Release v1.3.1 (#464)

Closes #463

DESCRIPTION

@@ -1,10 +1,11 @@
 Package: rbmi
 Title: Reference Based Multiple Imputation
-Version: 1.3.0.9000
+Version: 1.3.1
 Authors@R: c(
     person("Craig", "Gower-Page", email = "[email protected]", role = c("aut", "cre")),
     person("Alessandro", "Noci", email = "[email protected]", role = c("aut")),
     person("Marcel", "Wolbers", email = "[email protected]", role = "ctb"),
+    person("Isaac", "Gravestock", email = "[email protected]", role = "aut"),
     person("F. Hoffmann-La Roche AG", role = c("cph", "fnd"))
     )
 Description: Implements standard and reference based multiple imputation methods for continuous

NAMESPACE

@@ -104,3 +104,4 @@ importFrom(stats,var)
 importFrom(stats,vcov)
 importFrom(utils,capture.output)
 importFrom(utils,relist)
+importFrom(utils,sessionInfo)

NEWS.md

@@ -1,7 +1,7 @@
 
-# rbmi (development version)
+# rbmi 1.3.1
 
-- No new items yet...
+* Fixed bug where stale caches of the `rstan` model were not being correctly cleared (#459)
 
 # rbmi 1.3.0
 

R/utilities.R

@@ -535,10 +535,11 @@ ensure_rstan <- function() {
 #' Get session hash
 #' 
 #' Gets a unique string based on the current R version and relevant packages.
+#' @importFrom utils sessionInfo
 #' @keywords internal
 get_session_hash <- function() {
     pkg_versions <- vapply(
-        sessionInfo(c("rbmi", "rstan", "Rcpp", "RcppEigen", "BH"))[["otherPkgs"]],
+        sessionInfo(c("rbmi", "rstan", "Rcpp", "RcppEigen"))[["otherPkgs"]],
         function(x) x[["Version"]],
         character(1L)
     )

cran-comments.md

@@ -1,6 +1,6 @@
 ## Summary of Submission
 
-This version of the package adds two new vignettes as well as additional parallel processing support. It also includes a number of minor bug fixes and updates to the documentation.
+This version of the package fixes an issue that was causing the unit tests to crash on CRAN. The issue was due to the package not correctly clearing out the cache of previously compiled `rstan` models.
 
 
 ## R CMD check results

vignettes/advanced.html

@@ -714,7 +714,7 @@ <h1><span class="header-section-number">6</span> Custom imputation strategies</h
 <span id="cb6-17"><a href="#cb6-17" tabindex="-1"></a><span class="co">#&gt;     pars &lt;- list(mu = mu, sigma = sigma)</span></span>
 <span id="cb6-18"><a href="#cb6-18" tabindex="-1"></a><span class="co">#&gt;     return(pars)</span></span>
 <span id="cb6-19"><a href="#cb6-19" tabindex="-1"></a><span class="co">#&gt; }</span></span>
-<span id="cb6-20"><a href="#cb6-20" tabindex="-1"></a><span class="co">#&gt; &lt;bytecode: 0x7fd89cc34720&gt;</span></span>
+<span id="cb6-20"><a href="#cb6-20" tabindex="-1"></a><span class="co">#&gt; &lt;bytecode: 0x7fd7e885e158&gt;</span></span>
 <span id="cb6-21"><a href="#cb6-21" tabindex="-1"></a><span class="co">#&gt; &lt;environment: namespace:rbmi&gt;</span></span></code></pre></div>
 <p>To further illustrate this for a simple example, assume that a new strategy is to be implemented as follows:
 - The marginal mean of the imputation distribution is equal to the marginal mean trajectory for the subject according to their assigned group and covariates up to the ICE.

