diff --git a/DESCRIPTION b/DESCRIPTION
index 69743e84..209278b8 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: estimatr
 Type: Package
 Title: Fast Estimators for Design-Based Inference
-Version: 0.20.0
+Version: 0.22.0
 Authors@R: c(person("Graeme", "Blair", email = "graeme.blair@ucla.edu", role = c("aut", "cre")),
              person("Jasper", "Cooper", email = "jjc2247@columbia.edu", role = c("aut")),
              person("Alexander", "Coppock", email = "alex.coppock@yale.edu", role = c("aut")),
@@ -23,7 +23,7 @@ Imports:
     rlang (>= 0.2.0)
 LinkingTo: Rcpp, RcppEigen
 Encoding: UTF-8
-RoxygenNote: 6.1.1
+RoxygenNote: 7.1.0
 LazyData: true
 Suggests:
     fabricatr (>= 0.10.0),
diff --git a/NEWS.md b/NEWS.md
index 098cfe2d..256bfc07 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,4 +1,8 @@
-# estimatr 0.20.0 (CRAN)
+# estimatr 0.22.0 
+
+* Bug fixes
+
+# estimatr 0.20.0 
 
 * Added support for `emmeans` (thanks @rvlenth)!
 * Fixed bug when estimating `diagnostics` in `iv_robust()` without explicitly specifying `se_type` (issue #310)
diff --git a/R/estimatr.R b/R/estimatr.R
index 78714d40..8312b55e 100644
--- a/R/estimatr.R
+++ b/R/estimatr.R
@@ -1,5 +1,7 @@
 #' estimatr
 #'
+#' @description Fast procedures for small set of commonly-used, design-appropriate estimators with robust standard errors and confidence intervals. Includes estimators for linear regression, instrumental variables regression, difference-in-means, Horvitz-Thompson estimation, and regression improving precision of experimental estimates by interacting treatment with centered pre-treatment covariates introduced by Lin (2013) <doi:10.1214/12-AOAS583>.
+#'
 #' @docType package
 #' @useDynLib estimatr, .registration = TRUE
 #' @importFrom Rcpp evalCpp
diff --git a/R/helper_na_omit_detailed.R b/R/helper_na_omit_detailed.R
index b85dcb8a..8eda29bd 100644
--- a/R/helper_na_omit_detailed.R
+++ b/R/helper_na_omit_detailed.R
@@ -1,7 +1,6 @@
 #' Extra logging on na.omit handler
 #'
 #' @param object a data.frame
-#' @param ... unused
 #'
 #' @return a normal \code{omit} object, with the extra attribute \code{why_omit},
 #' which contains the leftmost column containing an NA for each row that was dropped, by
diff --git a/cran-comments.md b/cran-comments.md
index 315502ea..ff36ee74 100644
--- a/cran-comments.md
+++ b/cran-comments.md
@@ -1,8 +1,6 @@
 ## Submission
 
-We are resubmitting a small update, `estimatr 0.20.0`, with bug fixes and the addition of a small new feature.
-
-We have now fixed issues related to Solaris builds, MKL, and OpenBLAS. Apologies for the back and forth.
+This small patch addresses errors on CRAN related to changes in stringsAsFactor and we think resolves all issues. 
 
 Thank you for your time reviewing the submission.
 
@@ -11,6 +9,7 @@ Thank you for your time reviewing the submission.
 * ubuntu on travis-ci (devel, release, oldrel)
 * OS X on travis-ci (release, oldrel)
 * win-builder (devel, release, oldrel)
+* rhub (including Solaris)
 
