TY - JOUR
T1 - No News Is News
T2 - Nonignorable Nonresponse in Roll-Call Data Analysis
AU - Rosas, Guillermo
AU - Shomer, Yael
AU - Haptonstahl, Stephen R.
N1 - Publisher Copyright:
©2015 by the Midwest Political Science Association 59 2 April 2015 10.1111/ajps.12148 ARTICLE AJPS WORKSHOP ©2014, Midwest Political Science Association.
PY - 2015/4/1
Y1 - 2015/4/1
N2 - Roll-call votes are widely employed to infer the ideological proclivities of legislators. However, many roll-call matrices are characterized by high levels of nonresponse. Under many circumstances, nonresponse cannot be assumed to be ignorable. We examine the consequences of violating the ignorability assumption that underlies current methods of roll-call analysis. We present a basic estimation framework to model nonresponse and vote choice concurrently, build a model that captures the logic of competing principals that underlies accounts of nonresponse in many legislatures, and illustrate the payoff of addressing nonignorable nonresponse through both simulated and real data. We conclude that modeling presumed patterns of nonignorable nonresponse can yield important inferential payoffs over current models that assume random missingness, but we also emphasize that the decision to model nonresponse should be based on theoretical grounds since one cannot rely on measures of goodness of fit for the purpose of model comparison.
AB - Roll-call votes are widely employed to infer the ideological proclivities of legislators. However, many roll-call matrices are characterized by high levels of nonresponse. Under many circumstances, nonresponse cannot be assumed to be ignorable. We examine the consequences of violating the ignorability assumption that underlies current methods of roll-call analysis. We present a basic estimation framework to model nonresponse and vote choice concurrently, build a model that captures the logic of competing principals that underlies accounts of nonresponse in many legislatures, and illustrate the payoff of addressing nonignorable nonresponse through both simulated and real data. We conclude that modeling presumed patterns of nonignorable nonresponse can yield important inferential payoffs over current models that assume random missingness, but we also emphasize that the decision to model nonresponse should be based on theoretical grounds since one cannot rely on measures of goodness of fit for the purpose of model comparison.
UR - http://www.scopus.com/inward/record.url?scp=85027918554&partnerID=8YFLogxK
U2 - 10.1111/ajps.12148
DO - 10.1111/ajps.12148
M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???
AN - SCOPUS:85027918554
SN - 0092-5853
VL - 59
SP - 511
EP - 528
JO - American Journal of Political Science
JF - American Journal of Political Science
IS - 2
ER -