vignettes/quickstart.html

@@ -456,7 +456,7 @@ <h1><span class="header-section-number">3</span> Draws</h1>
 <span id="cb4-57"><a href="#cb4-57" tabindex="-1"></a>    <span class="at">method =</span> method,</span>
 <span id="cb4-58"><a href="#cb4-58" tabindex="-1"></a>    <span class="at">quiet =</span> <span class="cn">TRUE</span></span>
 <span id="cb4-59"><a href="#cb4-59" tabindex="-1"></a>)</span>
-<span id="cb4-60"><a href="#cb4-60" tabindex="-1"></a><span class="co">#&gt; Warning in fit_mcmc(designmat = model_df_scaled[, -1, drop = FALSE], outcome = model_df_scaled[, : The largest R-hat is 1.06, indicating chains have not mixed.</span></span>
+<span id="cb4-60"><a href="#cb4-60" tabindex="-1"></a><span class="co">#&gt; Warning in fit_mcmc(designmat = model_df_scaled[, -1, drop = FALSE], outcome = model_df_scaled[, : The largest R-hat is 1.05, indicating chains have not mixed.</span></span>
 <span id="cb4-61"><a href="#cb4-61" tabindex="-1"></a><span class="co">#&gt; Running the chains for more iterations may help. See</span></span>
 <span id="cb4-62"><a href="#cb4-62" tabindex="-1"></a><span class="co">#&gt; https://mc-stan.org/misc/warnings.html#r-hat</span></span>
 <span id="cb4-63"><a href="#cb4-63" tabindex="-1"></a>drawObj</span>
@@ -697,33 +697,33 @@ <h1><span class="header-section-number">6</span> Pool</h1>
 <span id="cb9-20"><a href="#cb9-20" tabindex="-1"></a><span class="co">#&gt;      trt_4    -0.092  0.683  -1.439  1.256   0.893  </span></span>
 <span id="cb9-21"><a href="#cb9-21" tabindex="-1"></a><span class="co">#&gt;    lsm_ref_4  -1.616  0.486  -2.576  -0.656  0.001  </span></span>
 <span id="cb9-22"><a href="#cb9-22" tabindex="-1"></a><span class="co">#&gt;    lsm_alt_4  -1.708  0.475  -2.645  -0.77   &lt;0.001 </span></span>
-<span id="cb9-23"><a href="#cb9-23" tabindex="-1"></a><span class="co">#&gt;      trt_5    1.328   0.924  -0.497  3.153   0.153  </span></span>
-<span id="cb9-24"><a href="#cb9-24" tabindex="-1"></a><span class="co">#&gt;    lsm_ref_5  -4.14   0.66   -5.443  -2.838  &lt;0.001 </span></span>
-<span id="cb9-25"><a href="#cb9-25" tabindex="-1"></a><span class="co">#&gt;    lsm_alt_5  -2.812  0.646  -4.088  -1.537  &lt;0.001 </span></span>
-<span id="cb9-26"><a href="#cb9-26" tabindex="-1"></a><span class="co">#&gt;      trt_6    1.939     1    -0.037  3.915   0.054  </span></span>
-<span id="cb9-27"><a href="#cb9-27" tabindex="-1"></a><span class="co">#&gt;    lsm_ref_6  -6.085  0.718  -7.503  -4.667  &lt;0.001 </span></span>
-<span id="cb9-28"><a href="#cb9-28" tabindex="-1"></a><span class="co">#&gt;    lsm_alt_6  -4.146  0.699  -5.527  -2.766  &lt;0.001 </span></span>
-<span id="cb9-29"><a href="#cb9-29" tabindex="-1"></a><span class="co">#&gt;      trt_7    2.136   1.12   -0.078   4.35   0.058  </span></span>
-<span id="cb9-30"><a href="#cb9-30" tabindex="-1"></a><span class="co">#&gt;    lsm_ref_7  -6.982  0.812  -8.587  -5.377  &lt;0.001 </span></span>
