diff --git a/DESCRIPTION b/DESCRIPTION
index 984036c..9b8a650 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,20 +1,26 @@
 Package: tipr
 Type: Package
 Title: Tipping Point Analyses
-Version: 1.0.0
+Version: 1.0.1
 Authors@R: c(
     person("Lucy", "D'Agostino McGowan", , "lucydagostino@gmail.com", 
     role = c("aut", "cre"), comment = c(ORCID = "0000-0002-6983-2759"))
            )
 Description: The strength of evidence provided by epidemiological and observational 
             studies is inherently limited by the potential for unmeasured confounding. 
-            We focus on three key quantities: the observed bound of the confidence interval
-            closest to the null, a plausible residual effect size for an unmeasured continuous 
-            or binary confounder, and a realistic mean difference or prevalence difference for 
-            this hypothetical confounder. Building on the methods put forth by 
-            Lin, Psaty, & Kronmal (1998) <doi:10.2307/2533848>, we can use these quantities to 
-            assess how an unmeasured confounder may tip our result to insignificance, rendering the
-            study inconclusive.
+            We focus on three key quantities: the observed bound of the confidence 
+            interval closest to the null, the relationship between an unmeasured 
+            confounder and the outcome, for example a plausible residual effect 
+            size for an unmeasured continuous or binary confounder, and the 
+            relationship between an unmeasured confounder and the exposure, 
+            for example a realistic mean difference or prevalence difference 
+            for this hypothetical confounder between exposure groups. Building 
+            on the methods put forth by Cornfield et al. (1959), Bross (1966), 
+            Schlesselman (1978), Rosenbaum & Rubin (1983), Lin et al. (1998), 
+            Lash et al. (2009), Rosenbaum (1986), Cinelli & Hazlett (2020), 
+            VanderWeele & Ding (2017), and Ding & VanderWeele (2016), 
+            we can use these quantities to assess how an unmeasured confounder
+            may tip our result to insignificance.<doi:10.21105/joss.04495>
 License: MIT + file LICENSE
 Encoding: UTF-8
 RoxygenNote: 7.1.2
diff --git a/NEWS.md b/NEWS.md
index 3018f12..5f64e5e 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -2,6 +2,7 @@
 
 * Fixed bug, functions based on the `adjust_coef_with_binary` function had the old parameter names (`exposed_p` and `unexposed_p`). These were changed to match the other new updates from version 1.0.0 to now be `exposed_confounder_prev` and `unexposed_confounder_prev`.
 * Change "relative risk" to "risk ratio" in all documentation.
+* Add new JOSS citation
 
 # tipr 1.0.0
 
diff --git a/inst/CITATION b/inst/CITATION
new file mode 100644
index 0000000..d320218
--- /dev/null
+++ b/inst/CITATION
@@ -0,0 +1,11 @@
+bibentry(
+  "Article",
+  title = "tipr: An R package for sensitivity analyses for unmeasured confounders",
+  author = "Lucy D'Agostino McGowan",
+  year = 2022,
+  journal = "Journal of Open Source Software",
+  volume = 7,
+  number = 77,
+  pages = 4495,
+  doi = "10.21105/joss.04495"
+)