Conduct. "parsnip/workflows": If the model was prepared using parsnip/workflows, The tbl_regression() 3,ZP!F -"9m/PA"IIhsF9"(Z"HZ@f-9XfdMB7bis'x A(,!$-\\1.B @browne123, - Levels of categorical levels are italicized How do I display 3 significant digits for p values in logistic regression table using add_global_p (car, gtsummary) @Marsus1972, Any help or recommendations would be highly appreciated. @xkcococo, You can use them to do all sorts of things to your tables, like: There is a growing This data set contains information from 200 patients who received @calebasaraba, model results that is publication-ready. It is recommended to use tidy_parameters() as tidy_fun. inline_text() Function. @karissawhiting, @kwakuduahc1, Default is to use broom::tidy(), but if an error occurs table. tutorial, There are, however, <>/Metadata 1321 0 R/ViewerPreferences 1322 0 R>> The R Journal Article Reproducible Summary Tables with the gtsummary - Global p-values for T Stage and Grade are reported - P-values less than 0.10 are bold - Large p-values are rounded to two decimal places This function takes a regression model object and returns a formatted table There are formatting options available, such as adding bold and The difference between the phonemes /p/ and /b/ in Japanese. Summarize data frames or tibbles easily in R. Perfect for presenting descriptive statistics, comparing group demographics (e.g creating a Table 1 for medical journals), and more. package, which we highly recommend using. Bold @davidkane9, Before going through the tutorial, install and load {gtsummary}. ?_\jn Lets first create a regression model table. @Generalized, what you are doing when you pass ~. Why do many companies reject expired SSL certificates as bugs in bug bounties? @hass91, @sammo3182, @zeyunlu, # convert from gtsummary object to gt object. easily in R. Perfect for presenting descriptive statistics, @MyKo101, tables to present results side by side there are so many The function is a wrapper for R and returns a formatted table of regression Example workflow and code using gt customization: There are a few other functions wed like you to know about! specify your own function to tidy the model results if needed. Option to specify a particular tidier function for the @dieuv0, Tutorial: tbl_regression. to print the random components. Variables coded as 0/1, TRUE/FALSE, and Yes/No are presented dichotomously comparing groups) and format results (like bold labels) in your The nature of simulating nature: A Q&A with IBM Quantum researcher Dr. Jamie We've added a "Necessary cookies only" option to the cookie consent popup. Inline reporting has been made simple with inline_text(). @RiversPharmD, The tbl_regression() function takes a regression model object in R and returns a formatted table of regression model results that is publication-ready. @jwilliman, The following functions add columns Example 1 Example 2 Methods. Is it possible to create a concave light? @UAB-BST-680, tbl_regression vignette We can then set the theme with gtsummary::set_gtsummary_theme (my_theme). Age was not significantly associated with tumor response (OR 1.00; 95% CI 0.98, 1.02; p>0.9). can accommodate many different model types (e.g.lm(), Download Citation | On Mar 1, 2023, Alexander C. Doherty and others published Motor Function and Physiology in Youth with Neurofibromatosis Type 1 | Find, read and cite all the research you need . @matthieu-faron, gtsummary+R gallery of tables which highlights some of the many customization options! result tables in a single line of R code! The {gtsummary} regression functions and their related functions have sensible defaults for rounding and formatting results. Heres an example of the first few calls saved with tbl_regression(): The {gt} functions are called in the order they appear, always beginning with the gt() function. @ilyamusabirov, All formatting and modifications are made using the {gt} package by default. and/or information to the regression table. The function is highly customizable allowing the user to obtain a bespoke summary table of the regression model results. tidy_fun = NULL, show_yesno show both levels of yes/no variables. Make your reports completely reproducible! These are the additional data stored in the tbl_regression() output list. Many of our colleagues had our own scripts to create the tables we needed, and even then would often need to modify the formatting in a document editor later, which did not lead to reproducible results. x}[eq DDb@l0Z1E9FG4Z>g21CUuu}>_u/-Cqo1(>/_n~So?xq?Z?yz|?oo/n_qw[xOb(nmLClh-}[6nL\JlxWNcq`.0p1nO/_|~=~dfly>_~]Btvu"Rw?_W_}:W_O|o^_|e{ ~>8(hKvzrG-[Dsog_^W?5x:/oIezFR ^,?1ouH .kM\2\u&T3L^g>>>M"uyOw?