adds test_left_censorship, and all the docs to do it

DESCRIPTION

@@ -1,24 +1,44 @@
 Package: ICIKendallTau
 Title: Calculates information-content-informed Kendall-tau
-Version: 1.0.5
-Date: 2024-04-08
-Authors@R: c(person(given = c("Robert", "M"), family = "Flight", role =
-        c("aut", "cre"), email = "rflight79@gmail.com", comment =
-        c(ORCID = "0000-0001-8141-7788")), person(given = c("Hunter",
-        "NB"), family = "Moseley", role = "aut", comment = c(ORCID =
-        "0000-0003-3995-5368")))
+Version: 1.1.0
+Authors@R: c(
+    person(
+      given = c("Robert", "M"), 
+      family = "Flight", 
+      role = c("aut", "cre"), 
+      email = "rflight79@gmail.com", 
+      comment = c(ORCID = "0000-0001-8141-7788")), 
+    person(
+      given = c("Hunter", "NB"), 
+      family = "Moseley", 
+      role = "aut", 
+      comment = c(ORCID = "0000-0003-3995-5368")))
 Description: Provides functions for calculating
         information-content-informed Kendall-tau. This version of
         Kendall-tau allows for the inclusion of missing values.
 VignetteBuilder: knitr
+LazyData: true
 License: MIT + file LICENSE
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
 RoxygenNote: 7.3.1
 LinkingTo: Rcpp
-Imports: Rcpp, purrr, utils, stringr
-Suggests: furrr, future, testthat (>= 3.0.0), microbenchmark,
-        rmarkdown, knitr, dplyr, logger
-URL: https://moseleybioinformaticslab.github.io/ICIKendallTau
-        https://github.com/moseleybioinformaticslab/ICIKendallTau
+Imports: Rcpp, 
+         purrr, 
+         utils, 
+         stringr,
+         stats
+Suggests: furrr, 
+          future, 
+          testthat (>= 3.0.0), 
+          microbenchmark,
+          rmarkdown, 
+          knitr, 
+          dplyr, 
+          logger, 
+          withr,
+          naniar
+URL: https://moseleybioinformaticslab.github.io/ICIKendallTau/
+        https://github.com/moseleybioinformaticslab/ICIKendallTau/
+BugReports: https://github.com/moseleybioinformaticslab/ICIKendallTau/issues
 Config/testthat/edition: 3

NEWS.md

@@ -1,3 +1,7 @@
+# ICIKendallTau 1.1.0
+
+- adds the function `test_left_censorship` to verify if `ici_kendalltau` is appropriate to use on the data or not.
+
 # ICIKendallTau 1.0.0
 
 - Calculates correlation between columns of the matrix, **not** the rows.

R/kendalltau.R

@@ -12,11 +12,9 @@
 #' @param check_timing logical to determine should we try to estimate run time for full dataset? (default is FALSE)
 #' @param return_matrix logical, should the data.frame or matrix result be returned?
 #' 
-#' @seealso [vignette("ici-kendalltau", package = "ICIKendallTau")] [test_left_censorship()]
+#' @seealso [test_left_censorship()] [pairwise_completeness()] [kt_fast()]
 #' 
-#' @details For more details, see the ICI-Kendall-tau vignette 
-#' 
-#' \code{browseVignettes("ICIKendallTau")}
+#' @details For more details, see the vignette `vignette("ici-kendalltau", package = "ICIKendallTau"))`
 #' 
 #'   The default for \code{global_na} includes what values in the data to replace with NA for the Kendall-tau calculation. By default these are \code{global_na = c(NA, Inf, 0)}. If you want to replace something other than 0, for example, you might use \code{global_na = c(NA, Inf, -2)}, and all values of -2 will be replaced instead of 0.
 #'   
@@ -30,6 +28,10 @@
 #'   * taumax: the theoretical maximum kendall-tau value possible
 #'   
 #'   Eventually, we plan to provide two more parameters for replacing values, \code{feature_na} for feature specific NA values and \code{sample_na} for sample specific NA values.
+#'   
+#'   If you want to know if the missing values in your data are possibly due to 
+#'   left-censorship, we recommend testing that hypothesis with [test_left_censorship()]
+#'   first.
 #' 
 #' @return list with cor, raw, pval, taumax
 #' 
@@ -315,8 +317,8 @@ ici_kendalltau = function(data_matrix,
 #' @param use an optional character string giving a method for computing correlations in the presence of missing values. This must be (an abbreviation of) one of the strings "everything", "all.obs", "complete.obs", or "pairwise.complete.obs".
 #' @param return_matrix Should the matrices of values be returned, or a long data.frame
 #' 
-#' @details Although the interface is *mostly* identical to the built-in `stats::cor` method, 
-#'   there are some differences. 
+#' @details Although the interface is *mostly* identical to the built-in 
+#' [stats::cor()] method, there are some differences. 
 #'   
 #'  * if providing both `x` and `y`, it is assumed they are both
 #'  single vectors.
@@ -535,6 +537,8 @@ kt_fast = function(x, y = NULL, use = "everything", return_matrix = TRUE)
 #' @param include_only is there certain comparisons to do?
 #' @param return_matrix should the matrix or data.frame be returned?
 #' 
+#' @seealso [ici_kendalltau()]
+#' 
 #' @export
 #' 
 #' @return matrix of degree of completeness

