<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Glynn, A.N.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Product and Difference Fallacies for Indirect Effects</style></title><secondary-title><style face="normal" font="default" size="100%">American Journal of Political Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><volume><style face="normal" font="default" size="100%">56</style></volume><pages><style face="normal" font="default" size="100%">257-269</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Political scientists often cite the importance of mechanism-specific causal knowledge, both for its intrinsic scientific value and as a necessity for informed policy. This article explains why two common inferential heuristics for mechanism-specific (i.e., indirect) effects can provide misleading answers, such as sign reversals and false null results, even when linear regressions provide unbiased estimates of constituent effects. Additionally, this article demonstrates that the inferential difficulties associated with indirect effects can be ameliorated with the use of stratification, interaction terms, and the restriction of inference to subpopulations (e.g., the indirect effect on the treated). However, indirect effects are inherently not identifiable— even when randomized experiments are possible. The methodological discussion is illustrated using a study on the indirect effect of Islamic religious tradition on democracy scores (due to the subordination of women).&lt;/p&gt;
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