Low literacy is often cited as one factor that might contribute to measurement error in self-administered surveys. Most studies that attempt to examine the link between literacy and data quality rely on education as a proxy for literacy, but measures such as years of education do not account for variation in the quality of education that might ultimately impact literacy. Education is correlated with literacy, but tends to overestimate it considerably. Few surveys have examined the effect of literacy itself, but with many surveyors switching from telephone to self-administered mail or web surveys, understanding how literacy impacts data quality (above and beyond education) is increasingly important. In this paper we examine how literacy affects measures of data quality such as item nonresponse rates, execution of skip instructions, and valid responses to text and number box open-ended questions. We also examine how experimental variations in questionnaire design affect the quality of responses across literacy groups. In particular, we focus on experiments that manipulate how much text versus visual information has to be processed such as how skip instructions are designed, how answer boxes are sized and labeled, how grids are labeled, and the types of definitions that accompany questions. The data for this paper come from the 2009 Quality of life in a Changing Nebraska survey (n=565, AAPOR RR2 = 46%). As an example, preliminary results indicate that, as we would expect, those with lower literacy provide shorter responses with less information to open-ended questions, even when education is controlled. Results both shed light on the link between literacy and data quality and provide insight into questionnaire design features that may improve data quality among low literacy populations.