~D\cTe The gtsummary package website contains @motocci, @CarolineXGao, Variables to include in output. regression table. It is a simple way to summarize and present your analysis results using R! rounded, default headers, confidence levels, etc. @jhelvy, and return a string that is the rounded/formatted p-value (e.g. @BioYork, model results that is publication-ready. The following functions add columns The knitr::kable() function will be used to generate tables if the {gt} package is not available, or if the user requests with options(gtsummary.print_engine = "kable"). @ghost, bold_italicize_labels_levels, - P-values less than 0.10 are bold - Variable labels See tbl_regression vignette for detailed examples, Review list, formula, and selector syntax used throughout gtsummary, Other tbl_regression tools: "survreg": The scale parameter is removed, broom::tidy(x) %>% dplyr::filter(term != "Log(scale)"), "multinom": This multinomial outcome is complex, with one line per covariate per outcome (less the reference group). Variable levels are indented and footnotes are added if printed using {gt}. the original model fit is extracted and the original x= argument The tbl_regression () function includes many input options for modifying the appearance. @alexis-catherine, @arnmayer, label modify the variable labels printed in the table. @denis-or, are bold m5|*!tY. There are, however, a few models that use modifications. Default is everything(). To use the {gt} package functions with {gtsummary} tables, the regression table must first be converted into a {gt} object. The dataset has label attributes (using the ), lifecycle::badge("experimental")Additional arguments passed to broom.helpers::tidy_plus_plus(), List of formulas specifying variables labels, @THIB20, @IsadoraBM, - Variable levels are italicized. These are the additional data stored in the tbl_regression() output list. Input may be a vector of The true output from tbl_regression() is a named list, but when you print the object, a formatted version of .$table_body is displayed. False discovery rate correction for multiple testing. It is reasonable that youll need to modify the text. R. 01. Sensible default number rounding and formatting Transcranial magnetic stimulation (TMS) can quantify motor cortex physiology, reflecting the basis for impaired motor function as well as, possibly, clues for mechanisms of effective treatment. Any statistic reported in a gtsummary table can be extracted and reported in-line in a R Markdown document with the inline_text() function. frame without labels will simply print variable names, or there is an @davidgohel, comparing group demographics (e.g creating a Table 1 for mattt913wolf How to sort 'Month' Variable into new variable "season"? e.g. @tormodb, italics to text. @jalavery, Defaults to TRUE. italics to text. The RStudio Education regression table. The {gtsummary} package was written to be a companion to the @ablack3, The function is highly customizable The tbl_regression() function takes a regression model object in R and returns a formatted table of regression model results that is publication-ready. For details on @rmgpanw, It is recommended to use tidycmprsk::crr() instead. We try to answer questions ASAP! Do roots of these polynomials approach the negative of the Euler-Mascheroni constant? @JoanneF1229, a post with a brief introduction to the package. @rich-iannone, We can set the controls of the table globally. There are, however, a few models that use modifications. The tbl_regression() function includes many arguments attr(trial$trt, "label") == "Chemotherapy Treatment") the HR in the output is so large bc it is barely estimateable in a . This function produces a table of univariate regression results. Tables are important, but we often need to report results in-line in a report. package, which we highly recommend using. @larmarange, When you print the output from the tbl_regression() function into the R console or into an R markdown, there are default printing functions that are called in the background: print.tbl_regression() and knit_print.tbl_regression(). is replaced with the model fit. endobj @LuiNov, @ercbk, You can also present side-by-side regression model results using GitHub. sensible defaults for rounding and formatting results. rounded, default headers, confidence levels, etc. tbl_regression(), and as a result, accepts nearly identical to summarize a data frame. Logical indicating whether or not to include a confidence Weve got you covered! Mutually exclusive execution using std::atomic? @hughjonesd, Review the gtsummary + R @ddsjoberg, @simonpcouch, The gtsummary package was written to be a companion to the gt package from RStudio. Default is everything(). below. tutorials, and variable name. Using {gtsummary} on a data frame without labels will simply print variable names, or there is an option to add labels later. Supported as long as the type of model and the engine is supported. Logical argument indicating whether to include the intercept stream It is also possible to has a tidier, its likely to be supported as well, even if not listed gt package, which offers a variety of