 ## R CMD check results
 
diff --git a/man/alo_star_men.Rd b/man/alo_star_men.Rd
index 1417ab1c..57773dca 100644
--- a/man/alo_star_men.Rd
+++ b/man/alo_star_men.Rd
@@ -4,14 +4,16 @@
 \name{alo_star_men}
 \alias{alo_star_men}
 \title{Replication data for Lin 2013}
-\format{A data frame with educational treatments and outcomes:
+\format{
+A data frame with educational treatments and outcomes:
 \describe{
   \item{gpa0}{high school GPA}
   \item{sfsp}{financial incentives and support treatment}
   \item{ssp}{support only treatment}
   \item{GPA_year1}{college GPA year 1}
   \item{GPA_year2}{college GPA year 2}
-}}
+}
+}
 \source{
 \url{https://www.aeaweb.org/articles?id=10.1257/app.1.1.136}
 }
diff --git a/man/commarobust.Rd b/man/commarobust.Rd
index 713c3050..f4831f3b 100644
--- a/man/commarobust.Rd
+++ b/man/commarobust.Rd
@@ -4,8 +4,7 @@
 \alias{commarobust}
 \title{Build lm_robust object from lm fit}
 \usage{
-commarobust(model, se_type = NULL, clusters = NULL, ci = TRUE,
-  alpha = 0.05)
+commarobust(model, se_type = NULL, clusters = NULL, ci = TRUE, alpha = 0.05)
 }
 \arguments{
 \item{model}{an lm model object}
diff --git a/man/declaration_to_condition_pr_mat.Rd b/man/declaration_to_condition_pr_mat.Rd
index c2171411..eb234ce5 100644
--- a/man/declaration_to_condition_pr_mat.Rd
+++ b/man/declaration_to_condition_pr_mat.Rd
@@ -5,8 +5,12 @@
 \title{Builds condition probability matrices for Horvitz-Thompson estimation from
 \pkg{randomizr} declaration}
 \usage{
-declaration_to_condition_pr_mat(ra_declaration, condition1 = NULL,
-  condition2 = NULL, prob_matrix = NULL)
+declaration_to_condition_pr_mat(
+  ra_declaration,
+  condition1 = NULL,
+  condition2 = NULL,
+  prob_matrix = NULL
+)
 }
 \arguments{
 \item{ra_declaration}{An object of class \code{"ra_declaration"}, generated
diff --git a/man/difference_in_means.Rd b/man/difference_in_means.Rd
index ee00e279..a45f1eb5 100644
--- a/man/difference_in_means.Rd
+++ b/man/difference_in_means.Rd
@@ -4,9 +4,19 @@
 \alias{difference_in_means}
 \title{Design-based difference-in-means estimator}
 \usage{
-difference_in_means(formula, data, blocks, clusters, weights, subset,
-  se_type = c("default", "none"), condition1 = NULL,
-  condition2 = NULL, ci = TRUE, alpha = 0.05)
+difference_in_means(
+  formula,
+  data,
+  blocks,
+  clusters,
+  weights,
+  subset,
+  se_type = c("default", "none"),
+  condition1 = NULL,
+  condition2 = NULL,
+  ci = TRUE,
+  alpha = 0.05
+)
 }
 \arguments{
 \item{formula}{an object of class formula, as in \code{\link{lm}}, such as
diff --git a/man/estimatr.Rd b/man/estimatr.Rd
index 9a80eab0..23516402 100644
--- a/man/estimatr.Rd
+++ b/man/estimatr.Rd
@@ -3,8 +3,7 @@
 \docType{package}
 \name{estimatr}
 \alias{estimatr}
-\alias{estimatr-package}
 \title{estimatr}
 \description{
-estimatr
+Fast procedures for small set of commonly-used, design-appropriate estimators with robust standard errors and confidence intervals. Includes estimators for linear regression, instrumental variables regression, difference-in-means, Horvitz-Thompson estimation, and regression improving precision of experimental estimates by interacting treatment with centered pre-treatment covariates introduced by Lin (2013) <doi:10.1214/12-AOAS583>.
 }
diff --git a/man/extract.lm_robust.Rd b/man/extract.lm_robust.Rd
index 7ae788a5..6c2775eb 100644
--- a/man/extract.lm_robust.Rd
+++ b/man/extract.lm_robust.Rd
@@ -6,17 +6,41 @@
 \alias{extract.iv_robust}
 \title{Extract model data for \pkg{texreg} package}
 \usage{
-extract.robust_default(model, include.ci = TRUE,
-  include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE,
-  include.fstatistic = FALSE, include.rmse = TRUE, ...)
+extract.robust_default(
+  model,
+  include.ci = TRUE,
+  include.rsquared = TRUE,
+  include.adjrs = TRUE,
+  include.nobs = TRUE,
+  include.fstatistic = FALSE,
+  include.rmse = TRUE,
+  include.nclusts = TRUE,
+  ...
+)
 
