surv_timepoint, a_surv_timepoint_diff.survival_time) s_surv_time, a_surv_time.survival_coxph_pairwise) s_coxph_pairwise, a_coxph_pairwise.survival_duration_subgroups) a_survival_subgroups.count_cumulative) s_count_cumulative, a_count_cumulative.count_missed_doses) s_count_nonmissing, s_count_missed_doses, a_count_missed_doses.count_patients_events_in_cols) s_count_patients_and_multiple_events, summarize_patients_events_in_cols.incidence_rate) s_incidence_rate, a_incidence_rate.cox_regression_inter, decorate_grob_factory, draw_grob, estimate_coef.summary_labels, summary_formats, s_count_patients_sum_exposure, a_change_from_baseline s_change_from_baseline, a_ancova, s_ancova, arrange_grobs, as_factor_keep_attributes, combine_levels, split_text_grob, groups_list_to_df, s_cox_multivariate, is_leaf_table, a_response_subgroups, range_noinf, has_count_in_cols, has_counts_difference, prop_chisq, prop_cmh, prop_schouten, prop_fisher, s_test_proportion_diff, a_test_proportion_diff, fct_discard, fct_explicit_na_if.stats::ancova output due to version inconsistency.NA coming from rtables.formatters::var_labels.prop_diff functions to respect success responses (TRUE values).cut_quantile_bins.rtables split functions)s_ancova causing an error when the first level of the arm factor is not the control arm.s_abnormal_by_worst_grade when there is one PARAM level.prop_diff_wald when selecting all responders, updated tests accordingly.h_ancova that caused an error when deselecting all covariates.g_mmrm.tern:::) and added dontrun to internal function examples.color_palette and h_set_nest_theme in favor of nestcolor::color_palette and nestcolor::theme_nest, respectively.color_palette, color_palette_core, h_set_nest_theme, s_cox_univariate.fit_mmrm, g_mmrm_diagnostic, g_mmrm_lsmeans, as.rtable.mmrm, h_mmrm_fixed, h_mmrm_cov, h_mmrm_diagnostic, tidy.mmrm, s_mmrm_lsmeans, s_mmrm_lsmeans_single, summarize_lsmeans.arm to study_arm and extract to extract_by_name.rtables.R to utils_rtables.R.cox_regression_inter into a separate file from cox_regression.estimate_incidence_rate.R to incidence_rate.R to match the documentation grouping name.control_incidence_rate into a separate file because it produces a separate documentation file.@md and removed @order from incidence_rate.R. Modified examples accordingly.prop_schouten function documentation.draw_grob function.h_split_by_subgroups documentation warning fix for wrong placing of example block@description instead of every @descriptionIn function. Corrected accordingly summarize_variables_in_colsg_lineplot, g_step, g_waterfall, cox_regression, score_occurrences, add_rowcounts, odds_ratio, count_occurrences, count_occurrences_by_grade, explicit_na, df_explicit_na, count_patients_with_event, decorate_grob, combine_groups, append_varlabels, univariate, stack_grobs, count_abnormal (reference to abnormal), count_abnormal_by_baseline (reference to abnormal_by_baseline)._pkgdown.yml polished and tern::: for tests, examples, and vignettes when present for the following functions:
h_format_row, h_map_for_count_abnormalmake_names, month2day, day2month empty_vector_if_na, aesi_label, n_available, format_xx, arm.count_values_funs, prop_difference, combine_counts.s_count_abnormal, a_count_abnormal.s_count_abnormal_by_baseline, a_count_abnormal_by_baseline, d_count_abnormal_by_baseline.s_cox_univariate function has now deprecated badge.g_lineplot with table to automatically scale the table height and return a ggplot object.g_ipp with caption argument and adjust the position.prop_diff, tern function and related functions to be able to apply a continuity correction in the Newcombe method.summarize_numeric_in_columns and summarize_variables to allow factor/character summary and to be able to summarize the number of BLQs in AVALC from ADPC dataset.sum option to summarize_variables.stream by default).h_pkparam_sort function with argument key_var to allow data with different column names.test-table_aet02.R variant 12.scda data version to ‘2022-02-28’.pkgdown site.grDevices, stringr, and viridisLite.summarize_numeric_in_columns to summarize_variables_in_columns.summarize_vars_numeric_in_cols to summarize_vars_in_cols.g_lineplot plot were not connected when missing values.tern.mmrm.h_pkparam_sort to order PK PARAM value based on the order of the dataset generated by d_pkparam().d_pkparam to