Often, the classification of words does not go beyond "difficult" (i.e., infrequent, late-learned, nonimageable, etc.) or "easy" (i.e., frequent, early-learned, imageable, etc.) words. In the present study, we used a latent cluster analysis to divide 703 Dutch words with scores for eight word properties into seven clusters of words. Each cluster…

Using Functional Measurement (Anderson, 2008), Frileux, Lelievre, Munoz Sastre, Mullet, and Sorum (2003) examined the joint impact of several key factors on lay people's judgments of the acceptability of physicians' interventions to end patients' lives. The level of acceptability was high, and the information integration rule that best described…

India has witnessed a major expansion in participation in basic education in recent years, in the context of a major programme for its promotion: Sarva Shiksha Abhiyan (SSA). Despite a significantly improved picture at the basic level, a considerable proportion of children continue to drop out before reaching the secondary level. Over half of…

Describes the appropriate control of experiment-wise error rates and the researcher's role in making decisions to control for Type 1 errors. Issues related to level of significance, one- versus two-tailed tests, and the use of multivariate statistics are included. (Author/CT)

Cluster analysis has a rich history in many disciplines and although cluster analysis has been used in clinical psychology to identify types of disorders, its use in other areas of psychology has been less popular. The purpose of the current experiments was to use cluster analysis to investigate husband-wife decision making. Cluster analysis was…

This study explored a career readiness typology of 629 8th-grade students using the Career Factors Inventory. Data revealed developmentally appropriate elevated needs for information, specifically self-knowledge. In addition, cluster analysis demonstrated the heterogeneity of career development needs of 8th-grade students. Typal membership…

A method is presented for determining the optimal number of conditions to use in multivariate-multifacet generalizability designs when resource constraints are imposed. A decision maker can determine the number of observations needed to obtain the largest possible generalizability coefficient. The procedure easily applies to the univariate case.…

Choosing the most appropriate method to handle missing data during analyses is one of the most challenging decisions confronting researchers. Often, missing values are just ignored rather than replaced with a reliable imputation method. Six methods of data imputation were used to replace missing data from two data sets of varying sizes; this…

Two case studies, a study of retention of health care personnel and a study of internal organizational communication, are presented that illustrate the application of multidimensional unfolding (MDU) and mapping to organizational concerns. This approach to multivariate analysis allows clients and stakeholders to picture the results of complex…

Making decisions about residential or day program placement for adults with developmental disabilities requires examination of multidimensional measures of behavior and thus the use of multivariate statistical techniques along with expert opinion. This study used adaptive and maladaptive cluster scores on the Inventory for Client and Agency…

Although methodological integrity is not the sole determinant of the value of a program evaluation, decision-makers do have a right, at a minimum, to be able to expect competent work from evaluators. This paper explores five areas where evaluators might improve methodological practices. First, evaluation reports should reflect the limited…