version 0.2.0

DESCRIPTION

@@ -1,15 +1,18 @@
 Package: arsenal
 Title: An Arsenal of 'R' Functions for Large-Scale Statistical
         Summaries
-Version: 0.1.2
-Date: 2016-12-29
+Version: 0.2.0
+Date: 2017-01-31
+URL: https://cran.r-project.org/package=arsenal
 Authors@R: c(
     person("Ethan", "Heinzen", email = "heinzen.ethan@mayo.edu", role = c("aut", "cre")),
     person("Jason", "Sinnwell", role="aut"),
     person("Elizabeth", "Atkinson", role="aut"),
     person("Tina", "Gunderson", role="aut"),
     person("Gregory", "Dougherty", role="aut"),
     person("Patrick", "Votruba", role="ctb"),
+    person("Ryan", "Lennon", role="ctb"),
+    person("Krista", "Goergen", role="ctb"),
     person("Emily", "Lundt", role="ctb")
   )
 Description: An Arsenal of 'R' functions for large-scale statistical summaries,
@@ -20,22 +23,24 @@ Description: An Arsenal of 'R' functions for large-scale statistical summaries,
   variable; modelsum(), which performs simple model fits on the same endpoint
   for many variables (univariate or adjusted for standard covariates);
   and freqlist(), a powerful frequency table across many categorical variables.
-Suggests: knitr, rmarkdown, xtable, survival, testthat, coin, pROC,
-        MASS, gam, rpart
+Suggests: knitr, rmarkdown, xtable, pander, survival, testthat, coin,
+        pROC, MASS, gam, rpart
 Depends: R (>= 3.2.0), stats (>= 3.2.0)
 Imports: broom, stringr
 VignetteBuilder: knitr
 License: GPL (>= 2)
 RoxygenNote: 5.0.1
 NeedsCompilation: no
-Packaged: 2016-12-29 15:03:54 UTC; m144326
+Packaged: 2017-01-31 23:21:39 UTC; m144326
 Author: Ethan Heinzen [aut, cre],
   Jason Sinnwell [aut],
   Elizabeth Atkinson [aut],
   Tina Gunderson [aut],
   Gregory Dougherty [aut],
   Patrick Votruba [ctb],
+  Ryan Lennon [ctb],
+  Krista Goergen [ctb],
   Emily Lundt [ctb]
 Maintainer: Ethan Heinzen <heinzen.ethan@mayo.edu>
 Repository: CRAN
-Date/Publication: 2016-12-30 01:18:42
+Date/Publication: 2017-02-01 00:41:55

