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This theoretical note describes an expansion of the behavioral prediction equation, in line with the greater complexity encountered in models of structured learning theory (R. B. Cattell, 1996a). This presents learning theory with a vector substitute for the simpler scalar quantities by which traditional Pavlovian-Skinnerian models have hitherto been represented. Structured learning can be demonstrated by vector changes across a range of intrapersonal psychological variables (ability, personality, motivation, and state constructs). Its use with motivational dynamic trait measures (R. B. Cattell, 1985) should reveal new theoretical possibilities for scientifically monitoring change processes (dynamic calculus model: R. B. Cattell, 1996b), such as encountered within psychotherapeutic settings (R. B. Cattell, 1987). The enhanced behavioral prediction equation suggests that static conceptualizations of personality structure such as the Big Five model are less than optimal.

Some problems of multiple group factor rotation based on Cattell's "parallel proportional profiles" and "confactor rotation" are described (see Cattell, 1944, 1966, 1972). Some relations between these classic ideas and contemporary practices in structural equation modeling (e.g., LISREL) are explored. We show how the Confactor approach: (a) is related to Meredith's (1964a) selection model, (b) can be a parsimonious model for multiple group factor analyses, and (c) how this model can be fitted using standard structural equation modeling techniques. We discuss several alternative structural modeling solutions, including (d) selection of a good reference variable solution, (e) rotation of the invariant orthogonal structure by standard rotation routines, and (f) higher-order, latent paths, and latent means structural model restrictions. Mathematical and statistical properties of these models are examined using Meredith's (1964b) four group problem fitted by Jdreskog and Sdrbom's (1979, 1985) LlSREL algorithm. The benefits and limitations of this structural modeling approach to oblique Confactor resolution are examined and opportunities for future research are discussed.

The growth of validated objective devices, and of knowledge of ergic and sentiment structure has now, for 20 years, put new instruments (MAT and SMAT) in the hands of psychological practitioners. They have been slow to recognize, however, the theoretical powers in conflict measurement, decision theory, the general dynamic calculus, and structured learning theory which this has brought about. Illustration is given here of the experimental and clinical gains, with a view to the growth of several areas inaccessible to bivariate experiment.

This paper describes the inception of a scientific movement (the Society of Multivariate Experimental Psychology); the individuals who begot it; the two journals and numerous scientific articles which resulted; its effects in stimulating new areas of teaching and of theoretical development; and its international reception as well as its successes and failures in stimulating the creation of satellite societies on the same pattern.

Basing hypotheses on interpretations of 12 personality factors most replicated in 10 past researches with children, this experiment sets up about eight subtests as specific markers for each. Ninety-five tests, taking eight hours in all, were administered to 394 14-16-year olds. A majority of the personality pattern hypotheses were sustained factor analytically by evidence on number of factors, significance of unique simple structure reached, and goodness of identifying match (chi-square test). Concept validities can be obtained for some six of the factors rivalling those for intelligence tests. A brief discussion is given of the bearing of the present results upon theoretical explanations of the given source traits, including extraversion, and it is pointed out that the psychological meaning of most, for personality research, is as important, in variance terms, as for the one or two, such as anxiety and extraversion, which have tended to monopolize discussion.

Tested over 3,000 boys (identical and fraternal twins, ordinary sibs, general population) aged 12-18 on Ego Strength, Super Ego Strength, and Self Sentiment. The Multiple Abstract Variance Analysis (MAVA) method was used to obtain estimates of abstract (hereditary, environmental) variances and covariances that contribute to total variation in the three traits. Within-family heritabilities for these traits were about .30, .05, and .65. Between-family heritabilities were .60, .08, and .45. Within-family correlations of genetic and environmental deviations were trivial, unusually so among personality variables, but between-family values showed the usual high negative values, consistent with the law of coercion to the biosocial mean.

The person-centered environmental representation (PCER) model aims to bring extra-personality determiners of behavior measures (stimulus, response form, situation, observer) as known values into the behavioral equations. Illustration begins with the simplest 3-dimensional data box case -- person, test, situation -- in which the response score is a product of the characteristic trait score of the individual and the characteristic interaction of that trait with that kind of performance. In extending this to a particular kind of situation it is recognized that a test-situation interaction term must, realistically, be added. The problem in experiment is to infer the magnitude of the contributors from the 3-sums in the cells of the empirically given data box frame. Three ways of attempting this are described and the third, judged most practical, is illustrated in a plasmode of data typical of experiment. It is shown that the discovery from the frame data of the factor structure, originally put into the contributory test and situation matrices is reasonably good, and it is pointed out that since this can be achieved with only 10 situations, 12 tests and 14 people, the smoothing effect of more typical large samples makes the method practicable. If further research with real data confirms the speculation that the personality factors determining situation reaction are the same as those determining test reaction, a split loading model could be used permitting, as a by-product, assessment of relative variance contributions of differences among persons, stimuli, response forms, and observers.

Korth (1978) does well to describe factor matching as vital to personality research but seriously underestimates the extent of successful matching both within and between cultures. His evaluation of matching of a set of factors is an advance, but the achievement of "diagonalization" of r[SUBc] coefficients in a matching matrix probably has a higher significance than his method would indicate. Regarding Monte Carlo determinations of r[SUBc] distributions, the writer maintains that treating loadings as random normal deviates is incorrect and that a special distribution (here presented) is required. Further, it is argued that "factor invariance," as commonly defined, is not the required proof of identify of determiners. Instead, the principles of real base factor analysis need to be applied to demonstrate degree of matching of determiners. A numerical illustration shows that when congruence is actually perfect for the real base factor patterns, it is not so for ordinary factor analysis patterns. Even in this framework the congruence, coefficient has weaknesses, and it is suggested that decisions be based on the joint outcome of r[SUBc] and 8, the salient variable similarity index.