generate PK parameter map for sorting.nudge_y argument of h_g_ipp to be dependent on the data, fixing an issue whereby the baseline labels were offset incorrectly.stat_mean_ci and s_summary.numeric to calculate the geometric mean with its confidence intervals.rtables package refactor.with_label, var_labels, and var_labels<- to resolve conflict with the formatters package, a new dependency.tern” and “tern tabulation” vignettes.h_map_for_count_abnormal to create the map used in trim_levels_to_map split function by calling this helper function. It supports two methods: one with all observed mapping, one with at least low limit above zero and at least one non missing high limit.s_summary_numeric_in_cols and summarize_vars_numeric_in_cols functions to generate summary statistics in columns, mainly used for PK datasets.s_summary.numeric to use in s_summary_numeric_in_cols.tabulate_survival_subgroups and tabulate_rsp_subgroups (Survival Duration and Best Response analyses) to calculate N-s based on the records considered to create the model.estimate_proportion and related functions to be able to apply a continuity correction in the Wilson method.count_abnormal_by_marked and related statistics and formatting functions to use a more efficient layout with .spl_context argument used for determining denominators and with trim_levels_to_map split function under split_rows_by to show the desired levels in the table. This is a breaking change.count_abnormal_by_worst_grade and related statistics and formatting functions to use a more efficient layout with .spl_context argument used for determining denominators and with trim_levels_to_map split function under split_rows_by to show the desired levels in the table. This is a breaking change.count_abnormal function and related statistics and formatting functions to use a more efficient layout with trim_levels_to_map split function under split_rows_by to show the desired levels in the table. Also updated abnormal argument to be able to consider more than one level for each direction. This is a breaking change.estimate_incidence_rate and related functions to consider the week as time unit for data input.assertthat functions that output wrong data frame names and limited length of failure message outputs.utils.nest by using the checkmate and purrr packages for validation and moved get_free_cores and skip_if_too_deep functions from utils.nest into tern.survival_biomarkers_subgroups and response_biomarkers_subgroups.g_lineplot plot function, including new h_format_row helper function and control_lineplot_vars function. Removed g_summary_by.h_stack_by_baskets to stack events in SMQ and/or CQ basket flag in ADAE data set.s_summary.numeric. Added names attribute to each element of the final list returned by the s_summary.numeric function. Added summary_formats and summary_labels helper functions.df_explicit_na.h_append_grade_groups to improve its flexibility, robustness and clearness, and to make sure the result is ordering according to the order of grade_groups. Also, added remove_single argument which controls whether the elements of one-element grade groups are in the output or removed.var_labels and show_labels arguments to count_occurrences and count_patients_with_flags to allow for creation of a title row.na_level argument to count_abnormal_by_baseline.h_append_grade_groups to no longer fill-in empty grade groups with zeros.prop_diff_cmh to handle edge case of no FALSE (or TRUE) responses.g_mmrm_diagnostic to improve error handling when data is not amenable to the Locally Weighted Scatterplot Smoothing.g_km:
arm variable includes a single level and annot_coxph = TRUE.day2month and month2day to work with NA data.stat_mean_ci and stat_median_ci so that they may return different outputs.h_row_counts to handle analysis rows with NULL cells.LICENCE and README with new package references.error_on_lint: TRUE to .lintr.count_abnormal_by_marked tabulates marked laboratory abnormalities.summarize_patients_exposure_in_cols tabulates patient counts and sum of exposure across all patients.arm variable.cox_regression to work without covariates. Also in case of interaction model summary, p-values for main effect coefficients are no longer displayed.summarize_vars now include quantiles. summarize_vars now accepts the control function control_summarize_vars to specify details