Package: WhatIf
Version: 1.5-5
Date: 2009-03-03
Title: WhatIf: Software for Evaluating Counterfactuals
Author: Heather Stoll <hstoll@polsci.ucsb.edu>, Gary King
        <king@harvard.edu>, Langche Zeng <zeng@ucsd.edu>,
Maintainer: Heather Stoll <hstoll@polisci.ucsb.edu>
Depends: R (>= 2.3.1), lpSolve
Description: Inferences about counterfactuals are essential for
        prediction, answering what if questions, and estimating causal
        effects.  However, when the counterfactuals posed are too far
        from the data at hand, conclusions drawn from well-specified
        statistical analyses become based largely on speculation hidden
        in convenient modeling assumptions that few would be willing to
        defend.  Unfortunately, standard statistical approaches assume
        the veracity of the model rather than revealing the degree of
        model-dependence, which makes this problem hard to detect.
        WhatIf offers easy-to-apply methods to evaluate counterfactuals
        that do not require sensitivity testing over specified classes
        of models.  If an analysis fails the tests offered here, then
        we know that substantive inferences will be sensitive to at
        least some modeling choices that are not based on empirical
        evidence, no matter what method of inference one chooses to
        use.  WhatIf implements the methods for evaluating
        counterfactuals discussed in Gary King and Langche Zeng, 2006,
        "The Dangers of Extreme Counterfactuals," Political Analysis 14
        (2); and Gary King and Langche Zeng, 2007, "When Can History Be
        Our Guide?  The Pitfalls of Counterfactual Inference,"
        International Studies Quarterly 51 (March).
License: GPL (>= 2)
URL: http://gking.harvard.edu/whatif
Packaged: Tue Mar 3 20:49:37 2009; king
Repository: CRAN
Date/Publication: 2009-03-08 16:10:18
