Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Lam looks at population and development in next 15 years in UN commission keynote address

Mitchell et al. find harsh family environments may magnify disadvantage via impact on 'genetic architecture'

Frey says Arizona's political paradoxes explained in part by demography

Highlights

NIH announces new policy for resubmissions (4/17/14)

2014 PAA Annual Meeting, May 1-3, Boston

PSC newsletter spring 2014 issue now available

Raghunathan appointed director of Survey Research Center

Next Brown Bag


PSC Brown Bags will return in the fall

Yu Xie photo

Values and limitations of statistical models

Publication Abstract

Xie, Yu. 2011. "Values and limitations of statistical models." Research in Social Stratification and Mobility, 29(3): 343-349.

Methodological consequences of population heterogeneity for the sequential logit model in studies of education transitions are now well understood. There are two main mechanisms by which heterogeneity may cause biases to parameter estimates in sequential logit models: outcome incommensurability and population incommensurability. These methodological problems are intrinsic to the substantive research question and thus are not easily remediable with better statistical models. All statistical solutions require extra information in the form of additional data or additional assumptions. In some settings, the researcher may explicitly introduce a form of heterogeneity into the sequential logit model and then evaluate the model. In other settings, the researcher may wish to stay with the conventional sequential logit model and interpret the results descriptively.

DOI:10.1016/j.rssm.2011.04.001 (Full Text)

PMCID: PMC3203205. (Pub Med Central)

Browse | Search : All Pubs | Next