about confidence level for mean and median and quantile details. The control argument replaces conf_level.var_labels and show_labels arguments to count_occurrences_by_grade.indent argument in append_varlabels to accept non-negative integer to represent the indent space defined by user. Previous calls with Boolean indent will do an integer conversion and produce a warning.tabulate_survival_subgroups and related survival forest plot functions to use total number of events, instead of observations, as default for scaling the symbol sizes in the plot. (The user might still use total number of observations manually if they wish to do so.)h_adsl_adlb_merge_using_worst_flag will now impute BTOXGR for missing visits.count_abnormal_by_worst_grade_by_baseline and its related statistic and analysis functions as a simpler design will create lab abnormality tables.scda instead of random.cdisc.data package.fit_rsp_step and fit_survival_step, the corresponding tidy method tidy.step as well as the graph function g_step.compare_vars which compares variables of different types between columns and produces a p-value for the comparison to the reference column. Function built on top of the summarize_vars functionality.cut_quantile_bins cuts a numeric vector into quantile bins.fct_collapse_only collapses levels of a factor and keeps those in the order provided.fct_explicit_na_if inserts explicit missings in a factor based on a condition.range_noinf is a kind of a wrapper function of base::range. It returns c(NA, NA) instead of c(-Inf, Inf) for zero-length data.fit_coxreg_univar and fit_coxreg_multivar is now also possible without treatment arm. In the univariate case this means that it fits separate univariate models for the provided covariates and tabulation of corresponding effect estimates can later occur.fraction in result returned by s_count_occurrences. It contains a list of numerators and denominators with one element per occurrence.sum_num_patients and count_occurrences for the result unique and count_fraction to return (0, 0) when input is empty.groups_lists to extract_survival_subgroups, extract_rsp_subgroups and associated helper functions which allows to group factor levels of subgroup variables into manually defined groups, enhancing the flexibility of the resulting forest graphs.g_forest now extracts default arguments from attributes of the input table produced by tabulate_rsp_subgroups and tabulate_survival_subgroups so that the user does not have to do this manually anymore.g_km:
s_surv_time function to use a newly created function range_noinf instead of base::range.no_fillin_visits added to h_adsl_adlb_merge_using_worst_flag to specify excluded visits from the post-baseline worst toxicity grade output. Improved h_adsl_adlb_merge_using_worst_flag to include variables shared between adsl and adlb, along with PARAM, PARAMCD, ATOXGR, BTOXGR and optionally AVISIT, AVISITN when by_visit = TRUE. Prior output contained USUBJID, ARMCD, PARAMCD, ATOXGR, and BTOXGR.s_surv_timepoint for cases when there are zero patients at risk.stat_median_ci function so that when passing empty var with empty name, no row names contain missing values error would show.s_cox_univariate function, use fit_coxreg_univar function instead.hr and hr_ci in a_coxph_pairwise and median in s_surv_time to align with STREAM.test-table_ttet01.R and test-table_dort01.R to make sure the analysis variable EVNT1 has both levels of the factor defined.position_surv_med added to g_km to move position of the annotation table with median survival times.g_km related to the ignored arguments pch and size which were not passed on to helper function h_ggkm.xticks and max_time arguments in g_km for greater functionality. max_time added as an argument in h_xticks to allow this.prop_diff_cmh that led to NaN weighted proportion difference estimates and missing confidence intervals. Before this change, when including no patients from one treatment arm for at least one stratum the estimation did not lead to numeric results.prop_cmh giving an error in case of at least one stratum containing less than two observations.n_events added to estimate_incidence_rate.denom added to count_occurrences.yval and ci_ribbon added to g_km.g_ipp along with helpers h_g_ipp and h_set_nest_theme.count_patients_with_events, now shows zero counts without percentage.get_mmrm_lsmeans