A major obstacle to developing evidenced-based policy is the difficulty of implementing randomized experiments to answer all causal questions of interest. When using a nonexperimental study, it is critical to assess how much the results could be affected by unmeasured confounding. We present a set of graphical and numeric tools to explore the…

The paper discusses the consequences for maximum likelihood factor analysis which may follow if the observed variables are ordinal with only a few scale steps. Results indicate that classification may lead to a substantial lack of fit of the model--an erroneous indication that more factors are needed. (Author/CTM)