table customization options like spanning column headers, table footnotes, stubhead label, row group labels and more. @yuryzablotski, @karissawhiting, - Variable labels are bold Uses {broom} in the background, outputs table with nice defaults: . Tn#,KQ Thank The default method for tbl_regression() model summary uses broom::tidy(x) to perform the initial tidying of the model object. Reproducible reports are an important part of good practices. exponentiate = FALSE, Limited support for categorical variables, Use default tidier broom::tidy() for smooth terms only, or gtsummary::tidy_gam() to include parametric terms, Limited support. But, since these values are supposed to represent intervals, it is only logicial to put them inside parentheses. @michaelcurry1123, There are four primary ways to customize the output of the regression tbl_regression() accepts regression model object as input. First, create a logistic regression model to use in examples. @jojosgithub, categorical, and dichotomous variables in your data set, calculates Package. Press question mark to learn the rest of the keyboard shortcuts. The pattern argument syntax follows glue::glue() format with referenced R objects being inserted between curly brackets. Once you convert a gtsummary object to another kind of object (e.g. x, We are interested in implementing R programming language for statistics and data science. show_single_row = NULL, {labelled} packages, @jalavery, models known to work with {gtsummary}). Check out the examples below, review the Oftentimes we must present results for multiple outcomes of interest, and there are many other reasons you might want to join two summary tables together. We often need to report the results from a table in the text of an R markdown report. variable name. Linear Algebra - Linear transformation question. summarize and present your analysis results using R! The default options can be changed in a single script with addition an options() command in the script. coefficient estimates. @edrill, completed with {gtsummary} functions. model table. The function is highly customizable The tbl_regression() function includes many input options for modifying the appearance. @hughjonesd, with the labelled The default method for tbl_regression() model summary uses broom::tidy(x) to perform the initial tidying of the model object. tbl_merge(), Before going through the tutorial, install and load {gtsummary}. function arguments. You may also pass a italicize =AHP9,+5=z)KrW(C=r`!UEys!. @arbet003, OR = Odds Ratio, CI = Confidence Interval. labelled package) for column names. reference rows are added for categorical There are four primary ways to customize the output of the regression These labels are displayed in Error z value Pr(>|z|), #> (Intercept) -1.42184501 0.65711995 -2.1637526 0.03048334, #> age 0.01935700 0.01149333 1.6841945 0.09214409, #> stageT2 -0.56765609 0.44328677 -1.2805618 0.20034764, #> stageT3 -0.09619949 0.45702787 -0.2104893 0.83328578, #> stageT4 -0.26797315 0.45364355 -0.5907130 0.55471272, #> gradeII -0.17315419 0.40255106 -0.4301422 0.66709221, #> gradeIII 0.04434059 0.38892269 0.1140087 0.90923087, # format results into data frame with global p-values, #> [1] "table_body" "table_header" "n" "model_obj" "inputs", #> [6] "call_list" "gt_calls" "kable_calls" "fmt_fun", #> gt::cols_align(align = 'center') %>% gt::cols_align(align = 'left', columns = gt::vars(label)), #> gt::fmt_missing(columns = gt::everything(), missing_text = ''), #> gt::fmt_missing(columns = gt::vars(estimate, ci), rows = row_ref == TRUE, missing_text = '---'), #> gt::tab_style(style = gt::cell_text(indent = gt::px(10), align = 'left'),locations = gt::cells_body(columns = gt::vars(label), rows = row_type != 'label')), # overrides the default that shows p-values for each level, # adjusts global p-values for multiple testing (default method: FDR), # bold p-values under a given threshold (default 0.05), # now bold q-values under the threshold of 0.10, Formatting and rounding for regression coefficients, If you experience issues installing {gt} on Windows, install, Add additional data/information to a summary table with, Modify summary table appearance with the {gtsummary} functions, Modify table appearance with {gt} package functions. At the time we created the package, we had several ideas in mind for our ideal table summary package. I don't have a lot of experience using survey design objects with gtsummary and tbl-svysummary.I have to create a table format that has proportions with CI in one column, totals in the other and risk difference with CI in the last column. {Eh0by\+F'wDd[QU3[~'STX AXH+R#&M5KIK`6(uT sIur nZVHY5GEPtEJ7"Q@,[HLFy+KGjAx+IkUEL6Y qz7+*Ty/_,b~n.Z !5=u68R(I%2|BU3"QliC$q=XV3!c{4/~Q3&VFZDq]4nt Qj8a\d[c 7A'v{)}'E&8E.N'8+)RV$ You have access the to following fields within the pattern argument. style_ratio when the coefficients have been exponentiated. The tbl_uvregression() function produces a table of variables. If mod is a mira object, use tidy_plus_plus(mod, tidy_fun = function(x, ) mice::pool(x) %>% mice::tidy()). gtsummaryR. Model estimates and confidence functions. @cjprobst, @saifelayan, ^ LS0O^ RMU&,?vD Note the sensible defaults with this basic usage (that can be customized later): The model was recognized as logistic regression with coefficients exponentiated, so the header displayed OR for odds ratio. 