version 8.3

Author: Graeme Blair

ChangeLog

@@ -17,5 +17,6 @@ version      date  description
 7.1	 11/28/14  Bug fixes
 8.0	 05/19/15  Added statistical model to combine responses to a list experiment and a direct question on the same subject proposed in Aronow, Coppock, Crawford, and 	Green (2015), and also added weighted regression for many standard list experiment models including linear, NLS, and several maximum likelihood models. Several bug fixes.
 8.1  07/26/16  Bug fix
-8.2  08/15/16  Added functionality for including auxiliary information by generalized method of moments
+8.2  08/15/16  Minor changes
+8.3  10/25/16  Added functionality for including auxiliary information by generalized method of moments
 

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: list
-Version: 8.2
-Date: 2016-7-26
+Version: 8.3
+Date: 2016-10-25
 Title: Statistical Methods for the Item Count Technique and List Experiment
 Author: Graeme Blair [aut, cre], Kosuke Imai [aut, cre], Bethany Park [ctb],
     Alexander Coppock [ctb], Winston Chou [ctb]
@@ -28,18 +28,21 @@ Description: Allows researchers to conduct multivariate
     survey methodology is also known as the item count technique or
     the unmatched count technique and is an alternative to the commonly
     used randomized response method. The package implements the methods
-    developed by Imai (2011), Blair and Imai (2012), Blair,
-    Imai, and Lyall (2013), Imai, Park, and Greene (2014),
-    and Aronow, Coppock, Crawford, and Green (2015).
-    This includes a Bayesian MCMC implementation of regression
-    for the standard and multiple sensitive item list experiment
-    designs and a random effects setup, a Bayesian MCMC hierarchical
-    regression model with up to three hierarchical groups, the
-    combined list experiment and endorsement experiment regression
-    model, a joint model of the list experiment that enables
-    the analysis of the list experiment as a predictor in
-    outcome regression models, and a method for combining list
-    experiments with direct questions. In addition, the package
+    developed by Imai (2011) <doi:10.1198/jasa.2011.ap10415>, 
+    Blair and Imai (2012) <doi:10.1093/pan/mpr048>, 
+    Blair, Imai, and Lyall (2013) <doi:10.1111/ajps.12086>, 
+    Imai, Park, and Greene (2014) <doi:10.1093/pan/mpu017>,
+    Aronow, Coppock, Crawford, and Green (2015) <doi:10.1093/jssam/smu023>, 
+    and Chou, Imai, and Rosenfeld (2016) 
+    <http://imai.princeton.edu/research/files/auxiliary.pdf>. 
+    This includes a Bayesian MCMC implementation of regression for the 
+    standard and multiple sensitive item list experiment designs and a 
+    random effects setup, a Bayesian MCMC hierarchical regression model 
+    with up to three hierarchical groups, the combined list experiment 
+    and endorsement experiment regression model, a joint model of the 
+    list experiment that enables the analysis of the list experiment as 
+    a predictor in outcome regression models, and a method for combining 
+    list experiments with direct questions. In addition, the package
     implements the statistical test that is designed to detect
     certain failures of list experiments, and a placebo test
     for the list experiment using data from direct questions.

inst/CITATION

@@ -6,12 +6,12 @@ citEntry(entry = "misc",
                    as.person("Kosuke Imai")),
   howpublished = "Available at The Comprehensive R Archive Network (CRAN)",
   year         = "2010",
-  url          = "http://CRAN.R-project.org/package=list",
+  url          = "https://CRAN.R-project.org/package=list",
 
   textVersion  =
   paste("Graeme Blair and Kosuke Imai (2010).",
         "list: Statistical Methods for the Item Count Technique and List Experiment.",
         "available at The Comprehensive R Archive Network (CRAN).",
-        "URL http://CRAN.R-project.org/package=list.")
+        "URL https://CRAN.R-project.org/package=list")
 )