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[english] In standard statistical packages sequential tests are seldom and when they are offered, they mainly concern just tests about means. By a simulation study it was shown that a new sequential triangular test for the null-hypothesis : 0

The present paper gives a general introduction to the linear logistic test model (Fischer, 1973), an extension of the Rasch model with linear constraints on item parameters, along with eRm (an R package to estimate different types of Rasch models; Mair, Hatzinger, & Mair, 2014) functions to estimate the model and interpret its parameters. The applications of the model in test validation, hypothesis testing, cross-cultural studies of test bias, rule-based item generation, and investigating construct irrelevant factors which contribute to item difficulty are explained. The model is applied to an English as a foreign language reading comprehension test and the results are discussed.

In aptitude and achievement tests, different response formats are usually used. A fundamental distinction must be made between the class of multiple-choice formats and the constructed response formats. Previous studies have examined the impact of different response formats applying traditional statistical approaches, but these influences can also be studied using methods of item response theory to deal with incomplete data. Response formats can influence item attributes in two ways: different response formats could cause items to measure different latent traits or they could contribute differently to item difficulty. In contrast to previous research, the present study examines the impact of response formats on item attributes of a language awareness test applying different item response theory models. Results indicate that although the language awareness test contains items with different response formats, only one latent trait is measured; no format-specific dimensions were found. Response formats do, however, have a distinct impact on the difficulty of the items. In addition to the effects of the three administered item types, a fourth component that makes items more difficult was identified. (Contains 2 figures and 4 tables.)

For large-scale assessments, usually booklet designs administering the same item at different positions within a booklet are used. Therefore, the occurrence of position effects influencing the difficulty of the item is a crucial issue. Not taking learning or fatigue effects into account would result in a bias of estimated item difficulty. The occurrence of position effects is examined for a 4th-grade mathematical competence test of the Austrian Educational Standards by means of the linear logistic test model (LLTM). A small simulation study assesses the test power for this model. Overall, the LLTM without a modelled position effect yielded a good model fit. Therefore, no relevant global item position effect could be found for the analysed mathematical competence test. (Contains 4 tables and 1 figure.)

Though calibration of an achievement test within psychological and educational context is very often carried out by the Rasch model, data sampling is hardly designed according to statistical foundations. However, Kubinger, Rasch, and Yanagida (2009) recently suggested an approach for the determination of sample size according to a given Type I and Type II risk, and a certain effect of model misfit when testing the Rasch model is supported by some new results. The approach uses a three-way analysis of variance design [image omitted] x "C" with mixed classification. There is a (fixed) group factor "A", a (random) factor "B" of testees within "A", and a (fixed) factor "C" of items cross-classified with [image omitted]. The simulation study in this article deals with further item parameter ranges and ability parameter distributions, and with larger sample sizes and item numbers than the original paper. The results are: The approach works given several restrictions, and its main aim, the determination of the sample size, is attained. (Contains 2 notes, 6 tables, and 1 figure.)

In large-scale assessments, it usually does not occur that every item of the applicable item pool is administered to every examinee. Within item response theory (IRT), in particular the Rasch model (1960), this is not really a problem because item calibration works nevertheless. The different test booklets only need to be conceptualized according to a connected incomplete block design. Yet, connectedness of such a design should best be fulfilled severalfold, since deletion of some items in the course of the item pool's IRT calibration may become necessary. The real challenge, however, is to meet constraints determined by numerous moderator variables such as different response formats and several topics of content--all the more so, if several ability dimensions are under consideration, the testing duration is strongly limited or individual scoring and feedback is an issue. In this article, we offer a report of how to deal with the resulting problems. Experience is based on the governmental project of the Austrian Educational Standards (Kubinger et al., 2007). (Contains 1 note, 1 table, and 4 figures.)

Item position effects provoke serious problems within adaptive testing. This is because different testees are necessarily presented with the same item at different presentation positions, as a consequence of which comparing their ability parameter estimations in the case of such effects would not at all be fair. In this article, a specific adaptive Rasch-model-calibrated test, AID 2 ("Adaptive Intelligence Diagnosticum"--Version 2.2; Kubinger, 2009a), is analyzed according to a suggestion of Kubinger (2008, 2009b): applying the Rasch-model-based "Linear logistic test model" (LLTM) to test item presentation's sequence effects. AID 2's subtests are to be administered along a branched testing design; 5 of these subtests are now under consideration. Results showed no stringent trend of an item position effect for any specific subtest or generally for any combinations of item subsets; to the extent that such an effect was established, it was not really large enough to be of practical relevance. (Contains 2 notes, 7 tables, and 2 figures.)