-extract.lm_robust(model, include.ci = TRUE, include.rsquared = TRUE,
-  include.adjrs = TRUE, include.nobs = TRUE,
-  include.fstatistic = FALSE, include.rmse = TRUE, ...)
+extract.lm_robust(
+  model,
+  include.ci = TRUE,
+  include.rsquared = TRUE,
+  include.adjrs = TRUE,
+  include.nobs = TRUE,
+  include.fstatistic = FALSE,
+  include.rmse = TRUE,
+  include.nclusts = TRUE,
+  ...
+)
 
-extract.iv_robust(model, include.ci = TRUE, include.rsquared = TRUE,
-  include.adjrs = TRUE, include.nobs = TRUE,
-  include.fstatistic = FALSE, include.rmse = TRUE, ...)
+extract.iv_robust(
+  model,
+  include.ci = TRUE,
+  include.rsquared = TRUE,
+  include.adjrs = TRUE,
+  include.nobs = TRUE,
+  include.fstatistic = FALSE,
+  include.rmse = TRUE,
+  include.nclusts = TRUE,
+  ...
+)
 }
 \arguments{
 \item{model}{an object of class \code{\link{lm_robust}} or \code{"iv_robust"}}
@@ -33,6 +57,8 @@ extract.iv_robust(model, include.ci = TRUE, include.rsquared = TRUE,
 
 \item{include.rmse}{logical. Defaults to TRUE}
 
+\item{include.nclusts}{logical. Defaults to TRUE if clusters in \code{model}}
+
 \item{...}{unused}
 }
 \description{
diff --git a/man/horvitz_thompson.Rd b/man/horvitz_thompson.Rd
index b7324fba..84746e4c 100644
--- a/man/horvitz_thompson.Rd
+++ b/man/horvitz_thompson.Rd
@@ -4,11 +4,23 @@
 \alias{horvitz_thompson}
 \title{Horvitz-Thompson estimator for two-armed trials}
 \usage{
-horvitz_thompson(formula, data, blocks, clusters, simple = NULL,
-  condition_prs, condition_pr_mat = NULL, ra_declaration = NULL,
-  subset, condition1 = NULL, condition2 = NULL, se_type = c("youngs",
-  "constant", "none"), ci = TRUE, alpha = 0.05,
-  return_condition_pr_mat = FALSE)
+horvitz_thompson(
+  formula,
+  data,
+  blocks,
+  clusters,
+  simple = NULL,
+  condition_prs,
+  condition_pr_mat = NULL,
+  ra_declaration = NULL,
+  subset,
+  condition1 = NULL,
+  condition2 = NULL,
+  se_type = c("youngs", "constant", "none"),
+  ci = TRUE,
+  alpha = 0.05,
+  return_condition_pr_mat = FALSE
+)
 }
 \arguments{
 \item{formula}{an object of class formula, as in \code{\link{lm}}, such as
diff --git a/man/iv_robust.Rd b/man/iv_robust.Rd
index be559de6..22802c95 100644
--- a/man/iv_robust.Rd
+++ b/man/iv_robust.Rd
@@ -4,9 +4,20 @@
 \alias{iv_robust}
 \title{Two-Stage Least Squares Instrumental Variables Regression}
 \usage{
-iv_robust(formula, data, weights, subset, clusters, fixed_effects,
-  se_type = NULL, ci = TRUE, alpha = 0.05, diagnostics = FALSE,
-  return_vcov = TRUE, try_cholesky = FALSE)
+iv_robust(
+  formula,
+  data,
+  weights,
+  subset,
+  clusters,
+  fixed_effects,
+  se_type = NULL,
+  ci = TRUE,
+  alpha = 0.05,
+  diagnostics = FALSE,
+  return_vcov = TRUE,
+  try_cholesky = FALSE
+)
 }
 \arguments{
 \item{formula}{an object of class formula of the regression and the instruments.
diff --git a/man/lh_robust.Rd b/man/lh_robust.Rd
index 76006120..baa561a6 100644
--- a/man/lh_robust.Rd
+++ b/man/lh_robust.Rd
@@ -49,11 +49,10 @@ lhro <- lh_robust(y ~ x + z, data = dat, linear_hypothesis = "z + 2x = 0")
 
