Description: Observational studies are limited in that there could be
an unmeasured variable related to both the response variable
and the primary predictor.  If this unmeasured variable were
included in the analysis it would change the relationship
(possibly changing the conclusions).  Sensitivity analysis is a
way to see how much of a relationship needs to exist with the
unmeasured variable before the conclusions change.  This
package provides tools for doing a sensitivity analysis for
regression (linear, logistic, and cox) style models.

Title: Sensitivity Analysis for Observational Studies

Description: Checks that a given dataset passes user-specified
rules. The main functions are observe_if() and inspect().
Imports: bazar, bit, dplyr, lazyeval, magrittr, tibble, utils

Author: Keith Poole <kpoole@ucsd.edu>, Jeffrey Lewis <jblewis@ucla.edu>, James Lo <jameslo@ucla.edu> and Royce Carroll <rcarroll@ucsd.edu>
Description: Estimates Optimal Classification scores from roll call votes supplied though a 'rollcall' object from package 'pscl'.
Packaged: Tue Mar 27 19:08:14 2007; jameslo

Packaged: Thu May 10 16:52:22 2007; jameslo

Packaged: Wed Aug 15 19:35:21 2007; jameslo

Packaged: Wed Sep  3 09:43:49 2008; hornik

Author: Keith Poole <kpoole@ucsd.edu>, Jeffrey Lewis
<jblewis@ucla.edu>, James Lo <jameslo@ucla.edu> and Royce
Description: Estimates Optimal Classification scores from roll call
votes supplied though a 'rollcall' object from package 'pscl'.

Author: Keith Poole <ktpoole@uga.edu>, Jeffrey Lewis
<jblewis@ucla.edu>, James Lo <jameslo@princeton.edu> and Royce

<jblewis@ucla.edu>, James Lo <lojames@usc.edu> and Royce

Title: Optimal Classification Roll Call Analysis Software
Description: Estimates optimal classification (Poole 2000) <doi:10.1093/oxfordjournals.pan.a029814>
scores from roll call votes supplied though a 'rollcall'

Title: Estimates PET neuroreceptor occupancies
Description: This package provides a generic function for estimating
positron emission tomography (PET) neuroreceptor occupancies
from the total volumes of distribution of a set of regions of
interest. Fittings methods include the simple 'reference
region' and 'ordinary least squares' (sometimes known as
occupancy plot) methods, as well as the more efficient