When credible evidence indicates potential bias in measurement (i.e., lack of consistent construct meaning across groups, DIF, DTF) or bias in predictive relations, these potential sources of bias should be independently investigated because the presence or absence of one form of such bias may have no relationship with other forms of bias. For example, a predictor test may show no significant levels of DIF, yet show group differences in regression lines in predicting a criterion. Although it is important to guard against the possibility of measurement bias for the subgroups that have been defined as relevant in the intended test population, it may not be feasible to fully investigate all possibilities, particularly in the employment context. For example, the number of subgroup members in the field test or norming population may limit the possibility of standard empirical analyses. In these cases, previous research, a construct-based rationale, and/or data from similar tests may address concerns related to potential bias in measurement. In addition, and especially where credible evidence of potential bias exists, small sample methodologies should be considered. For example, potential bias for relevant subgroups may be examined through small-scale tryouts that use cognitive labs and/or interviews or focus groups to solicit evidence on the validity of interpretations made from the test scores.