MD5

@@ -1,66 +1,78 @@
-966d309a0df5d55be152e36454793ba7 *DESCRIPTION
-3f62d030021234740076da4d1ba8f002 *NAMESPACE
-a5124b7fb1a608cf22414d0d439c5893 *NEWS.md
-babe9da5c34ab0be1462ebb582b67f01 *R/arsenal.R
+64ca95954a157e40c441927a12517109 *DESCRIPTION
+163a641c4257c9de5b13411233a96e6d *NAMESPACE
+ed12d43b046ac8b13ad042d42dd7dcf4 *NEWS.md
+9e5c80edccdf89f7401dc898be315b6a *R/arsenal.R
 79e2033244f329fa85d87cbc4013f678 *R/formulize.R
-cfa9ea4571efbb3e9de3bc79dcc56041 *R/freqlist.R
+9b361e8234e2f7dbdb5bf8abad07e12a *R/freqlist.R
 e42ce669505128b0f0b20ac6c621e91d *R/freqlist.internal.R
-02a7e6a76fe38503ed55d6d0da6e12dd *R/internal.functions.R
+75cce2779e3a321a78e8cd56f6e42b6a *R/internal.functions.R
 2f474534e9fc946996d331ad8103b5ea *R/magic8.R
 e54a23c0326058d798de6b3c912a8003 *R/mdy.Date.R
 1de6a042544ab82b1d3e5d5264e3ffe9 *R/mockstudy.R
-8a60fb9fd3e6b75451fd52a671343fdf *R/modelsum.R
+db9d7550daea1f2251908395723b6606 *R/modelsum.R
 8972abaedd55f0c7f1418ad70f233302 *R/modelsum.control.R
 8c879e7ce937bdbedb5fd3fb31a11d3f *R/modelsum.internal.R
 0e56f25775a178e261295319e70889bd *R/not.in.R
 50cd5149107450c83f3e3f855aeb57ad *R/release_questions.R
 915d58ab60615cd9c66bfc92131cfba1 *R/summary.freqlist.R
-1dff52d601070cac366b7123de8f8680 *R/summary.modelsum.R
+e3eaad9fb39c372f2ed4aeaddf303289 *R/summary.modelsum.R
 318e7c0c95e3737f5c209a9ba9ebea7b *R/summary.tableby.R
-918558ed28af0fd4f0338c9d9787b926 *R/tableby.R
+5df40ef875f0a8d2d7ffdca177c051d5 *R/tableby.R
 6cd26e41a5b57be0697d1e98594fb16d *R/tableby.control.R
 4b5df64d48a8f090b29f7eb55008b5db *R/tableby.internal.R
 9bb29fd9186f2e7c11351693f70aa2e8 *R/tableby.stat.tests.R
 d795cb92f9d3e5ec846b31c0579badd3 *R/tableby.stats.R
-872993fdbe93e6707fae16f6e0a0c99f *R/write2.R
-018618b1d1fb15a1945e7892e2868204 *README.md
-4aafc7bc18223c036874a46def9050bc *build/vignette.rds
+56b73ad8b0d8ae2da6a8cd8e0934749e *R/write2.R
+9978346e6d56e7fcdf127d79f01a7649 *README.md
+e91dac73925af6b800aafec7b3780ab6 *build/vignette.rds
 30cd2d9369ee4d94dd76dcbf5a215559 *data/mockstudy.RData
-79433ae6628afba73b4751b5e6bbb32e *inst/doc/freqlist.R
-b90b634df89f2a4dc597b834d4a0457d *inst/doc/freqlist.Rmd
-197db4ba70c32f0a3579ba56e71b8c7b *inst/doc/freqlist.pdf
-2be512c16c57f0c19d46a03559fa66ed *inst/doc/modelsum.R
-cfe0b0bd54ea0d5dd64b179d025a5621 *inst/doc/modelsum.Rmd
-85570c3c621adb383c345f2e09bd5a1e *inst/doc/modelsum.html
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-0f686caa3862dd071b6538bd17b5d0c8 *inst/doc/tableby.Rmd
-78a397ba49bf53164ac6bf6eb5278c0b *inst/doc/tableby.html
-fb7f3dd8cf45309fc533d5cb863271b8 *man/arsenal.Rd
+6426e345a14c9dec20d62c6456c4e9f0 *inst/doc/freqlist.R
+d81e95828e521941e139482c962e9710 *inst/doc/freqlist.Rmd
+37d87dba1400ad18ec9abbba8dda1cbf *inst/doc/freqlist.html
+92e0994599563842bd6a019ec6ea4102 *inst/doc/modelsum.R
+7b5d1fa9bc0c43d57a226738d4b54c7f *inst/doc/modelsum.Rmd
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+a68ec9f4260ce8c2c93e5a85f6c673e2 *inst/doc/tableby.R
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+eb330c6faaa31ef5f91bcf135056faad *inst/doc/tableby.html
