Publication Type: Paper/Poster ProposalAbstract: The increasing uncertainty of the US publics reaction to survey requests has led to heightened awareness of the interplay of costs, nonresponse rates, and nonresponse errors in large scale household surveys. Groves and Heeringa (2004) outline an approach to survey design that directs orderly changes to key features of the recruitment protocol of a survey, based on real-time analysis of the incoming survey data. These so-called responsive designs identify a set of alternative key statistics, callback alternatives, and incentive options prior to the start of the data collection. Cost and error-related models are measured during the early phases of a survey, and then used to determine final design features, more nearly cost-optimal. In short, these designs adapt or respond to real-time information about the performance of the survey. A key tool in this responsive process is the use of propensity models on the sample case level, estimating the probability that an active case will be interviewed.
Propensity models are also used after the survey data collection period has been completed. These propensity models are often used to form weighting class adjustments in an attempt to reduce unit nonresponse error (Little, 1982). These models identify groups that have higher or lower likelihood of being measured, based on all knowledge available at the end of the data collection.
This paper addresses whether the predictors of propensity during data collection heavily overlap those available at the end of the data collection period. It relates this analysis to efforts during the data collection to attempt to achieve the most cost efficient acquisition of completed cases. It then studies how the estimated propensities of cases correlate with key statistics in the survey, among respondents. Conclusions are drawn about the relative utility of observational and process data predictors for response propensity in adjustment models.
Publication Type: Roundtable PaperAbstract: The purpose of this study is to examine the North Korean defectors’ fear of crime with 4 theoretical models: sub-cultural diversity model, community policing model, vulnerability model, and victimization model. This study utilizes survey data collected from 214 North Korean defectors who are over 20 years old living in South Korea. Two types of fear of crime, i.e., general and specific measures, are tested. Research findings show that perceived risk of victimization is a significant factor in both measures of fear of crime. That is, defectors who perceive higher risk of victimization show higher level of fear of crime. In addition, when general measure of fear of crime is tested, gender and victimization experiences are turned out to be significant factors. Women defectors’ fear of crime is higher than that of men’s; and unexpectedly, defectors who experienced victimization show lower level of fear of crime.
On the other hand, when specific measure of fear of crime is tested, findings show that difficulties in cultural adjustment is another significant factor. Defectors who experience cultural difficulties in South Korea show higher level of fear of crime. Research findings are interpreted and discussed from the theoretical perspectives.
Publication Type: Conference Paper/Unpublished ManuscriptAbstract: This study is a theoretical review about message discrepancy and a proposal of a new model of message discrepancy. This study analyzed four mathematical models of message discrepancy (Anderson & Hovland, 1957; Fink, Kaplowitz, & Bauer, 1983; Fishbein & Ajzen,1975; Laroche, 1977). A new mathematical model was proposed by solving a differential equation that derived from on a biological metaphor and existing models. A new model predicts a monotonically increasing function of message discrepancy.
Publication Type: Conference Paper/Unpublished ManuscriptAbstract: The combination of the emergence of a set of serious global-scale challenges such as climate change, biodiversity loss, and fisheries depletion, and the very real problem that solutions to address one challenge can cause problems in another arena such as
Publication Type: AbstractReview Method: Peer ReviewedAbstract: Investigation of comments, via latent semantic analysis (LSA), show the attitudes toward public transportation from users extend beyond what is prevalent in extant literature and validates the expansion of the current decision-making framework. Subsequent data collection and analysis validates the functionality of LSA for both exploratory and confirmatory model development.