R/left_censorship.R

@@ -17,7 +17,9 @@
 #' instances (minus missing values) as the number of trials, and the number of
 #' of features below the sample medians as the number of successes.
 #' 
-#' @seealso [vignette("testing-for-left-censorship", package = "ICIKendallTau")]
+#' There is a bit more detail in the vignette: `vignette("testing-for-left-censorship", package = "ICIKendallTau")`
+#' 
+#' @seealso [ici_kendalltau()]
 #' 
 #' @examples
 #' # this example has 80% missing due to left-censorship

README.Rmd

@@ -21,7 +21,7 @@ knitr::opts_chunk$set(
 [![ICIKendallTau status badge](https://moseleybioinformaticslab.r-universe.dev/badges/ICIKendallTau)](https://moseleybioinformaticslab.r-universe.dev)
 <!-- badges: end -->
 
-You can see the pkgdown site [here](https://moseleybioinformaticslab.github.io/ICIKendallTau).
+You can see the pkgdown site [here](https://moseleybioinformaticslab.github.io/ICIKendallTau/).
 
 ## Installation
 
@@ -49,7 +49,7 @@ install.packages("ICIKendallTau")
   * In these cases, NA is informative.
   * Therefore, in **most** analytical measurements (gene expression, proteomics, metabolomics), missing measurements should be included, and contribute to the correlation.
 
-If you want to read more on **how** we solve this problem, see the package vignette.
+If you want to read more on **how** we solve this problem, see the package [vignette](https://moseleybioinformaticslab.github.io/ICIKendallTau/articles/ici-kendalltau.html).
 
 ## Package Functions
 
@@ -65,6 +65,8 @@ The functions that implement this include:
     * `plan(multiprocess)`
   * Otherwise will only use a single core.
 
+We've also included a function for testing if the missingness in your data comes from left-censorship, `test_left_censorship`. We walk through creating example data and testing it in the vignette [Testing for Left Censorship](https://moseleybioinformaticslab.github.io/ICIKendallTau/articles/testing-for-left-censorship).
+
 ## Examples
 
