A flexible test for early-stage studies with multiple endpoints.

This paper builds on the recently proposed prediction test for muliple endpoints. The prediction test combines information across multiple endpoints while accounting for the correlation between them. The test performs well with small samples relative to the number of endpoints of interest and is flexible in the hypotheses across the individual endpoints that can be combined. The prediction test addresses a global hypothesis that is of particular interest in early-stage studies and can be used as justification for continuing on to a larger trial. However, the prediction test has several limitations which we seek to address. First, the prediction test is overly conservative when both the effect sizes across all endpoints and the number of endpoints are small. By using a parametric bootstrap to estimate the null distribution, we show that the test achieves the nominal error rate in this situation and increases the power of the test. Second, we provide a framework to allow for predictions of a difference on one or more endpoints. Finally, we extend the test with a composite null hypothesis that allows for different null hypothesized predictive abilities across the endpoints which can be especially useful if the study contains both familiar and novel endpoints. We use an example from a physical activity trial to illustrate these extensions.

Evaluating Paired Categorical Data when the Pairing is Lost.

We encountered a problem in which a study's experimental design called for the use of paired data, but the pairing between subjects had been lost during the data collection procedure. Thus we were presented with a data set consisting of pre and post responses but with no way of determining the dependencies between our observed pre and post values. The aim of the study was to assess whether an intervention called Self-Revelatory Performance had an impact on participant's perceptions of Alzheimer's disease. The participant's responses were measured on an Affect grid before the intervention and on a separate grid after. To address the underlying question in light of the lost pairing we utilized a modified bootstrap approach to create a null hypothesized distribution for our test statistic, which was the distance between the two Affect Grids' Centers of Mass. Using this approach we were able to reject our null hypothesis and conclude that there was evidence the intervention influenced perceptions about the disease.

Variant of congenital dyserythropoietic anemia.

Nonspherocytic hemolytic anemia was diagnosed in a 34-year-old man with jaundice since childhood. Splenectomy at the age of 8 had no influence on the anemia. Bronze diabetes was diagnosed at age 31, presumably due to hemosiderosis and secondary hemochromatosis. Iron chelation was unsuccessful in controlling iron overload, but phlebotomies proved effective without aggravating the anemia. We believe the anemia represents a variant of congenital dyserythropoietic anemia, type I.