+2be7ca8e41f22208b476876029e80657 *inst/doc/write2.R
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 a08790dee110e6f91216f1c9f7b9888e *man/as.data.frame.freqlist.Rd
-fb7c429f3c12092d0fad2dc88754fd8f *man/as.data.frame.modelsum.Rd
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 1326c71d7954bf79cd26895f0aedd30f *man/as.data.frame.tableby.Rd
 2133b459a58b59f77b1e835fafc009e6 *man/formulize.Rd
 c15c3a5f78637e5ac782800687fd2289 *man/freqlist.Rd
 b149f67287b2605109b516fbd9ef8f20 *man/freqlist.internal.Rd
 5148640645d5b9f0de27a83ba4ed6788 *man/grapes-nin-grapes.Rd
 2e1f8c2d941134f65a82f84346247458 *man/mdy.Date.Rd
 4cd57758131c3d1dffce65879eb34e76 *man/mockstudy.Rd
-fb624ea9b801473dae9d30eefe8a1047 *man/modelsum.Rd
+1d876b7eb1a077a5220759b72535f65c *man/modelsum.Rd
 ee7241120bee38b7c92d9160f86699e0 *man/modelsum.control.Rd
 56b926cfc2d81c0539e70ca8a4d68794 *man/modelsum.internal.Rd
 562faf3ed641a245644af5887f5704aa *man/summary.freqlist.Rd
-1a749d94bb67684290e8d11927700f0d *man/summary.modelsum.Rd
+0ab1c3227e5d79e9a4419e0546fbaa77 *man/summary.modelsum.Rd
 b03d9fe7d9940a052a7b539b58a4f2c5 *man/summary.tableby.Rd
-d8894b3a8db813af90570d664d3009dd *man/tableby.Rd
+43e9f7d6d6a5c5316f98dc1bdc78e3c1 *man/tableby.Rd
 e60ebe8ed16f9112a141ec2b24574b10 *man/tableby.control.Rd
 c00a698159af17705b7306ce44e2070b *man/tableby.internal.Rd
 a7d8a4fca049fadfeb6be460b35a209f *man/tableby.stats.Rd
-6d0a923e8398c923744d26bcbb44ddc3 *man/write2.Rd
+fa58b2bb17f00974410a7d06f6b20b83 *man/write2.Rd
+013f6556b9cd188c26365af8f42c1ec7 *man/write2specific.Rd
 b86d96d2b720f7aeeb3b9412b87d67ef *tests/testthat.R
-ba8ab9b99798b694a5f5b06b9a28f2d8 *tests/testthat/test_formulize.R
-6811553415304e4626ae831d29c1d680 *tests/testthat/test_freqlist.R
-d4732617af6ee210bbdc165014b5a4b2 *tests/testthat/test_modelsum.R
-357806abad78c1b6ca0c358d6d4d9b4a *tests/testthat/test_tableby.R
-b90b634df89f2a4dc597b834d4a0457d *vignettes/freqlist.Rmd
-cfe0b0bd54ea0d5dd64b179d025a5621 *vignettes/modelsum.Rmd
-0f686caa3862dd071b6538bd17b5d0c8 *vignettes/tableby.Rmd
+1c0b875954db84c2384bf6d753d50146 *tests/testthat/test_formulize.R
+2943f65b203a330bfde7f22fbd0967d9 *tests/testthat/test_freqlist.R
+8016a1934078062f9128e70b1943a8fb *tests/testthat/test_modelsum.R
+d37c1af2099852398edf4aa01295a6bf *tests/testthat/test_tableby.R
+1c732994556af5cd482c218cf6c039d8 *tests/testthat/test_write2.R
+f177f2b74b4f9f751e8edbb6a9fad712 *tests/testthat/write2.freqlist.html
+0a7b3e0ee537b49cf7ed5c11b1a4fecd *tests/testthat/write2.kable.html
+83bfb15f5b9103e625c16cbccbfad808 *tests/testthat/write2.modelsum.html
+61cdf411f2af5411f89903cba990ea9e *tests/testthat/write2.pander.html
+f43dc701ee19bf489fa31c12c1f9ffb1 *tests/testthat/write2.tableby.html
+f00648a7b68d7c41a326ef44d2129152 *tests/testthat/write2.xtable.html
+d81e95828e521941e139482c962e9710 *vignettes/freqlist.Rmd
+7b5d1fa9bc0c43d57a226738d4b54c7f *vignettes/modelsum.Rmd
+d19754caf6254260ec847743d8b228db *vignettes/tableby.Rmd
+403d798936814c679eeaa22ea6180ff7 *vignettes/write2.Rmd