Describe four personality factors with preliminary indications of distinguishing depressed patients from normals, namely those indexed in the O-A Kit as U.I. 19, U.I. 20, U.I. 25 and U.I. 30. Thirty-one clinically depressed Ss--22 inpatients and 9 outpatients--were administered the O-A (Objective-Analytic) battery for these four and the scores compared with those of 30 demographically matched controls. From earlier research and the general psychological theory that concerned these source traits it was hypothesized that depressed Ss would deviate negatively on U.I. 19 and U.I. 25 and positively on U.I. 20 and U.I. 30. A comparison of means that used a one-tailed t-test showed significant differences on two of the factors, U.I. 19 and U.I. 20, at p less than level of significance, and on U.I. 25 and U.I. 30 at p less than .05 significance level. Thus, the clinical sample showed the hypothesized directions of divergence from the control sample on all four of the factors. Later use of a discriminant function on this pattern of deviations shows a high degree of patient-control separation (Price, Cattell, & Patrick, Note 1).

Attribution theory is in need of a multivariate model to handle its problems. A model for handling the causes of perceptual difference (misperception) in estimating traits in people already exists in trait view theory. A natural extension of this model will cover the remaining half of attribution research: that concerned with perception of the causal action of situations. The model, integrating both, is a subsumption of the psychology of perception under the general behavioral equation. Spectrad theory is so named because it combines a tetrad of spectra (vectors) for (1) the contextual action of (a) the traits, and (b) the situation of the perceived person or situation and (2) the construing action of (a) the traits and (b) the situation of the perceiver. All four enter into predicting the deviation of a perception from the true value (operationally defined) of (a) a trait score, and (b) the behavioral indices by which the meaning and causal action of a situation are expressed.

1,768 12- to 18-year-old boys, in pairs from five constellations (identical and fraternal twins, brothers, unrelated boys raised together and a random general population sample) were measured by the O-A (performance) personality battery on source traits UI 16, 17 and 19. Corrections were made for ages and test validities in computing observed variances. Nine equations were set up in the multiple abstract variance (MAVA) model giving expectancies from seven unknown abstract variances (genetic, threptic, and genothreptic covariances) with respect to observed variances. Maximum likelihood analysis showed that genetic or threptic contribution alone was unable to fit the data, and the best fit was given by a parsimonious form of MAVA dropping genothreptic correlations. Population heritabilities calculated on this basis were 0.46 for UI 16 (ego assertion), 0.21 for UI 17 (control, upbringing), and 0.50 for UI 19 (independence). When compared with an earlier study by the O-A, but by a different analysis, and with the same data analyzed by tho other methods, a reasonably consistent conclusion emerges that UI 17 is little inherited, while UI 16 and UI 19 are rather strongly inherited. The contribution of the behavior-genetic evidence to the theories about these source traits is discussed. It is concluded that UI 16 is initially in development a temperament factor, probably with physiological associations in metabolic rate, etc.; that UI 19 is a strong and sex-related temperament factor, and that UI 17 is a sentiment pattern of cultured inhibition almost wholly dependent on family and social upbringing.

In most well designed researches larger substantive factors show a break in size from those of a trivial lower degree of variance, which are due to error and other sources. The only short test for the number of such factors that has been repeatedly supported by plasmode results is the scree. The present experiment extends this empirical testing of the scree by taking 15 plasmodes, which vary in (1) number of variables, (2) of factors, (3) degree of obliquity, from orthogonal cases on, (4) presence of simple structure, (5) presence of error, extending to factoring random numbers, and (6) size of communality. The results support the scree and show it superior to the Kaiser-Guttman unity root criterion. Apart from the scree itself, a brief examination is made of the reliability of its use in the hands of trained and untrained judges. A second evaluation of the intrinsic validity of the scree is made by examining internal consistency of item and parcel factoring, of different sampling of variables and of change of population. The result again supports its capacity to locate the correct number of factors within narrow limits.

issues related to the decision of the number of factors to retain in factor analysis are identified, and three widely-used decision rules -- the Kaiser-Guttman, scree, and likelihood ratio tests -- are isolated for empirical study. Using two differing structural models and incorporating a number of relevant independent variables (such as number of variables, ratio of number of factors to number of variables, variable communality levels, and factorial complexity), the authors simulated 144 population data sets and, then, from these, 288 sample data sets, each with a precisely known (or incorporated) number of factors. The Kaiser-Guttman and scree rules were applied to the population data in Part I of the study, and all three rules were applied to the sample data sets in Part II. Overall trends and interactive results, in terms of the independent variables examined, are discussed in detail, and methods are presented for assessing the quality of the number-of-factors indicated by a particular rule.

A Series of questionnaire items designed to measure the psychological states of anxiety, depression, effort stress and fatigue were administered to 151 male and female subjects and then readministered, one month later, to the same subjects. Difference scores, some based on individual items and some on item parcels, were intercorrelated and factor analyzed. The factor analytic investigation was carried through a third order analysis. Results support the notion that change score patterns are of substantial dimensionality and that the hypothesized dimensions can be identified on the basis of the included marker variables. Implications and future directions for research on the validity of the trait-state distinction are briefly discussed.