The purpose of this study was to examine primary appraisal of sexual harassment, that is, a victim's cognitive evaluation of the harassment and the factors that influence this appraisal. The perspectives of 72 female plaintiffs were investigated by measuring their primary appraisal of the event, examining the structure of this appraisal, and…

It is a false, but common, belief that statistical significance testing evaluates result replicability. In truth, statistical significance testing reveals nothing about results replicability. Since science is based on replication of results, methods that assess replicability are important. This is particularly true when multivariate methods, which…

The redundancy statistic (Rd) is discussed in relation to canonical correlation analysis. The index is a measure of the variance of one set of variables predicted from the linear combination of the other set of variables. A small data set (N=6) from the work of D. Clark (1975) was analyzed using SPSS-X. Two sets of two variables each were…

This paper suggests that multivariate analysis techniques are very important in educational research, and that one multivariate technique--canonical correlation analysis--may be particularly useful. The logic of canonical analysis is explained. It is suggested that a backward variable elimination strategy can make the method even more powerful, by…

All parametric methods are special cases of canonical correlation analysis and can, in fact, be performed using the canonical correlation procedures found in commonly available computer statistics packages such as the Statistical Analysis System (SAS) software. It is suggested that canonical analysis has advantages of versatility since it can…

Planned comparisons have been known for several years. Due to the availability of computers, these comparisons have become a more viable alternative to post hoc testing. There are several different types of planned comparisons that can be performed. Research goals must be well thought out when using planned comparisons, since the appropriate…

Canonical correlation (CC) analysis is discussed with a view toward providing an intuitive understanding of how the technique operates. CC analysis entails calculation of one or more sets of canonical variate coefficients (CVC), i.e., weights which can be applied to the variables in a study. A canonical function (CF) always consists of exactly two…

Designed to provide comparative analyses which could be employed as a basis for judicious program selection and use of generally available canonical correlation computer programs. (RC)

Describes how the test statistic for nonparametric one-way multivariate analysis of variance can be obtained by submitting the data to a packaged computer program. Monte Carlo evidence indicates that the nonparametric approach is advantageous under certain violations of the assumptions of multinormality and homogeneity of covariance matrices.…

When selection occurs on the basis of two or more predictors, multivariate restriction of range can reduce various parameters of a validation study. A Statistical Analysis System (SAS) and a Fortran IV program are described that allow for correction of criterion standard deviation(s) and zero-order validities. (Author)

This paper presents three variable deletion strategies in canonical correlation analysis. All three strategies are illustrated by examples. The first strategy uses the canonical communality (h2) coefficients of the three functions to decide which variable to delete. The second function also uses the canonical communality coefficients, but only…

The stabilities of standardized (ß) and structure (rs) coefficients in canonical (CA) and discriminant analyses (DA) were studied. Four different situations were studied--two pertaining to CA and two to DA. The situations were meant to represent "somewhat typical" and yet varying research conditions that often would not be thought to be…

Data are often a continuous function of a variable such as time observed over some interval. One or more such functions might be observed for each subject. The extension of classical data analytic techniques to such functions is discussed. (Author/JKS)