Survey breakoff – when respondents discontinue their participation before completing the questionnaire – has attracted a growing amount of interest and attention (see, e.g., Peytchev 2009). The increased interest in breakoff involving Internet survey respondents has been accelerated by the relatively recent availability of paradata collection methods for Web surveys. In addition to respondent and survey design characteristics, it is now relatively easy to obtain data such as the amount of time taken per survey item (response latency), number of response changes to questions, time of day when the survey breakoff occurs, as well as a number of other factors that can be evaluated as contributors to survey breakoff. The proposed study examines data from monthly waves of the Internet component of the Gallup Panel, a multi-mode (mail and Web) panel of American households. In addition to standard demographic respondent characteristics and survey design factors (e.g., question complexity, topic, number of questions on the page, length of survey), the analysis will include a variety of respondent self-reports on Internet sophistication and survey design factors and paradata to explore factors related to survey breakoff. Preliminary analysis indicates that while long-term panel members are less likely to breakoff, that there appears to be a clear and persistent pattern with respect to response latency; as respondents approach breaking off their survey participation, they tend to slow down in their response time (increase response latency). The study will explore the potential use of such predictive models for survey breakoff in designing possible responsive/adaptive design (Groves and Heeringa 2006) interventions for Internet surveys that may prove useful in averting, or delaying, Internet survey breakoff.