which did not allow MMRM analysis of more than 3000 observations.stat_mean_ci and stat_median_ci to handle edge cases with number of elements in input series equal to 1. For such cases, NA_real_ is now returned, instead of NA or +/-Inf for confidence interval (CI) estimates.n_lim argument of stat_mean_ci to n_min to better reflect its desired meaning.This version of tern introduces a major rewriting of tern due to the change to layout based tabulation in rtables. tern now does not build tables directly anymore, instead it provides analysis functions to build tables, see the examples. * Counting patients with abnormal values post-baseline with count_abnormal. * Counting patients with graded abnormal values with count_abnormal_by_worst_grade. * Counting patients with abnormal values by baseline status with count_abnormal_by_baseline. * Counting patients with missed doses with s_count_missed_doses and count_missed_doses. * Counting patients with event flags with count_patients_with_event and count_patients_with_flags. * Summarizing variables with summarize_vars (supports numeric, factor, character and logical variables). Note that factors need to have NAs converted to na_level before use. * Summarizing change from baseline with summarize_change. * Summarizing variables in columns with summarize_colvars. * Estimating difference for responder proportions with estimate_proportion_diff. * Estimating difference for Odds Ratio with estimate_odds_ratio. * Testing the difference in responder proportions with test_proportion_diff. * Estimating the responder proportion for the level of a factor with estimate_multinomial_response. * Fitting and tabulating the results of Cox regressions with fit_coxreg_univar, fit_coxreg_multivar and summarize_coxreg, respectively. * Pruning occurrence tables (or tables with counts and fractions) with flexible rules, see ?prune_occurrences for details. * Sorting occurrence tables using different options, see ?score_occurrences for details. * Fitting and tabulating MMRM models with fit_mmrm and as.rtable and summarize_lsmeans, see ?tabulate_mmrm for details. * Counting the number of unique and non-unique patients with summarize_num_patients. * Counting occurrences with count_occurrences. * Counting occurrences by grade with summarize_occurrences_by_grade and count_occurrences_by_grade. * Counting patients and events in columns with summarize_patients_events_in_cols. * Tabulating the binary outcome response by subgroup with extract_rsp_subgroups and tabulate_rsp_subgroups. * Tabulating the survival duration by subgroup with extract_survival_subgroups and tabulate_survival_subgroups.
a_mean_sd, a_median, a_n_true_and_freq, a_count, a_q1q3, a_iqr, a_range.s_test_proportion_diff: Chi-Squared Test with Schouten Correction.t_contingency for contingency tables.splitText to dynamicSplitText to resolve the name conflict with the package ggpubr.rreplace_format for tabulation post-processing.t_ancova to create ANCOVA tables, as well as corresponding elementary table function t_el_ancova and summary function s_ancova.s_odds_ratio to estimate Odds Ratio of response between categories, as well as the corresponding elementary table function t_el_odds_ratio.agresti-coull, jeffreys) for s_proportion.anderson-hauck and newcombe to s_proportion_diff.s_test_proportion_diff.t_binary_outcome takes now lists (instead of character vectors) specified by the helper function control_binary_comparison as the arguments strat_analysis and unstrat_analysis. Odds Ratio estimates and CIs are now removable and included by default, similarly to the other subsections of the arm comparison analyses. Also added argument rsp_multinomial.t_el_multinomial_proportion.t_abn_shift.s_mmrm, as well as corresponding table functions t_mmrm_lsmeans, t_mmrm_cov, t_mmrm_diagnostic, t_mmrm_fixed, and plot functions g_mmrm_lsmeans, g_mmrm_diagnostic. The results of these match SAS results (up to numeric precision).a_mmrm and t_mmrm (they give a deprecation warning but still work) to remove in the next release. The reason is that the results of these functions don’t match SAS results.g_km related to numbers in patients at risk table to correct numbers for integer time-to-event variable inputs.row_by argument, inputs no longer require use of nested_by.stat_mean_ci and stat_median_ci for error bars in ggplot2.t_coxreg