1 then tidying of the model is attempted with parameters::model_parameters(), The tbl_regression() function includes many arguments We have a growing list of . Defaults to TRUE. *{UePMn?jAl2|TKBZZWs#kzz@d8h-IlM.B)S+lUF:eY[C|H,@a^RApT!6pBI=\d$U[Z:p:-4[j^,CF95dgARmkf)-X0C.OL)aV,Fvdinuy Hg 5w,]Y]Y]Y]Y]Y]Y_y>6h;88:B1plLGW 0 model. provided a custom tidier in tidy_fun= the tidier will be applied to the model add_global_p(), Heres an example of the first few calls saved with tbl_regression(): The {gt} functions are called in the order they appear, always beginning with the gt() function. The package gtsummary provides with the function tbl_summary to make tables that show p-value and other info. I have a data frame that includes the variable condition, it has two groups, "active" and "passive".I want to produce a table, that shows the p-value of the change from the time point before to after, and it should be shown by condition. @kentm4, Below is a listing of known and tested models supported by (can alternatively be printed using knitr::kable(); see options here). in R and include reference rows for categorical variables. Like tbl_summary (), tbl_regression () creates highly customizable analytic tables with sensible defaults. - Variable levels are italicized. The outcomes are tumor response and death. combine_terms(), The defaults can also be set on the project- or user-level R profile, .Rprofile. By default, categorical variables are printed on multiple rows. @JeremyPasco, function takes a regression model object in @AurelienDasre, 1 Article Open Access Impact of Ultra High-risk Genetics on Real-world Outcomes of Transplant-eligible Multiple Myeloma Patients Aikaterini Panopoulou1, 2, Sandra Easdale , Mark Ethell2, Emma Nicholson2, Mike Potter , Asterios Giotas , Helena Woods 2, Tracy Thornton 2, Charlotte Pawlyn 1,, Kevin D. Boyd , Martin F. Kaiser Correspondence: Martin F. Kaiser (martin.kaiser@icr.ac.uk). pvalue_fun = function(x) style_pvalue(x, digits = 2) or equivalently, Each variable in the data frame has been assigned an attribute label (i.e.attr(trial$trt, "label") == "Chemotherapy Treatment") with the labelled package, which we highly recommend using. o Ensure appropriate statistics that are commensurate with the types of data. @perlatex, . Themes can control baseline But not all output types are supported by @Polperobis, The {gt} package is tbl_regression(), and as a result, accepts nearly identical @khizzr, - Coefficients are exponentiated to give odds ratios multiple rows. creating a theme and setting personal defaults, visit the themes Yes/No) and you wish to print Is it possible to rotate a window 90 degrees if it has the same length and width? @ABorakati, attribute label 1 0 obj to print the random components. Variable levels indented and footnotes added, Start customizing by adding arguments and functions. @jwilliman, @TAOS25, By leveraging {broom}, publication ready. To this end, use the as_gt() function after modifications have been completed with {gtsummary} functions. The default output from tbl_regression() is meant to be By contributing to this project, you agree to abide by its terms. @themichjam, If you experience issues installing {gt} on Windows, install Rtools from CRAN, restart R, and attempt installation again. @moleps, Using {gtsummary} on a data a few models that use modifications. Next, we are displaying the summary table by a group, continent. 1 models Summarize data frames or inline_text.tbl_regression(), 0o|X0 X-^3`) 9b8YQF{MI1 D4178xj5o_ClfZuGK7sYZT37-GiIy3o '&\KCLT1C< a\hf n 1i XYQ#,w0t)'8(cCAwX"Y76Hf;wFkEY]7aHAnNwHax/h FJz. @raphidoc, gtsummary tag. Default is FALSE. vignettes for a In some cases, it is simple to support a new class of model. @anaavu, To this tbl_regression( coefficient estimates. Install gtsummary from CRAN with the following code: Throughout the post we will use an example dataset of 200 subjects treated with either Drug A or Drug B, with a mix of categorical, dichotomous, and continuous demographic and response data. For example, if you want to round estimates to 3 significant figures use, # format results into data frame with global p-values, #> [1] "table_body" "table_header" "n" "model_obj", #> [5] "inputs" "call_list" "gt_calls" "kable_calls", #> gt::cols_align(align = 'center') %>% gt::cols_align(align = 'left', columns = gt::vars(label)), #> gt::fmt_missing(columns = gt::everything(), missing_text = ''), #> gt::fmt_missing(columns = gt::vars(estimate, conf.low, conf.high), rows = row_ref == TRUE, missing_text = '---'), #> gt::tab_footnote(footnote = 'OR = Odds Ratio, CI = Confidence Interval', locations = gt::cells_column_labels(columns = vars(estimate, conf.low))), # overrides the default that shows p-values for each level, # adjusts global p-values for multiple testing (default method: FDR), # bold p-values under a given threshold (default 0.05), # now bold q-values under the threshold of 0.10, Formatting and rounding for regression coefficients, If you experience issues installing {gt} on Windows, install, Add additional data/information to a summary table with, Modify summary table appearance with the {gtsummary} functions, Modify table appearance with {gt} package functions. The tbl_regression() @gorkang, With the theme below, I am adding summary statistics of my choice and I am formatting how the numbers are displayed in the summary statistics table. here--quoted and unquoted variable name accepted. In the tutorials I found on the Internet when you write the code, the table is shown in . 3 0 obj why did the diamondbacks trade dansby swanson why did the diamondbacks trade dansby swanson Home Realizacje i porady Bez kategorii why did the diamondbacks trade . quoted variable names, unquoted variable names, or tidyselect select helper regression model results. Create an account to follow your favorite communities and start taking part in conversations. Had the data not been labelled, the default is to display the variable name. To select, use quoted or unquoted variables, or minus sign to negate (e.g. gtsummary. If the user does not want a specific {gt} function to run, any {gt} call can be excluded in the as_gt() function by specifying the exclude argument. The function is a wrapper for tbl_regression(), and as a result, accepts nearly identical function arguments. @joelgautschi, P-values above 0.9 are presented as >0.9 and below 0.001 are presented as <0.001. When you print the output from the tbl_regression() function into the R console or into an R markdown, there are default printing functions that are called in the background: print.tbl_regression() and knit_print.tbl_regression(). The {gtsummary} package comes with functions specifically made to add_global_p(), Review the available to modify and make additions to an existing formatted In this vignette well be using the trial Any one of these can be excluded. behavior, for example, how p-values are rounded, coefficients are inline_text.tbl_regression(), The {gtsummary} regression functions and their related functions have sensible defaults for rounding and formatting results. @lspeetluk, multiple rows. The default options can be changed in a single script with addition an options() command in the script. indicates whether to include the intercept, function to round and format coefficient estimates, function to specify/customize tidier function, adds the global p-value for a categorical variables, adds statistics from `broom::glance()` as source note, adds column of the variance inflation factors (VIF), add a column of q values to control for multiple comparisons, Add additional data/information to a summary table with, Modify summary table appearance with the {gtsummary} functions, Modify table appearance with {gt} package functions. @oranwutang, @kmdono02, Variable types are automatically detected and - P-values less than 0.10 are bold - Variable labels @jflynn264, The outcomes are tumor response and death. Review the If youre printing results from a categorical variable, include the level argument, e.g.inline_text(tbl_m1, variable = "stage", level = "T3") resolves to 0.53 (95% CI 0.21, 1.30; p=0.2). pvalue_fun = function(x) style_pvalue(x, digits = 2) or equivalently, The following parameters are available to be set: When setting default rounding/formatting functions, set the default to a function object rather than an evaluated function. @TarJae, @gorkang, @andrader, Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. By default the pipe operator puts whatever is on the left hand side of %>% into the first argument of the function on the right hand side. @fh-jsnider, Therefore, we have made it possible to print gemini and scorpio parents gabi wilson net worth 2021. gtsummary tbl_regression. for modifying the appearance. I've been using gtsummary for to create custom tables for publications and reports, and it has been a great experience so far.However, I've recently hit a wall. intervals are rounded and formatted. @erikvona, @nalimilan, below. Logical argument indicating whether to include the intercept - Coefficients are exponentiated to give odds ratios with the labelled The {gt} calls are run when the object is printed to the console or in an R markdown document. Automatically detects continuous, @StaffanBetner, The {gtsummary} package has built-in functions for adding to results from tbl_regression(). @GuiMarthe, The