Performing the Kernel Method of Test Equating with the Package kequate

Hyperandrogenicity in women is closely associated with insulin resistance and a risk factor for cardiovascular disease and noninsulin-dependent diabetes mellitus (NIDDM). Therefore, 25 postmenopausal women with NIDDM and sex hormone-binding globulin values less than 60 nmol/L, as an indicator of a moderate hyperandrogenicity, were treated with 2 mg 17-beta-estradiol orally for 3 months in a double-blind, cross-over, placebo-controlled trial. During the last 16 days of active treatment, 1 mg norethisterone acetate was added for 10 days for endometrial protection. Blood glucose, glycosylated hemoglobin, insulin, c-peptide, lipoprotein profile, sex steroid hormones, GH, and insulin-like growth factor I (IGF-I) were measured, and insulin sensitivity was determined by the euglycemic hyperinsulinemic clamp method. All metabolic measurements were taken at baseline and after 68 days of active or placebo treatment. Estradiol treatment, compared with the placebo period, was followed by a marked increase of sex hormone-binding globulin and a decrease of free testosterone. Blood glucose, glycosylated hemoglobin, c-peptide, total cholesterol, low-density lipoprotein cholesterol, and IGF-I decreased significantly (P < 0.01-P < 0.001), whereas high-density lipoprotein cholesterol rose (P < 0.001). In conclusion, estrogen replacement therapy in postmenopausal women with NIDDM ameliorated hyperandrogenicity, and this was accompanied by marked improvements in glucose homeostasis and lipoprotein profile.

National assessments and other investigations have drawn attention to the fact that there is considerable room for improvement in science teaching and learning. This article describes, exemplifies, and discusses a research program set up to address this unsatisfactory state of affairs. Briefly, the idea of the program is that researchers in science education and teachers in schools should work together to design teaching sequences and assess how they function in practice, including what the students learn. This work has two aims: first, to generate results of practical use, and second, to contribute to the development of educational science. Results of practical use are presented in the form of teacher's guides, written to be used as tools for generating further knowledge. As a contribution to educational science, attempts are made to formulate content‐oriented theories of conditions that are likely to improve learning with understanding. This article describes and discusses how the research program has been implemented in the area of geometrical optics at the upper level (grades 8 and 9) of compulsory school. It is suggested that the idea of content‐oriented theories is worth further examination and development and might contribute to strengthening science education as an autonomous discipline. © 2004 Wiley Periodicals, Inc. Sci Ed, 89:196–218, 2005 An Erratum has been published for this article in

In diagnostic classification models (DCMs), the Q matrix encodes in which attributes are required for each item. The Q matrix is usually predetermined by the researcher but may in practice be misspecified which yields incorrect statistical inference. Instead of using a predetermined Q matrix, it is possible to estimate it simultaneously with the item and structural parameters of the DCM. Unfortunately, current methods are computationally intensive when there are many attributes and items. In addition, the identification constraints necessary for DCMs are not always enforced in the estimation algorithms which can lead to non-identified models being considered. We address these problems by simultaneously estimating the item, structural and Q matrix parameters of the Deterministic Input Noisy “And” gate model using a constrained Metropolis–Hastings Robbins–Monro algorithm. Simulations show that the new method is computationally efficient and can outperform previously proposed Bayesian Markov chain Monte-Carlo algorithms in terms of Q matrix recovery, and item and structural parameter estimation. We also illustrate our approach using Tatsuoka’s fraction–subtraction data and Certificate of Proficiency in English data.