as single interface for diverse cox regression types.t_binary_endpoint and elementary functions: t_el_proportion, t_el_proportion_diff and t_el_test_proportion_diff. The supporting summary functions added are: s_proportion, s_adj_proportion_diff, s_proportion_diff and s_test_proportion_diff.t_events_patyear to create event table adjusted person-years.t_abnormality and the elementary table function t_el_abnormality.grade_levels argument from t_events_term_grade_id functions. Post-processing by reordering the leaves of the table tree creates a different ordering of rows if required. Creating a helper function will occur at a later time.prune_zero_rows argument to t_events_per_term_grade_id and t_max_grade_per_id to not show rows of all zeros as they can clutter the visualization in the Shiny app and make it slower.t_summary_by output when summarizing numeric columns in parallel with compare_in_header.t_coxph to t_coxph_pairwise to reflect the model process, add details in documentation.test.nest dependency.test.nest dependency.N in t_summary.t_logistic for multi-variable logistic regression table.df_explicit_na to replace NA by explicit values.t_tte to specify confidence level independent for survfit, coxph, and ztest, see the manual.t_rsp of not showing p-value, odds ratio and CIs when strata_data is not NULL.t_forest_rsp and t_forest_tte, with footnotes in g_forest.footnotes, footnotes<- and add_footnotes<- functions to deal with footnotes.conf_int for confidence interval level to t_el_forest_rps, t_forest_rsp, t_el_forest_tte, t_forest_tte.col_symbol_size to g_forest to control the relative size of symbols used in the plot.s_coxph_pairwise function to perform pairwise testing, used by t_tte and t_coxph.t_count_true replacing t_summary_true.t_count_unique to create analysis subsets, added t_el_count_unique for vectors.t_events_term_id so that table sort order is by decreasing frequency instead of alphabetical.color_palette and a new nest color palette.utils.nest.event_type argument to t_events_per_term_grade_id.t_summary_by.node S4 class to create trees:
rtables.keys and keys<- functions.tabulate_pairwise.get_N, col_N_add_total, check_id.na_as_level.as_factor_keep_attributes.r_by.t_el_disposition.t_el_forest_tte, t_el_forest_rsp.table_tree argument which returns a node object.t_summary.numeric:
f_numeric to choose which statistics to calculate.t_summary.factor:
denominator now also allows for omit if wanting to omit percentages.t_summary_by:
by to row_by.t_forest_rsp, t_forest_tte:
group_data using row_by_list.na_omit_group.t_count_unique:
indent argument, use the indent function in rtables. insteadrandom.cdisc.data to speed up testing.t_summary.Date method.save_join.test.nest tests:
width_row.names argument of g_forest function into width_row_names.censor.show argument of g_km function into censor_show.col.legend.title argument of g_waterfall function into col_legend_title.na.rm argument of t_count_unique function into na_rm.row.name argument of t_count_unique function into row_name.na.omit.group argument of t_forest_rsp function into na_omit_group.na.omit.group argument of t_forest_tte function into na_omit_group.row.name.TRUE and row.name.FALSE arguments of t_summary.logical into row_name_true and row_name_false respectively.splotTextGrob into split_text_grob.addTable, t_summarize_by_visit, t_summarize_variables.t_summary_by function.g_km function, renamed kmGrob into kmCurveGrob.t_events_* family of functions.t_summary and methods for data.frame, numeric, logical, character, factor, and Date objects.t_events_per_term_id, t_events_per_term_grade_id: Adverse Events & Concomitant Treatment Tables.t_max_grade_per_id, t_count_unique, t_events_summary elementary tables used for the Adverse Events & Concomitant Treatment Tables.g_waterfall: Horizontal Waterfall Plot.decorate_grob, decorate_grob_set, decorate_grob_factory, splitTextGrob.stack_grobs, arrange_grobs, draw_grob.t_tte now shows two rows with ranges for event and censored times, respectively.g_km works with one arm survfit objects.t_summarise_variables uses now n instead of N as a denominator for calculating percentages for factors by default.t_rsp now works when all response values are TRUE or FALSE.t_summarize_variables as t_summary is more powerful.t_summarize_by_visit with t_summary_by will occur in an upcoming release.