survout

NEWS code{white-space: pre-wrap;} span.smallcaps{font-variant: small-caps;} span.underline{text-decoration: underline;} div.column{display: inline-block; vertical-align: top; width: 50%;} div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;} ul.task-list{list-style: none;} survout 0.1.0 Added a NEWS.md file to track changes to the package.

README code{white-space: pre-wrap;} span.smallcaps{font-variant: small-caps;} span.underline{text-decoration: underline;} div.column{display: inline-block; vertical-align: top; width: 50%;} div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;} ul.task-list{list-style: none;} Survout This is my work related survival output format package. To install: the latest development version: devtools::install_github("SophiaJia/Survout")

Help for package survout const macros = { "\\R": "\\textsf{R}", "\\mbox": "\\text", "\\code": "\\texttt"}; function processMathHTML() { var l = document.getElementsByClassName('reqn'); for (let e of l) { katex.render(e.textContent, e, { throwOnError: false, macros }); } return; } Package {survout} Contents crisk_cat crisk_con crisk_multi crisk_multiuni crisk_ord factor2ind p2excel p2excel_pre surv_multi surv_multiuni surv_uni_cat surv_uni_con Type: Package Title: Excel Conversion of R Surival Analysis Output Version: 0.1.0 Author: Xuefei Jia Maintainer: Xuefei Jia <xuefeij.ai@gmail.com> Description: Simple and quick method of exporting the most often used survival analysis results to an Excel sheet. License: GPL-3 Imports: cmprsk, dplyr, openxlsx, stats, survival, tibble Suggests: covr, MASS, reshape2, testthat (≥ 3.0.0) Config/testthat/edition: 3 Encoding: UTF-8 RoxygenNote: 7.1.1 NeedsCompilation: no Packaged: 2022-09-25 19:50:44 UTC; jiax Repository: CRAN Date/Publication: 2022-09-26 12:50:02 UTC Modify the Output for Uni-variable and Multi-variable Competing Risk Analysis (Categorical Only) Description This function generates a table of competing risk analysis result with number of patients,number of event, number of competing event, Usage crisk_cat( csurv, cevent, cvars, gnames, month = 0, y1 = TRUE, y2 = TRUE, y5 = TRUE ) Arguments csurv the duration of follow-up time in months. cevent the status indicator, which is generally 0 = alive, 1 = event, 2 = other event cvars a vector, which has the variable's values (categorical only) gnames a text string, which is the name of the variable. month a number to get the month-rate of competing risk. y1 logical value indicating whether the 1-year competing risk rate should be reported. y2 logical value indicating whether the 2-year competing risk rate should be reported. y5 logical value indicating whether the 5-year competing risk rate should be reported. Value a tibble of competing risk analysis output. Examples Dat <- MASS::Melanoma Dat$time <- Dat$time/30.5 output <- crisk_cat(Dat$time, Dat$status, Dat$ulcer, "ulcer") Modify the Output for Uni-variable and Multi-variable Competing Risk Analysis (Continuous and Ordinal Only) Description This function generates a table of competing risk analysis result with HR (95% Confidence Interval),P value. Usage crisk_con(csurv, cevent, cvars, gnames) Arguments csurv the duration of follow-up time in months. cevent the status indicator, which is generally 0 = alive, 1 = event, 2 = other event cvars a matrix, which has the variables' values (continuous and ordinal only) gnames a text vector, which are the names of the variables. Value a dataframe containing HRs (with 95% Confidence Intervals) and P values Examples Dat <- MASS::Melanoma Dat$time <- Dat$time/30.5 X <- cbind(Dat$age, Dat$thickness) Gnames <- c('age', 'thickness') output <- crisk_con(Dat$time, Dat$status, X, Gnames) Modify the Output for a Multi-variable Competing Risk Analysis . Description Create a table with the general multi-variable competing risk analysis results, including the HR (95 percent CI), P value. Usage crisk_multi(dat, csurv, cevent, convars = NULL, catvars = NULL) Arguments dat a data.frame in which to interpret the variables. csurv this is the follow up time. cevent the status indicator, normally 0=alive, 1=dead. convars a vector of con variable names. catvars a vector of cat variable names. Value a tibble of competing risk analysis output. Examples Dat <- MASS::Melanoma Dat$time <- Dat$time/30.5 con_var <- c("age","thickness") cat_var <- c("sex","ulcer") multi_out <- crisk_multi(Dat, "time", "status", catvars = cat_var, convars =con_var) Modify the Output for Multiple Uni-variable Competing Risk Analysis . Description This function generates a table of competing risk analysis result with number of patients, number of event, number of competing event, Usage crisk_multiuni( dat, csurv, cevent, catvars = NULL, convars = NULL, ordvars = NULL, y1 = TRUE, y2 = TRUE, y5 = TRUE, month = 0 ) Arguments dat a data.frame in which to interpret the variables. csurv this is the follow up time. cevent the status indicator, normally 0=alive, 1=dead. catvars a vector of cat variable names. convars a vector of con variable names. ordvars a vector of ordinal variable names. y1 logical value indicating whether the 1-year competing risk rate should be reported. y2 logical value indicating whether the 2-year competing risk rate should be reported. y5 logical value indicating whether the 5-year competing risk rate should be reported. month a number to get the month-rate of competing risk. Value a tibble of competing risk analysis output. Examples Dat <- MASS::Melanoma Dat$time <- Dat$time/30.5 Dat$ulcer <- as.factor(Dat$ulcer) con_var <- c("age") ord_var <- c("ulcer") cat_var <- c("sex") uni_out <- crisk_multiuni(Dat, "time", "status",cat_var, con_var, ord_var) Modify the Output for Uni-variable and Multi-variable Competing Risk Analysis (Ordinal Only) Description This function generates a table of competing risk analysis result with number of patients, number of event, number of competing event, Usage crisk_ord( csurv, cevent, cvars, gnames, month = 0, y1 = TRUE, y2 = TRUE, y5 = TRUE ) Arguments csurv the duration of follow-up time in months. cevent the status indicator, which is generally 0 = alive, 1 = event, 2 = other event cvars a vector, which has the variable's values (ordinal only) gnames a text string, which is the name of the variable. month a number to get the month-rate of competing risk. y1 logical value indicating whether the 1-year competing risk rate should be reported. y2 logical value indicating whether the 2-year competing risk rate should be reported. y5 logical value indicating whether the 5-year competing risk rate should be reported. Value a tibble of competing risk analysis output. Examples Dat <- MASS::Melanoma Dat$time <- Dat$time/30.5 output <- crisk_ord(Dat$time, Dat$status, as.factor(Dat$year), "year") Make An Integer Matrix Out of A Factor Variable. Description Create an indicator matrix of dimension length(x) x (nlevels(x)-1) with the column corresponding to the baseline level removed (by default the first level is used as baseline). Usage factor2ind(x, baseline) Arguments x a variable. baseline a string indicating the reference level. Value a matrix Examples x = gl(4, 2, labels = c( "A", "B", "C", "D")) factor2ind(x) factor2ind(x, "C") Export the A Single Dataframe to An Excel Sheet Description The function saves a dataframe into an excel sheet with a predetermined format. Usage p2excel( tabname = "Default", datastable, tablename = "Default", filename = "Default.xlsx" ) Arguments tabname a string with the tab's name. datastable the dataframe that will be exported to Excel. tablename a string containing the table label and title, which will appear as the first row filename the name of the spreadsheet Value a spreadsheet containing an exported tables Prepare to Export the Dataframe to An Excel Sheet. Description The function saves the dataframe as a tab and prepares it for output into an excel sheet with a predetermined format. Usage p2excel_pre(tabname = "Default", datastable, tablename = "Default", filename) Arguments tabname a string with the tab's name. datastable the dataframe that will be exported to Excel. tablename a string containing the table label and title, which will appear as the first row filename the name of the spreadsheet Value a spreadsheet containing all of the exported tables Examples Dat <- survival::lung results <- surv_uni_cat(Dat, "time", "status", "sex", report_index = TRUE) wb <- openxlsx::createWorkbook() wb <- p2excel_pre("survival_results",results,"Table 1. Overall Survival anlaysis",wb) ## Not run: ## saveWorkbook(wb, file = "os.xlsx", overwrite = TRUE) ## End(Not run) Modify the Output for a Multi-variable Survival Analysis. Description Create a table with the general multi-variable survival analysis results, including the HR (95 percent CI),