The linear logistic test model (LLTM) breaks down the item parameter of the Rasch model as a linear combination of some hypothesized elementary parameters. Although the original purpose of applying the LLTM was primarily to generate test items with specified item difficulty, there are still many other potential applications, which may be of use for psychometric research on various testing conditions. This article provides some examples of such applications. The examples include (a) position effect of item presentation (in particular, learning and fatigue effects); (b) content-specific learning effect; (c) effect of speeded item presentation; and (d) effect of item response format. (Contains 3 figures.)

An interview guide for children and adolescents, which is based on systemic therapy, has recently been added to the collection of published instruments for psychological interviews. This article aims to establish the amount of information gained during a psychological investigation using the Systemic-based Interview Guide rather than an intuitive, unstructured interview approach; the latter is often used by inexperienced practitioners. For this purpose, an experiment was designed using reconstructed clinical cases, which were then presented by role players pretending to be patients in a psychological interview. Each case could thus be presented numerous times, in particular under both experimental conditions. The respective interview was carried out by 20 psychology students. A higher validity, as a result of more relevant information, and a higher economy, as a result of less irrelevant information, was found for the Systemic-based Interview Guide. Therefore, it can be recommended that the Systemic-based Interview Guide, as described here, be used instead of an intuitive unstructured approach, particularly for interviewers with less practical experience. (Contains 4 tables, 2 figures, and 2 notes.)

The present study, based on the work of Dweck (2000) and her description of helpless and mastery-orientated children, was designed to find a new, simple and economic way of assessing helplessness while testing a child's intelligence. Two hundred and thirty-two Austrian grammar-school children, previously classified as either helpless or mastery-oriented, were tested with the Adaptive Intelligence Diagnosticum (AID 2; Kubinger and Wurst, 2000), a German intelligence test-battery for children and adolescents. During the testing, the children were asked if they would prefer to continue with easier, equally difficult or harder items after each task block. Analysis of variance revealed that it is possible to identify helpless subjects during the regular test procedure with AID 2. (Contains 2 notes and 5 tables.)

The question is to what extent intelligence test-batteries prove any kind of empirical reference to common intelligence theories. Of particular interest are conceptualized tests that are of a high psychometric standard--those that fit the Rasch model--and hence are not exposed to fundamental critique. As individualized testing, i.e., a psychologist and a testee face to face, is often preferred by many practitioners, a Wechsler-like test-battery will be dealt with here: The Adaptive Intelligence Diagnosticum (AID 2; [Kubinger, K. D. &, Wurst, E. (2000). "Adaptives Intelligenz Diagnostikum--Version 2.1"(AID 2). ["Adaptive intelligence diagnosticum 2."] Weinheim: Beltz.]). Using the standardization sample, confirmatory factor analyses were performed with respect to intelligence theories and models, respectively, as concerns Spearman, Wechsler, Thurstone, Cattell, Jager, and Carroll. Additionally, a confirmatory factor analysis was performed with respect to a simplified neuropsychological model of specific learning disorders, which proved to fit the data best, even better than the (exploratory) four factor solution as given in the AID 2-manual. This model is based on the three interdependent factors "perception," "retrieval," and "utilization." The answer is that if modern test conceptualizations attempt to fulfill pragmatic purposes they hardly have any relation to pertinent intelligence theories, but rather create their own kind of informal, heuristic model of "intelligence."

This article emphasizes that the Rasch model is not only very useful for psychological test calibration but is also necessary if the number of solved items is to be used as an examinee's score. Simplified proof that the Rasch model implies specific objective parameter comparisons is given. Consequently, a model check per se is possible. For data and item pools that fail to fit the Rasch model, various reasons are listed. For instance, the two-parameter logistic or three-parameter logistic models would probably be more suitable. Several suggestions are given for controlling the overall Type I risk, for including a power analysis (i.e., taking the Type II risk into account), for disclosing artificial model check results, and for the deletion of Rasch model misfitting examinees. These suggestions are empirically founded and may serve in the establishment of certain rough state-of-the-art standards. However, a degree of statistical elaboration is needed; and forthcoming test authors will still suffer from the fact that no standard software exists that offers all of the given approaches as a package. (Contains 4 figures.)

The concept of IRT (Item Response Theory), offering several models which at least guarantee if they hold, that a scoring rule in question is indeed fair, can be referred to in regard to the pertinent scoring rule of the IQ (intelligence quotient) in many intelligence test-batteries. Muller's continuous Rasch model (1987, 1999) applies. Analyses were carried out for three test-batteries, that is the German and the English version of AID 3 and a respective version for group administration, to show this in an exemplary way. Sample sizes comprised 431, 761, and 2278, respectively. Above all, the graphical model check disclosed a serious misfit of the model: There is no support for the notion that the respective scoring rule is fair. Detailed inspections give the impression that essentially calculating the sum of the subtest scores mixes (at least) two components, "intelligence" and "willingness to achieve in unchallenging tasks." Practitioners should be assailed by doubts that all other intelligence test-batteries in use, which are not evaluated accordingly, do score fair. [ABSTRACT FROM AUTHOR]