Over the past decades there has been an increasing use of panel surveys at the household or individual level, instead of using independent cross-sections. Panel data have important advantages, but there are also two potential drawbacks: attrition bias and panel conditioning effects. Attrition bias can arise if respondents drop out of the panel non-randomly, i.e., when attrition is correlated to a variable of interest. Panel conditioning arises if responses in one wave are in°uenced by participation in the previous wave(s). The experience of the previous interview(s) may affect the answers of respondents in a next interview on the same topic, such that their answers differ systematically from the answers of individuals who are interviewed for the first time. The literature has mainly focused on estimating attrition bias; less is known on panel conditioning effects. In this study we discuss how to disentangle the total bias in panel surveys due to attrition and panel conditioning into a panel conditioning and an attrition effect, and develop a test for panel conditioning allowing for non-random attrition. First, we consider a fully nonparametric approach without any assumptions other than those on the sample design, leading to interval identification of the measures for the attrition and panel conditioning effect. Second, we analyze the proposed measures under additional assumptions concerning the attrition process, making it possible to obtain point estimates and standard errors for both the attrition bias and the panel conditioning effect. We illustrate our method on a variety of questions from two-wave surveys conducted in a Dutch household panel. We found a significant bias due to panel conditioning in knowledge questions, but not in other types of questions. The examples show that the bounds can be informative if the attrition rate is not too high. Point estimates of the panel conditioning effect do not vary a lot with the different assumptions on the attrition process.