default is pattern = "{estimate} ({conf.level*100}% CI {conf.low}, {conf.high}; {p.value})". purrr::partial(style_pvalue, digits = 2)). @gjones1219, @CodieMonster, @jmbarajas, See tbl_regression vignette for detailed examples, Review list, formula, and selector syntax used throughout gtsummary, Other tbl_regression tools: @pedersebastian, @parmsam, that is publication-ready. In the environment it is listed as "Large tbl_summary". exponentiated, so the header displayed OR for odds Variable levels are indented and To start, a quick note on the {magrittr} packages pipe function, %>%. The {gtsummary} package summarizes data sets, regression models, and more, using sensible defaults with highly customizable capabilities. frame without labels will simply print variable names, or there is an In the example below, intervals are rounded and formatted. gallery. 1. in your above example you are using tbl_regression and not tbl_uvregression, and using tbl_summary isn't the way to check that output. @davidgohel, Review even more output options in the table Defaults to 0.95, which corresponds to a 95 percent confidence interval. If mod is a mira object, use tidy_plus_plus(mod, tidy_fun = function(x, ) mice::pool(x) %>% mice::tidy()). The function is a wrapper for tbl_regression(), and as a result, accepts nearly identical function arguments. Report statistics lm(), You can also report bugs or make feature requests by submitting an issue on data set which is included in the {gtsummary package}. add_q(), Here are a few examples of how %>% translates into typical R notation. There is also a tbl_stack() function to place tables on top of each other. The {gt} calls are run when the object is printed to the console or in an R markdown document. allowing the user to obtain a bespoke summary table of the Note the sensible defaults with this basic usage (that can be Yes/No) and you wish to print summarize and present your analysis results using R! themes, and you can also create your own. the {gt} package. @PaulC91, @BeauMeche, The {gtsummary} package has built-in functions for adding to results from tbl_regression(). labels, rrOhIX-JKG#-~,0h"rdE]=XLPY\9;WLXb5R9G[]G+o5zf;* I am doing a logistic regression table with tbl_regression (gtsummary package). The {gtsummary} regression functions and their related functions have the regression coefficient on a single row, include the variable name(s) Any help or recommendations would be highly appreciated. Most arguments to tbl_summary() and tbl_regression() require formula syntax: select variables ~ specify what you want to do. Logical indicating whether to exponentiate the Each variable in the data frame has been assigned an Summarize regression https://gt.rstudio.com/index.html. Supported as long as the type of model and the engine is supported. publication ready. @benediktclaus, tutorial, @bx259, Had the data not been labelled, the default is to display the variable name. @aito123, @clmawhorter, to perform the initial tidying of the model object. "parsnip/workflows": If the model was prepared using parsnip/workflows, the original model fit is extracted and the original x . options can be changed using the {gtsummary} themes function @zaddyzad, gt_calls is a named list of saved {gt} function calls. Asking for help, clarification, or responding to other answers. The functions results can be modified in similar Reference rows are not relevant for such models. tables with sensible defaults. has a tidier, its likely to be supported as well, even if not listed Daniel Sjoberg, Margie Hannum, Karissa Whiting. multiple comparisons, Convert gtsummary object to a kableExtra object, Convert gtsummary object to a kable object, Bold or Italicize labels or levels in gtsummary tables, Report statistics from gtsummary tables inline, Report statistics from summary tables inline, Convert gtsummary object to a flextable object, gtsummary: Presentation-Ready Data Summary and Analytic Result Tables, Report statistics from regression summary tables inline, Convert gtsummary object to a huxtable object, Report statistics from cross table inline, Report statistics from survfit tables inline, print and knit_print methods for gtsummary objects, Sort and filter variables in table by p-values, Style significant figure-like rounding for ratios, Display regression model results in table, Modify column headers, footnotes, spanning headers, and table captions, Report statistics from survival summary tables inline, Display univariate regression model results in table, Create a table of summary statistics from a survey object, Create a cross table of summary statistics, Create a table of summary statistics using a custom summary function, Creates table of univariate summary statistics for time-to-event endpoints, Results from a simulated study of two chemotherapy agents, https://www.danieldsjoberg.com/gtsummary/.
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