-<span id="cb9-31"><a href="#cb9-31" tabindex="-1"></a><span class="co">#&gt;    lsm_alt_7  -4.846  0.789  -6.405  -3.287  &lt;0.001 </span></span>
+<span id="cb9-23"><a href="#cb9-23" tabindex="-1"></a><span class="co">#&gt;      trt_5    1.334   0.926  -0.494  3.162   0.151  </span></span>
+<span id="cb9-24"><a href="#cb9-24" tabindex="-1"></a><span class="co">#&gt;    lsm_ref_5  -4.151  0.661  -5.457  -2.846  &lt;0.001 </span></span>
+<span id="cb9-25"><a href="#cb9-25" tabindex="-1"></a><span class="co">#&gt;    lsm_alt_5  -2.817  0.648  -4.097  -1.537  &lt;0.001 </span></span>
+<span id="cb9-26"><a href="#cb9-26" tabindex="-1"></a><span class="co">#&gt;      trt_6    1.934     1    -0.042   3.91   0.055  </span></span>
+<span id="cb9-27"><a href="#cb9-27" tabindex="-1"></a><span class="co">#&gt;    lsm_ref_6  -6.088  0.715  -7.501  -4.676  &lt;0.001 </span></span>
+<span id="cb9-28"><a href="#cb9-28" tabindex="-1"></a><span class="co">#&gt;    lsm_alt_6  -4.155  0.698  -5.533  -2.777  &lt;0.001 </span></span>
+<span id="cb9-29"><a href="#cb9-29" tabindex="-1"></a><span class="co">#&gt;      trt_7    2.177   1.138  -0.073  4.426   0.058  </span></span>
+<span id="cb9-30"><a href="#cb9-30" tabindex="-1"></a><span class="co">#&gt;    lsm_ref_7  -7.002  0.827  -8.638  -5.367  &lt;0.001 </span></span>
+<span id="cb9-31"><a href="#cb9-31" tabindex="-1"></a><span class="co">#&gt;    lsm_alt_7  -4.826  0.783  -6.373  -3.278  &lt;0.001 </span></span>
 <span id="cb9-32"><a href="#cb9-32" tabindex="-1"></a><span class="co">#&gt;   --------------------------------------------------</span></span></code></pre></div>
 <p>The table of values shown in the print message for <code>poolObj</code> can also be extracted using the <code>as.data.frame()</code> function:</p>
 <div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb10-1"><a href="#cb10-1" tabindex="-1"></a><span class="fu">as.data.frame</span>(poolObj)</span>
 <span id="cb10-2"><a href="#cb10-2" tabindex="-1"></a><span class="co">#&gt;    parameter         est        se         lci        uci         pval</span></span>
 <span id="cb10-3"><a href="#cb10-3" tabindex="-1"></a><span class="co">#&gt; 1      trt_4 -0.09180645 0.6826279 -1.43949684  1.2558839 8.931772e-01</span></span>
 <span id="cb10-4"><a href="#cb10-4" tabindex="-1"></a><span class="co">#&gt; 2  lsm_ref_4 -1.61581996 0.4862316 -2.57577141 -0.6558685 1.093708e-03</span></span>
 <span id="cb10-5"><a href="#cb10-5" tabindex="-1"></a><span class="co">#&gt; 3  lsm_alt_4 -1.70762640 0.4749573 -2.64531931 -0.7699335 4.262148e-04</span></span>
-<span id="cb10-6"><a href="#cb10-6" tabindex="-1"></a><span class="co">#&gt; 4      trt_5  1.32800107 0.9239991 -0.49687491  3.1528770 1.526144e-01</span></span>
-<span id="cb10-7"><a href="#cb10-7" tabindex="-1"></a><span class="co">#&gt; 5  lsm_ref_5 -4.14031255 0.6595847 -5.44302381 -2.8376013 3.163421e-09</span></span>
