diff --git a/DESCRIPTION b/DESCRIPTION
index 2332a8426..9f2fb0f6d 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,8 +1,8 @@
 Package: broom
 Type: Package
 Title: Convert Statistical Analysis Objects into Tidy Data Frames
-Version: 0.3.7.9000
-Date: 2015-05-05
+Version: 0.4.0
+Date: 2015-11-30
 Authors@R: c(
     person("David", "Robinson", email = "admiral.david@gmail.com", role = c("aut", "cre")),
     person("Matthieu", "Gomez", email = "mattg@princeton.edu", role = "ctb"),
diff --git a/NEWS.md b/NEWS.md
index baead3dda..2b688e5e7 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,10 +1,13 @@
-* Added a `tidy` method for x,y,z lists used by `image` and `persp`
-
-broom 0.3.7.9000
+broom 0.4.0
 -----------
 
+* Added tidiers for geeglm, nlrq, roc, boot, bgterm, kappa, binWidth, binDesign, rcorr, stanfit, rjags, gamlss, and mle2 objects.
+* Added `tidy` methods for lists, including u, d, v lists from `svd`, and x, y, z lists used by `image` and `persp`
 * Added `quick` argument to `tidy.lm`, `tidy.nls`, and `tidy.biglm`, to create a smaller and faster version of the output.
 * Changed `rowwise_df_tidiers` to allow the original data to be saved as a list column, then provided as a column name to `augment`. This required removing `data` from the `augment` S3 signature. Also added `tests-rowwise.R`
+* Fixed various issues in ANOVA output
+* Fixed various issues in lme4 output
+* Fixed issues in tests caused by dev version of ggplot2
 
 broom 0.3.7
 -----------
diff --git a/R/mcmc_tidiers.R b/R/mcmc_tidiers.R
index 1ce340b1c..bbf4eecab 100644
--- a/R/mcmc_tidiers.R
+++ b/R/mcmc_tidiers.R
@@ -1,5 +1,3 @@
-## FIXME: design question -- how to make tidying methods inherit appropriately?
-
 #' Tidying methods for MCMC (Stan, JAGS, etc.) fits
 #'
 #' @param x an object of class \sQuote{"stanfit"}
@@ -79,16 +77,16 @@ tidyMCMC <- function(x,
     estimate.method <- match.arg(estimate.method, c("mean", "median"))
     m <- switch(estimate.method,
                 mean = colMeans(ss),
-                median = apply(ss, 2, median))
+                median = apply(ss, 2, stats::median))
 
     ret <- data.frame(estimate = m,
-                      std.error = apply(ss, 2, sd))
+                      std.error = apply(ss, 2, stats::sd))
     if (conf.int) {
         levs <- c((1 - conf.level) / 2, (1 + conf.level) / 2)
 
         conf.method <- match.arg(conf.method, c("quantile", "HPDinterval"))
         ci <- switch(conf.method,
-                     quantile = t(apply(ss, 2, quantile, levs)),
+                     quantile = t(apply(ss, 2, stats::quantile, levs)),
                      coda::HPDinterval(coda::as.mcmc(ss), prob = conf.level))
 
         colnames(ci) <- c("conf.low", "conf.high")
diff --git a/cran-comments.md b/cran-comments.md
index ea3c8c5c3..9f1f26344 100644
--- a/cran-comments.md
+++ b/cran-comments.md
@@ -1,18 +1,22 @@
-broom 0.3.7
+broom 0.4.0
 -----------
 
 ## Changes
 
-This is a re-submission:
-
-* Put 'dplyr', 'tidyr' and 'ggplot2' in single quotes in DESCRIPTION
+* Added tidiers for geeglm, nlrq, roc, boot, bgterm, kappa, binWidth, binDesign, rcorr, stanfit, rjags, gamlss, and mle2 objects.
+* Added `tidy` methods for lists, including u, d, v lists from `svd`, and x, y, z lists used by `image` and `persp`
+* Added `quick` argument to `tidy.lm`, `tidy.nls`, and `tidy.biglm`, to create a smaller and faster version of the output.
+* Changed `rowwise_df_tidiers` to allow the original data to be saved as a list column, then provided as a column name to `augment`. This required removing `data` from the `augment` S3 signature. Also added `tests-rowwise.R`
+* Fixed various issues in ANOVA output
+* Fixed various issues in lme4 output
+* Fixed issues in tests caused by dev version of ggplot2
 
 ## Test environments
-* local OS X install, R 3.2.0
+* local OS X install, R 3.2.2
 * win-builder (devel and release)
 
 ## R CMD check results
-There were no ERRORs or WARNINGs.
+There were no ERRORs, WARNINGs or NOTEs.
 
 ## Reverse dependencies
-Broom has one reverse dependency, radiant. I ran R CMD check on radiant 0.1.83 with broom 0.3.7 and it showed no ERRORs, WARNINGs, or NOTEs.
+Broom has seven reverse dependencies in CRAN: AutoModel, dotwhisker, eyetrackingR, forestmodel, HydeNet, pixiedust, and plotly. I ran R CMD CHECK on each with the newest version of broom and found no ERRORs, WARNINGs, or NOTEs.