Quantitative researchers use randomization to treatment or model the selection process so as to identify causal effects (Shadish, Cook, & Campbell, 2002); however, qualitative researchers sample in a “deliberate”and “purposeful”manner and samples are selected to “provide”the information needed to address the research questions (Maxwell, 1996). I examined whether this qualitative approach leads to valid findings, given that (a) restrictive sampling might prompt researchers to find associations between variables in ways that are intuitively appealing (based on selective sampling experience), and (b) with selective samples (or “sampling”on the dependent variable) it is impossible to determine associations. However, even though sampling units from restrictive samples share certain characteristics, this occurrence does not mean that these characteristics predict the dependent variable (Denrell, 2003). In two experiments (n= 396) I provided participants with cases describing individual managers and their performance (using both qualitative and quantitative information). I systematically varied two characteristics of the managers in tandem with their performance and also described the managers on 19 other characteristics that were not correlated with the dependent variables in the population. I then randomly assigned subjects in 1 of 10 groups, varying the number of cases and the representativeness of the cases with respect to the dependent variable. I theorized that only subjects given representative or random cases could recover the associations in the data (i.e., which characteristic predict performance). Planned contrasts indicated that subjects who received representative or randomly samples generally performed best. These results indicate that qualitative researchers must exercise extreme caution when selecting sampling units; if they do not exhibit a high degree of variance in the dependent variable then the validity of conclusions that are drawn may be severely compromised. References: Denrell, J. (2003). Vicarious learning, undersampling of failure, and the myths of management. Organization Science, 14(3), 227-243. Maxwell, J. A. (1996). Qualitative research design: An integrative approach. Thousand Oaks, CA: Sage Publications. Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Boston: Houghton Mifflin.