-<span id="cb10-8"><a href="#cb10-8" tabindex="-1"></a><span class="co">#&gt; 6  lsm_alt_5 -2.81231148 0.6459122 -4.08807336 -1.5365496 2.396574e-05</span></span>
-<span id="cb10-9"><a href="#cb10-9" tabindex="-1"></a><span class="co">#&gt; 7      trt_6  1.93891419 1.0001460 -0.03694571  3.9147741 5.438468e-02</span></span>
-<span id="cb10-10"><a href="#cb10-10" tabindex="-1"></a><span class="co">#&gt; 8  lsm_ref_6 -6.08530002 0.7176967 -7.50335519 -4.6672448 1.946811e-14</span></span>
-<span id="cb10-11"><a href="#cb10-11" tabindex="-1"></a><span class="co">#&gt; 9  lsm_alt_6 -4.14638583 0.6985434 -5.52650481 -2.7662668 1.911219e-08</span></span>
-<span id="cb10-12"><a href="#cb10-12" tabindex="-1"></a><span class="co">#&gt; 10     trt_7  2.13609482 1.1201125 -0.07781920  4.3500088 5.849971e-02</span></span>
-<span id="cb10-13"><a href="#cb10-13" tabindex="-1"></a><span class="co">#&gt; 11 lsm_ref_7 -6.98181990 0.8117268 -8.58678186 -5.3768579 1.511791e-14</span></span>
-<span id="cb10-14"><a href="#cb10-14" tabindex="-1"></a><span class="co">#&gt; 12 lsm_alt_7 -4.84572508 0.7885999 -6.40477980 -3.2866704 7.793320e-09</span></span></code></pre></div>
+<span id="cb10-6"><a href="#cb10-6" tabindex="-1"></a><span class="co">#&gt; 4      trt_5  1.33436741 0.9255820 -0.49370018  3.1624350 1.513737e-01</span></span>
+<span id="cb10-7"><a href="#cb10-7" tabindex="-1"></a><span class="co">#&gt; 5  lsm_ref_5 -4.15140080 0.6608110 -5.45658456 -2.8462170 3.110832e-09</span></span>
+<span id="cb10-8"><a href="#cb10-8" tabindex="-1"></a><span class="co">#&gt; 6  lsm_alt_5 -2.81703340 0.6478134 -4.09662455 -1.5374422 2.460646e-05</span></span>
+<span id="cb10-9"><a href="#cb10-9" tabindex="-1"></a><span class="co">#&gt; 7      trt_6  1.93372720 1.0000881 -0.04213496  3.9095894 5.502527e-02</span></span>
+<span id="cb10-10"><a href="#cb10-10" tabindex="-1"></a><span class="co">#&gt; 8  lsm_ref_6 -6.08849645 0.7148756 -7.50096014 -4.6760328 1.548722e-14</span></span>
+<span id="cb10-11"><a href="#cb10-11" tabindex="-1"></a><span class="co">#&gt; 9  lsm_alt_6 -4.15476925 0.6975559 -5.53298494 -2.7765536 1.739819e-08</span></span>
+<span id="cb10-12"><a href="#cb10-12" tabindex="-1"></a><span class="co">#&gt; 10     trt_7  2.17651184 1.1379189 -0.07335404  4.4263777 5.784145e-02</span></span>
+<span id="cb10-13"><a href="#cb10-13" tabindex="-1"></a><span class="co">#&gt; 11 lsm_ref_7 -7.00205125 0.8268086 -8.63751537 -5.3665871 4.132364e-14</span></span>
+<span id="cb10-14"><a href="#cb10-14" tabindex="-1"></a><span class="co">#&gt; 12 lsm_alt_7 -4.82553941 0.7830124 -6.37333317 -3.2777456 6.903910e-09</span></span></code></pre></div>
 <p>These outputs gives an estimated difference of
-2.136 (95% CI -0.078 to 4.350)
+2.177 (95% CI -0.073 to 4.426)
 between the two groups at the last visit with an associated p-value of 0.058.</p>
 </div>
 <div id="code" class="section level1" number="7">