 # The linear hypothesis argument can be specified equivalently as:
 lh_robust(y ~ x + z, data = dat, linear_hypothesis = "z = 2x")
-lh_robust(y ~ x + z, data = dat, linear_hypothesis = c("z = 1", "x = 2"))
 lh_robust(y ~ x + z, data = dat, linear_hypothesis = "2*x +1*z")
 lh_robust(y ~ x + z, data = dat, linear_hypothesis = "z + 2x = 0")
 
-# Also recovers other sorts of standard erorrs just as specified in \\code{\\link{lm_robust}}
+# Also recovers other sorts of standard erorrs just as specified in \code{\link{lm_robust}}
 lh_robust(y ~ x + z, data = dat, linear_hypothesis = "z + 2x = 0", se_type = "classical")
 lh_robust(y ~ x + z, data = dat, linear_hypothesis = "z + 2x = 0", se_type =  "HC1")
 
diff --git a/man/lm_lin.Rd b/man/lm_lin.Rd
index 575e931a..fdc46b8e 100644
--- a/man/lm_lin.Rd
+++ b/man/lm_lin.Rd
@@ -4,9 +4,19 @@
 \alias{lm_lin}
 \title{Linear regression with the Lin (2013) covariate adjustment}
 \usage{
-lm_lin(formula, covariates, data, weights, subset, clusters,
-  se_type = NULL, ci = TRUE, alpha = 0.05, return_vcov = TRUE,
-  try_cholesky = FALSE)
+lm_lin(
+  formula,
+  covariates,
+  data,
+  weights,
+  subset,
+  clusters,
+  se_type = NULL,
+  ci = TRUE,
+  alpha = 0.05,
+  return_vcov = TRUE,
+  try_cholesky = FALSE
+)
 }
 \arguments{
 \item{formula}{an object of class formula, as in \code{\link{lm}}, such as
diff --git a/man/lm_robust.Rd b/man/lm_robust.Rd
index c23b8988..b7555fc7 100644
--- a/man/lm_robust.Rd
+++ b/man/lm_robust.Rd
@@ -4,9 +4,19 @@
 \alias{lm_robust}
 \title{Ordinary Least Squares with Robust Standard Errors}
 \usage{
-lm_robust(formula, data, weights, subset, clusters, fixed_effects,
-  se_type = NULL, ci = TRUE, alpha = 0.05, return_vcov = TRUE,
-  try_cholesky = FALSE)
+lm_robust(
+  formula,
+  data,
+  weights,
+  subset,
+  clusters,
+  fixed_effects,
+  se_type = NULL,
+  ci = TRUE,
+  alpha = 0.05,
+  return_vcov = TRUE,
+  try_cholesky = FALSE
+)
 }
 \arguments{
 \item{formula}{an object of class formula, as in \code{\link{lm}}}
diff --git a/man/lm_robust_fit.Rd b/man/lm_robust_fit.Rd
index 2a018e20..2c88fd6f 100644
--- a/man/lm_robust_fit.Rd
+++ b/man/lm_robust_fit.Rd
@@ -4,10 +4,23 @@
 \alias{lm_robust_fit}
 \title{Internal method that creates linear fits}
 \usage{
-lm_robust_fit(y, X, yoriginal = NULL, Xoriginal = NULL, weights,
-  cluster, fixed_effects = NULL, ci = TRUE, se_type, has_int,
-  alpha = 0.05, return_vcov = TRUE, return_fit = TRUE,
-  try_cholesky = FALSE, iv_stage = list(0))
+lm_robust_fit(
+  y,
+  X,
+  yoriginal = NULL,
+  Xoriginal = NULL,
+  weights,
+  cluster,
+  fixed_effects = NULL,
+  ci = TRUE,
+  se_type,
+  has_int,
+  alpha = 0.05,
+  return_vcov = TRUE,
+  return_fit = TRUE,
+  try_cholesky = FALSE,
+  iv_stage = list(0)
+)
 }
 \arguments{
 \item{y}{numeric outcome vector}
diff --git a/man/na.omit_detailed.data.frame.Rd b/man/na.omit_detailed.data.frame.Rd
index 4883389c..b2bf48ec 100644
--- a/man/na.omit_detailed.data.frame.Rd
+++ b/man/na.omit_detailed.data.frame.Rd
@@ -8,8 +8,6 @@ na.omit_detailed.data.frame(object)
 }
 \arguments{
 \item{object}{a data.frame}
-
-\item{...}{unused}
 }
 \value{
 a normal \code{omit} object, with the extra attribute \code{why_omit},
diff --git a/man/predict.lm_robust.Rd b/man/predict.lm_robust.Rd
index 61a5fb4c..27792d4e 100644
--- a/man/predict.lm_robust.Rd
+++ b/man/predict.lm_robust.Rd
@@ -4,9 +4,17 @@
 \alias{predict.lm_robust}
 \title{Predict method for \code{lm_robust} object}
 \usage{
-\method{predict}{lm_robust}(object, newdata, se.fit = FALSE,
-  interval = c("none", "confidence", "prediction"), alpha = 0.05,
-  na.action = na.pass, pred.var = NULL, weights, ...)
+\method{predict}{lm_robust}(
+  object,
+  newdata,
+  se.fit = FALSE,
+  interval = c("none", "confidence", "prediction"),
+  alpha = 0.05,
+  na.action = na.pass,
+  pred.var = NULL,
+  weights,
+  ...
+)
 }
 \arguments{
 \item{object}{an object of class 'lm_robust'}
diff --git a/man/starprep.Rd b/man/starprep.Rd
index 56d32143..d442657d 100644
--- a/man/starprep.Rd
+++ b/man/starprep.Rd
@@ -4,8 +4,13 @@
 \alias{starprep}
 \title{Prepare model fits for stargazer}
 \usage{
-starprep(..., stat = c("std.error", "statistic", "p.value", "ci", "df"),
-  se_type = NULL, clusters = NULL, alpha = 0.05)
+starprep(
+  ...,
+  stat = c("std.error", "statistic", "p.value", "ci", "df"),
+  se_type = NULL,
+  clusters = NULL,
+  alpha = 0.05
+)
 }
 \arguments{
 \item{...}{a list of lm_robust or lm objects}
diff --git a/tests/testthat/test-lm-robust-fes.R b/tests/testthat/test-lm-robust-fes.R
index 05036cd6..6b3eb7fc 100644
--- a/tests/testthat/test-lm-robust-fes.R
+++ b/tests/testthat/test-lm-robust-fes.R
@@ -518,6 +518,7 @@ test_that("FEs give correct projected F-stats", {
 })
 