 The most common case is a large matrix of independent samples (columns) and measured features in each of the samples (i.e. gene expression).
@@ -158,7 +160,7 @@ r_3 = ici_kendalltau(matrix_2)
 In the case of hundreds of thousands of comparisons to be done, the result matrices can become very, very large, and require lots of memory for storage.
 They are also inefficient, as both the lower and upper triangular components are stored.
 An alternative storage format is as a `data.frame`, where there is a single row for each comparison performed.
-This is actually how the results are stored internally, and then they are converted to a matrix form if requested (the default).s
+This is actually how the results are stored internally, and then they are converted to a matrix form if requested (the default). 
 To keep the `data.frame` output, add the argument `return_matrix=FALSE` to the call of `ici_kendalltau`.
 
 ```{r}

README.html

@@ -606,10 +606,10 @@
 <h1 id="icikendalltau">ICIKendallTau</h1>
 <!-- badges: start -->
 
-<p><a href="https://moseleybioinformaticslab.r-universe.dev"><img src="data:image/svg+xml; charset=utf-8;base64,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" alt="ICIKendallTau status badge" /></a></p>
+<p><a href="https://moseleybioinformaticslab.r-universe.dev"><img src="data:image/svg+xml; charset=utf-8;base64,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" alt="ICIKendallTau status badge" /></a></p>
 <!-- badges: end -->
 
-<p>You can see the pkgdown site <a href="https://moseleybioinformaticslab.github.io/ICIKendallTau">here</a>.</p>
+<p>You can see the pkgdown site <a href="https://moseleybioinformaticslab.github.io/ICIKendallTau/">here</a>.</p>
 <h2 id="installation">Installation</h2>
 <p>You can install the current version of ICIKendallTau via GitHub:</p>
 <div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" tabindex="-1"></a>remotes<span class="sc">::</span><span class="fu">install_github</span>(<span class="st">&quot;MoseleyBioinformaticsLab/ICIKendallTau&quot;</span>)</span></code></pre></div>
@@ -639,7 +639,7 @@ <h2 id="problem">Problem</h2>
 </ul></li>
 </ul>
 <p>If you want to read more on <strong>how</strong> we solve this
-problem, see the package vignette.</p>
+problem, see the package <a href="https://moseleybioinformaticslab.github.io/ICIKendallTau/articles/ici-kendalltau.html">vignette</a>.</p>
 <h2 id="package-functions">Package Functions</h2>
 <p>The functions that implement this include:</p>
 <ul>
@@ -662,6 +662,10 @@ <h2 id="package-functions">Package Functions</h2>
 <li>Otherwise will only use a single core.</li>
 </ul></li>
 </ul>
+<p>We’ve also included a function for testing if the missingness in your
+data comes from left-censorship, <code>test_left_censorship</code>. We
+walk through creating example data and testing it in the vignette <a href="https://moseleybioinformaticslab.github.io/ICIKendallTau/articles/testing-for-left-censorship">Testing
+for Left Censorship</a>.</p>
 <h2 id="examples">Examples</h2>
 <p>The most common case is a large matrix of independent samples
 (columns) and measured features in each of the samples (i.e. gene
@@ -721,14 +725,10 @@ <h2 id="is-it-fast">Is It Fast?</h2>
 <span id="cb5-14"><a href="#cb5-14" tabindex="-1"></a>  <span class="at">times =</span> <span class="dv">5</span></span>
 <span id="cb5-15"><a href="#cb5-15" tabindex="-1"></a>)</span>
 <span id="cb5-16"><a href="#cb5-16" tabindex="-1"></a><span class="co">#&gt; Unit: microseconds</span></span>
-<span id="cb5-17"><a href="#cb5-17" tabindex="-1"></a><span class="co">#&gt;                           expr       min        lq       mean    median        uq       max</span></span>
-<span id="cb5-18"><a href="#cb5-18" tabindex="-1"></a><span class="co">#&gt;  cor(x, y, method = &quot;kendall&quot;) 11506.697 11670.094 12169.6628 12006.418 12482.883 13182.222</span></span>
-<span id="cb5-19"><a href="#cb5-19" tabindex="-1"></a><span class="co">#&gt;         ici_kt(x, y, &quot;global&quot;)   243.866   250.125   294.6542   275.104   320.058   384.118</span></span>
-<span id="cb5-20"><a href="#cb5-20" tabindex="-1"></a><span class="co">#&gt;       ici_kt(x2, y2, &quot;global&quot;) 13467.011 13739.312 14658.5050 14945.446 14987.140 16153.616</span></span>
-<span id="cb5-21"><a href="#cb5-21" tabindex="-1"></a><span class="co">#&gt;  neval</span></span>
-<span id="cb5-22"><a href="#cb5-22" tabindex="-1"></a><span class="co">#&gt;      5</span></span>
-<span id="cb5-23"><a href="#cb5-23" tabindex="-1"></a><span class="co">#&gt;      5</span></span>
-<span id="cb5-24"><a href="#cb5-24" tabindex="-1"></a><span class="co">#&gt;      5</span></span></code></pre></div>
+<span id="cb5-17"><a href="#cb5-17" tabindex="-1"></a><span class="co">#&gt;                           expr       min        lq       mean    median        uq       max neval</span></span>
+<span id="cb5-18"><a href="#cb5-18" tabindex="-1"></a><span class="co">#&gt;  cor(x, y, method = &quot;kendall&quot;) 11685.244 12730.878 12860.9060 13071.630 13406.514 13410.264     5</span></span>
