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A general linear model was described for tests constructed in a facet design. Guilford's structure of intellect model and an alternative model were specified as special cases. From the Guilford research seven data sets were selected such that both models could be compared. The comparison was done with oblique and orthogonal factors. Using covariance structure analysis the fit of the models was assessed, and the parameters estimated. Models with orthogonal factors did not fit the data. The fit of the oblique Guilford model was better than the alternative oblique model. For three of the data sets the oblique Guilford model yielded an acceptable fit to the data with parameter estimates that could be interpreted by the structure of intellect model. [ABSTRACT FROM AUTHOR]

In using tests of statistical significance, the null hypothesis will almost certainly be rejected if there is a large number of subjects. This statement also applies to the testing of hypotheses about covariance matrices. The problem can be solved within a decision theoretic framework of hypothesis testing using Monte Carlo procedures. The covariance structure of theoretical interest is specified in the alternative hypothesis, while the null hypothesis is identical in all secondary aspects to the alternative hypothesis but differs clearly from the alternative hypothesis in primary theoretical aspects. Using reasonable values for the parameters in both hypotheses, the relations between the number of subjects, the significance level, and the power of the test are studied with simulated data. From the Monte Carlo study an optimal and feasible combination of number of subjects, significance level, and power is determined for the empirical study. The procedure is demonstrated in detail with an example from the measurement of musical abilities. It is emphasized that the power of the test for the actual data should be investigated again in a simulation study, especially if the data differ in important ways from the planning of the experiment. [ABSTRACT FROM AUTHOR]

The Rasch model is formulated as a loglinear model. The goodness of fit and parameter estimates of the Rasch model can be obtained using the itera tive proportional fitting algorithm for loglinear models. It is shown in an example that the relation between the estimates of the iterative proportional fitting algorithm and the unconditional maximum likelihood Rasch algorithm are almost perfectly lin ear. The Rasch model can be extended with a de sign for the items, which can be formulated as a loglinear model. [ABSTRACT FROM PUBLISHER]

In applied measurement, test scores are usually transformed to decisions. Analogous to classical test theory, the reliability of decisions has been de fined as the consistency of decisions on a test and a retest or on two parallel tests. Coefficient kappa (Cohen, 1960) is used for assessing the consistency of decisions. This coefficient has been developed for assessing agreement between nominal scales. It is argued that the coefficient is not suited for as sessing consistency of decisions. Moreover, it is ar gued that the concept consistency of decisions is not appropriate for assessing the quality of a decision procedure. It is proposed that the concept con sistency of decisions be replaced by the concept optimality of the decision procedure. Two types of optimality are distinguished. The internal optimal ity is the risk of the decision procedure with respect to the true score the test is measuring. The external optimality is the risk of the decision procedure with respect to an external criterion. For assessing the optimality of a decision procedure, coefficient delta (van der Linden & Mellenbergh, 1978), which can be considered a standardization of the Bayes risk or expected loss, can be used. Two loss functions are dealt with: the threshold and the linear loss func tions. Assuming psychometric theory, coefficient delta for internal optimality can be computed from empirical data for both the threshold and the linear loss functions. The computation of coefficient delta for external optimality needs no assumption of psy chometric theory. For six tests coefficient delta as an index for internal optimality is computed for both loss functions; the results are compared with coefficient kappa for assessing the consistency of decisions with the same tests. [ABSTRACT FROM PUBLISHER]

From a decision theoretic point of view a general coefficient for tests, d, is derived. The coefficient is applied to three kinds of decision situations. First, the situation is considered in which a true score is estimated by a function of the observed score of a subject on a test (point estimation). Using the squared error loss function and Kelley's formula for estimating the true score, it is shown that d equals the reliability coefficient from classical test theory. Second, the situation is considered in which the ob served scores are split into more than two cate gories and different decisions are made for the categories (multiple decision). The general form of the coefficient is derived, and two loss functions suited to multiple decision situations are described. It is shown that for the loss function specifying con stant losses for the various combinations of cate gories on the true and on the observed scores, the coefficient can be computed under the assumptions of the beta-binomial model. Third, the situation is considered in which the observed scores are split into only two categories and different decisions are made for each category (dichotomous decisions). Using a loss function that specifies constant losses for combinations of categories on the true and ob served score and the assumption of an increasing regression function of t on x, it is shown that coeffi cient d equals Loevinger's coefficient H between true and observed scores. The coefficient can be com puted under the assumption of the beta-binomial model. Finally, it is shown that for a linear loss function and Kelley's formula for the regression of the true score on the observed score, the coefficient equals the reliability coefficient of classical test theory. [ABSTRACT FROM PUBLISHER]

The situation is considered in which a total score on a test is used for classifying examinees into two categories: "accepted (with scores above a cutting score on the test) and "not accepted" (with scores below the cutting score). A value on the latent variable is fixed in advance; examinees above this value are "suitable" and those below are "not suit able." Using a linear loss function, a procedure is described for computing a cutting score that mini mizes the risk for the decision rule. The procedure is demonstrated with a criterion-referenced achieve ment test of elementary statistics administered to 167 students. [ABSTRACT FROM PUBLISHER]

In this paper Jöreskog's model of congeneric tests is used to analyze agreement between raters. Raters are treated as measuring instruments. The model of congeneric tests, of which classical prallelism and tau-equivalence are shown to be special cases, is applied to teachers' ratings of students' responses on open-end questions. The findings suggest that the ratings are tau-equivalent and that the ratings given by the teachers are reliable. [ABSTRACT FROM PUBLISHER]

Comments on a study which used Monte Carlo Studies to investigate the power in testing covariance matrix hypotheses. Recommendation that simulations be based on empirical estimates of parameter values.

Objective: This research studied the relationship between associated congenital malformations and the mental and psychomotor development of children with clefts., Design: The study was cross-sectional., Setting: The study was conducted in a university hospital for children., Participants: The sample consisted of 148 children with cleft lip, cleft palate, or both., Main Outcome Measures: The children were assessed by a clinical geneticist at the age of 18 months. The children's level of development was determined by means of the Dutch version of the Bayley Scales of Infant Development., Results: One-third of the total sample had associated malformations. Children with an isolated cleft lip showed the least. Children with an isolated cleft palate showed the highest percentage of minor malformations that are minor yet possibly worrisome. The total group achieved a mean developmental index (DI) on the mental scale of 98.9 with SD of 20.9. The motor scale showed a mean DI of 104.9 and SD of 24.7. Analysis of variance (ANOVA) showed that on the mental scale, the three main effects (diagnosis, evaluation, and sex) were significant at the 5% level. On the motor scale, only the main effect "evaluation" was significant., Conclusions: This study demonstrated that children with associated congenital malformations might be disadvantaged with respect to their development. These malformations occurred most frequently with the cleft lip and palate and cleft palate only subgroups. More research, especially concerning the cleft palate only subgroup is needed because they are most at risk.