NAMESPACE

@@ -21,6 +21,13 @@ S3method(summary,freqlist)
 S3method(summary,modelsum)
 S3method(summary,tableby)
 S3method(tests,tableby)
+S3method(write2,character)
+S3method(write2,default)
+S3method(write2,freqlist)
+S3method(write2,knitr_kable)
+S3method(write2,modelsum)
+S3method(write2,tableby)
+S3method(write2,xtable)
 export("%nin%")
 export("labels<-")
 export(Date.mdy)
@@ -44,6 +51,7 @@ export(q1q3)
 export(tableby)
 export(tableby.control)
 export(tests)
+export(write2)
 export(write2html)
 export(write2pdf)
 export(write2word)

NEWS.md

@@ -1,3 +1,12 @@
+# arsenal 0.2.0
+
+* Vignettes have been updated.
+
+* `write2()` is now exported and supports all output formats supported by `rmarkdown::render()`. There is now a vignette for it
+  and the S3 methods have been expanded to handle more inputs, including `knitr::kable()`, `xtable::xtable()`, and `pander::pander_return()`.
+
+* Fixed a bug in `summary.modelsum()`.
+
 # arsenal 0.1.2
 
 * `broom` and `stringr` have been moved to `imports` instead of `depends`.

R/arsenal.R

@@ -6,6 +6,8 @@
 #' An Arsenal of 'R' functions for large-scale statistical summaries,
 #'   which are streamlined to work within the latest reporting tools in 'R' and 'RStudio' and
 #'   which use formulas and versatile summary statistics for summary tables and models.
+#'   
+#' The package download, NEWS, and README are available on CRAN: \url{https://cran.r-project.org/package=arsenal}
 #'
 #' @section Functions:
 #' 
@@ -19,6 +21,8 @@
 #' 
 #' \code{\link{write2word}}, \code{\link{write2html}}, \code{\link{write2pdf}}: Functions to generate a word, html, or pdf document containing a single table.
 #' 
+#' \code{\link{write2}}: Functions to generate a single document containing a single table. (Also the S3 backbone behind the \code{write2*} functions.)
+#' 
 #' \code{\link{formulize}}: A shortcut to generate one-, two-, or many-sided formulas.
 #' 
 #' \code{\link{mdy.Date}} and \code{\link{Date.mdy}}: Convert numeric dates for month, day, and year to Date object, and vice versa.
@@ -36,7 +40,6 @@
 NULL
 
 #### commands to build the package using devtools
-# devtools::document()
 # devtools::check_man()
 # devtools::test()
 # devtools::check()

R/freqlist.R

@@ -131,7 +131,7 @@ freqlist <- function(tab, sparse = FALSE, na.options = c('include', 'showexclude
 #' @export
 print.freqlist <- function(x, ...)
 {
-  cat("Freqlist object\n\n")
+  cat("Freqlist Object\n\n")
   cat(ncol(x$freqlist) - 4, " variables:\n", sep = "")
   print(colnames(x$freqlist)[1:(ncol(x$freqlist) - 4)])
   invisible(x)

R/internal.functions.R

@@ -498,7 +498,7 @@ makePaddedStr <- function(startStr, size, padChar = ' ') {
   }
 
   # See if can split the string on a reasonable boundary character
-  for (split in c(" ", "\t", "_", "-", "*", ".", ";", ":")) {
+  for (split in c(" ", "\t", "_", "-",".", ";", ":")) {
     results <- strsplit(startStr, split, fixed = TRUE)[[1]]
     if ((length(results) > 1) && (minStrLen(results) <= size))
       return(pastePaddedStr(results, size, sep = split, padChar = padChar, appendSep = TRUE))

R/modelsum.R

@@ -47,13 +47,14 @@
 #'  
 #' data(mockstudy)
 #' 
-#' tab1 <- modelsum(bmi ~ sex + age, data=mockstudy)
-#' summary(tab1, text=TRUE)
+#' tab1 <- modelsum(bmi ~ sex + age, data = mockstudy)
+#' summary(tab1, text = TRUE)
 #' 
-#' tab2 <- modelsum(alk.phos ~ arm + ps + hgb, adjust= ~age + sex, family="gaussian",data=mockstudy)
-#' summary(tab2, text=TRUE)
+#' tab2 <- modelsum(alk.phos ~ arm + ps + hgb, adjust = ~ age + sex,
+#'                  family = "gaussian", data = mockstudy)
+#' summary(tab2, text = TRUE)
 #' 
-#' summary(tab2, show.intercept=FALSE, text=TRUE)
+#' summary(tab2, show.intercept = FALSE, text = TRUE)
 #' 
 #' tab2.df <- as.data.frame(tab2)
 #' 

R/summary.modelsum.R

@@ -14,7 +14,7 @@ modelsum.translations <- list() ## adj.r.squared = "adj.rsq", sex = "Sex", sexM
 #' @param object The data defining the table to display
 #' @param title	Title for the table, defaults to \code{NULL} (no title)
 #' @param labelTranslations List where name is the label in the output, and value is the label you 
-#' 		want displayed e.g. \code{list (q1q3: "Q1, Q3", medsurv = "Median Survival")}.
+#' 		want displayed e.g. \code{list(q1q3 = "Q1, Q3", medsurv = "Median Survival")}.
 #' @param digits Maximum number of digits to display for floating point numbers. 
 #' 		If \code{NA} (default), it uses the value from \code{object$control$digits} 
 #' 		(whose default is 3, which would result in, e.g., 12.3, 1.23, 0.123, and 0.012).

R/tableby.R

@@ -111,7 +111,7 @@
 #' tab1 <- tableby(arm ~ sex + age, data=mockstudy)
 #' summary(tab1, text=TRUE)
 #' 
-#' mylabels <- list( sex = "SEX", age ="Age, yrs")
+#' mylabels <- list(sex = "SEX", age ="Age, yrs")
 #' summary(tab1, labelTranslations = mylabels, text=TRUE)
 #' 
 #' tab3 <- tableby(arm ~ sex + age, data=mockstudy, test=FALSE, total=FALSE,