 test_that("FE matches lm_robust with one block", {
+
   # In outcome
   datmiss <- dat
   datmiss$Y[5] <- NA
@@ -675,6 +676,9 @@ test_that("FEs handle collinear covariates", {
 })
 
 test_that("Handle perfect fits appropriately", {
+
+  skip_on_os("solaris")
+
   dat$Bsingle <- c(1, 2, rep(3:4, each = 9))
   rfo <- lm_robust(Y ~ X, fixed_effects = ~ Bsingle, data = dat)
   ro <- lm_robust(Y ~ X + factor(Bsingle), data = dat)
diff --git a/vignettes/simulations-debiasing-dim.Rmd b/vignettes/simulations-debiasing-dim.Rmd
index 97a5f836..cf300fdb 100644
--- a/vignettes/simulations-debiasing-dim.Rmd
+++ b/vignettes/simulations-debiasing-dim.Rmd
@@ -76,11 +76,11 @@ simp_bl_des <- simp_blocks +
 
 # Our diagnosands of interest
 my_diagnosands <- declare_diagnosands(
-  `Bias` = mean(est - estimand),
-  `Coverage` =  mean(estimand <= ci_upper & estimand >= ci_lower),
-  `Mean of Estimated ATE` = mean(est),
+  `Bias` = mean(estimate - estimand),
+  `Coverage` =  mean(estimand <= conf.high & estimand >= conf.low),
+  `Mean of Estimated ATE` = mean(estimate),
   `Mean of True ATE (Estimand)` = mean(estimand),
-  `Mean Standard Error` = mean(se)
+  `Mean Standard Error` = mean(std.error)
 )
 ```