+<span id="cb5-19"><a href="#cb5-19" tabindex="-1"></a><span class="co">#&gt;         ici_kt(x, y, &quot;global&quot;)   263.306   268.503   332.1288   274.858   283.589   570.388     5</span></span>
+<span id="cb5-20"><a href="#cb5-20" tabindex="-1"></a><span class="co">#&gt;       ici_kt(x2, y2, &quot;global&quot;) 14110.743 14322.836 15782.6490 16053.907 16595.979 17829.780     5</span></span></code></pre></div>
 <p>In the case of 40,000 features, the average time on a modern CPU is
 14 milliseconds.</p>
 <p>Of course, if you want to use it to calculate Kendall-tau-b without
@@ -757,7 +757,7 @@ <h2 id="many-many-comparisons">Many Many Comparisons</h2>
 triangular components are stored. An alternative storage format is as a
 <code>data.frame</code>, where there is a single row for each comparison
 performed. This is actually how the results are stored internally, and
-then they are converted to a matrix form if requested (the default).s To
+then they are converted to a matrix form if requested (the default). To
 keep the <code>data.frame</code> output, add the argument
 <code>return_matrix=FALSE</code> to the call of
 <code>ici_kendalltau</code>.</p>
@@ -770,7 +770,7 @@ <h2 id="many-many-comparisons">Many Many Comparisons</h2>
 <span id="cb9-7"><a href="#cb9-7" tabindex="-1"></a><span class="co">#&gt; 3 s4 s4    0 1.0000000      0 1.000000 1.0000000</span></span>
 <span id="cb9-8"><a href="#cb9-8" tabindex="-1"></a><span class="co">#&gt; </span></span>
 <span id="cb9-9"><a href="#cb9-9" tabindex="-1"></a><span class="co">#&gt; $run_time</span></span>
-<span id="cb9-10"><a href="#cb9-10" tabindex="-1"></a><span class="co">#&gt; [1] 0.01606894</span></span></code></pre></div>
+<span id="cb9-10"><a href="#cb9-10" tabindex="-1"></a><span class="co">#&gt; [1] 0.01747489</span></span></code></pre></div>
 <h2 id="code-of-conduct">Code of Conduct</h2>
 <p>Please note that the ICIKendallTau project is released with a <a href="https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html">Contributor
 Code of Conduct</a>. By contributing to this project, you agree to abide

README.md

@@ -10,7 +10,7 @@ badge](https://moseleybioinformaticslab.r-universe.dev/badges/ICIKendallTau)](ht
 <!-- badges: end -->
 
 You can see the pkgdown site
-[here](https://moseleybioinformaticslab.github.io/ICIKendallTau).
+[here](https://moseleybioinformaticslab.github.io/ICIKendallTau/).
 
 ## Installation
 
@@ -47,7 +47,8 @@ install.packages("ICIKendallTau")
     and contribute to the correlation.
 
 If you want to read more on **how** we solve this problem, see the
-package vignette.
+package
+[vignette](https://moseleybioinformaticslab.github.io/ICIKendallTau/articles/ici-kendalltau.html).
 
 ## Package Functions
 
@@ -66,6 +67,11 @@ The functions that implement this include:
     - `plan(multiprocess)`
   - Otherwise will only use a single core.
 
+We’ve also included a function for testing if the missingness in your
+data comes from left-censorship, `test_left_censorship`. We walk through
+creating example data and testing it in the vignette [Testing for Left
+Censorship](https://moseleybioinformaticslab.github.io/ICIKendallTau/articles/testing-for-left-censorship).
+
 ## Examples
 
 The most common case is a large matrix of independent samples (columns)
@@ -136,14 +142,10 @@ microbenchmark(
   times = 5
 )
 #> Unit: microseconds
-#>                           expr       min        lq       mean    median        uq       max
-#>  cor(x, y, method = "kendall") 11506.697 11670.094 12169.6628 12006.418 12482.883 13182.222
-#>         ici_kt(x, y, "global")   243.866   250.125   294.6542   275.104   320.058   384.118
-#>       ici_kt(x2, y2, "global") 13467.011 13739.312 14658.5050 14945.446 14987.140 16153.616
-#>  neval
-#>      5
-#>      5
-#>      5
+#>                           expr       min        lq       mean    median        uq       max neval
+#>  cor(x, y, method = "kendall") 11685.244 12730.878 12860.9060 13071.630 13406.514 13410.264     5
+#>         ici_kt(x, y, "global")   263.306   268.503   332.1288   274.858   283.589   570.388     5
+#>       ici_kt(x2, y2, "global") 14110.743 14322.836 15782.6490 16053.907 16595.979 17829.780     5
 ```
 
 In the case of 40,000 features, the average time on a modern CPU is 14
@@ -188,7 +190,7 @@ for storage. They are also inefficient, as both the lower and upper
 triangular components are stored. An alternative storage format is as a
 `data.frame`, where there is a single row for each comparison performed.
 This is actually how the results are stored internally, and then they
-are converted to a matrix form if requested (the default).s To keep the
+are converted to a matrix form if requested (the default). To keep the
 `data.frame` output, add the argument `return_matrix=FALSE` to the call
 of `ici_kendalltau`.
 
@@ -202,7 +204,7 @@ r_4
 #> 3 s4 s4    0 1.0000000      0 1.000000 1.0000000
 #> 
 #> $run_time
-#> [1] 0.01606894
+#> [1] 0.01747489
 ```
 
 ## Code of Conduct