Understanding the possible pitfalls of survey data is critical for empirical research. Among other things, poor data quality can lead to biased regression estimates, potentially resulting in incorrect interpretations that mislead researchers and policymakers alike. Common data problems include difficulties in tracking respondents and high survey attrition, enumerator error and bias, and respondent reporting error. This paper describes and analyzes these issues in Round 1 of the Kenyan Life Panel Survey (KLPS-1), collected in 2003-2005. The KLPS-1 is an innovative longitudinal dataset documenting a wide range of outcomes for Kenyan youths who had originally attended schools participating in a deworming treatment program starting in 1998. The careful design of this survey allows for examination of an array of data quality issues.