This paper presents a non-parametric imputation technique, named random forest, from the machine learning field. The random forest procedure has two main tuning parameters: the number of trees grown in the prediction and the number of predictors used. Fifty experimental conditions were created in the imputation procedure, with different…

The asymptotic power of the Cramer-von Mises test when parameters are estimated from the data is studied under certain local (contiguous) alternatives. Notion of (asymptotic) direction and distance from the null hypothesis of alternatives is introduced, and it is shown that there exist directions with maximum, minimum, and arbitrary intermediate…

A class of naive estimators of correlation was tested for robustness, accuracy, and efficiency against Pearson's r, Tukey's r, and Spearman's r. It was found that this class of estimators seems to be superior, being less affected by outliers, reasonably efficient, and frequently more easily calculated. (Author/CTM)

This paper presents an index of goodness-of-fit for comparing m models over n trials. The index allows for differentiated weighting of the trials as to their importance in the comparison of the models. Several possible weighting schemes are suggested and the conditions on the weights which assure asymptotic normality of the index distribution are…

The Chi-Square Test for Hierarchical Dependency (THD) is presented. The THD tests the hypothesis that all members of a population who possess a certain skill are a subset of the members who possess another skill. This hypothesis is basic to the writings of several prominent theorists, such as Gagne and Piaget. The THD is designed as an improvement…

A computer program named Program STANDARD is presented and demonstrated. This program calculates the statistical significance of the overall agreement of the categorical assignments. The program is based on Light's statistic, G, for describing the conjoint agreement of many observers with correct or standard set of classifications on nominal…

A Monte Carlo technique was used to investigate the small sample goodness of fit and statistical power of several nonparametric tests and their parametric analogues when applied to data which violate parametric assumptions. The motivation was to facilitate choice among three designs, simple random assignment with and without a concomitant variable…

When repeated measures are obtained on the same subjects, interobservation dependencies frequently are generated. The major ways in which these dependencies can arise are illustrated and it is shown how these dependencies may invalidate the use of analysis of variance (ANOVA) and its extension, trend analysis, as methods of evaluating the data of…