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Measurement Design (measurement + design)
Selected AbstractsWhat sources contribute to variance in observer ratings?INFANT AND CHILD DEVELOPMENT, Issue 3 2008Using generalizability theory to assess construct validity of psychological measures Abstract Cronbach and Meehl (Psychol. Bull. 1955; 52:281,302) stated that the key question to be addressed when assessing construct validity is ,What sources contribute to variance in test performance?' We illustrate the utility of generalizability theory (GT) as a conceptual framework that encourages psychological researchers to address this question and as a flexible set of analytic tools that can provide answers to inform both substantive theory and measurement practice. To illustrate these capabilities, we analyze observer ratings of 27 caregiver,child dyads, focusing on the importance of situational (contextual) factors as sources of variance in observer ratings of caregiver,child behaviors. Cross-situational consistency was relatively low for the categories of behavior analyzed, indicating that dyads vary greatly in their interactional patterns from one situation to the next, so that it is difficult to predict behavioral frequencies in one context from behaviors observed in a different context. Our findings suggest that single-situation behavioral measures may have limited generalizability, either to behavior in other contexts or as measures of global interaction tendencies. We discuss the implications of these findings for research and measurement design in developmental psychology. Copyright © 2008 John Wiley & Sons, Ltd. [source] Generalizability in Item Response ModelingJOURNAL OF EDUCATIONAL MEASUREMENT, Issue 2 2007Derek C. Briggs An approach called generalizability in item response modeling (GIRM) is introduced in this article. The GIRM approach essentially incorporates the sampling model of generalizability theory (GT) into the scaling model of item response theory (IRT) by making distributional assumptions about the relevant measurement facets. By specifying a random effects measurement model, and taking advantage of the flexibility of Markov Chain Monte Carlo (MCMC) estimation methods, it becomes possible to estimate GT variance components simultaneously with traditional IRT parameters. It is shown how GT and IRT can be linked together, in the context of a single-facet measurement design with binary items. Using both simulated and empirical data with the software WinBUGS, the GIRM approach is shown to produce results comparable to those from a standard GT analysis, while also producing results from a random effects IRT model. [source] Optimal measurement design for monitoring batch processesAICHE JOURNAL, Issue 3 2010Olja Stanimirovic First page of article [source] Intervention Effects on Cognitive Antecedents of Physical Exercise: A 1-Year Follow-Up StudyAPPLIED PSYCHOLOGY: HEALTH AND WELL-BEING, Issue 2 2009Wiebke Göhner We developed and evaluated a theory-based intervention programme (MoVo-LISA) that encompasses motivational and volitional strategies aiming to prepare orthopaedic rehabilitation patients to perform physical exercise on a regular basis after discharge. The intervention consists of six units: two group sessions, one one-to-one interview, and three after-care contacts. Two hundred and twenty inactive patients were subsequently assigned to an intervention group (standard care plus MoVo-LISA) and a control group (standard care). Participants filled out questionnaires assessing cognitive antecedents of physical exercise. Measurement took place before and after rehabilitation, 6 weeks and 6 months after discharge, and 1 year after discharge. A 2 × 5 repeated measurement design was applied. Results revealed significant main and interaction effects with regard to cognitive variables; the intervention group reported enhanced self-efficacy and more positive balance of outcome expectations at 6 months as well as stronger goal intentions, more elaborated implementation intentions, and optimised strategies of intention shielding at 12 months after discharge compared to patients of the control group. Our findings demonstrate that a short and inexpensive cognitive-behavioural training programme is an effective tool to enable rehabilitation patients to follow treatment recommendations after discharge. The standardised intervention can be conducted by personnel other than psychologists. [source] Real-time detection of single-living pancreatic ,-cell by laser tweezers Raman spectroscopy: High glucose stimulationBIOPOLYMERS, Issue 7 2010Xi Rong Abstract Glucose acts as a ,-cell stimulus factor and leads to cellular responses that involve a large amount of biomolecule formation, relocation, and transformation. We hypothesize that information about these changes can be obtained in real-time by laser tweezers Raman spectroscopy. To test this hypothesis, repeated measurements designs in accordance with the application of Raman spectroscopy detection were used in the current experiment. Single rat ,-cells were measured by Raman spectroscopy in 2.8 mmol/l glucose culture medium as a basal condition. After stimulation with high glucose (20 mmol/l), the same cells were measured continuously. Each cell was monitored over a total time span of 25 min, in 5 min intervals. During this period of time, cells were maintained at an appropriate temperature controlled by an automatic heater, to provide near-physiological conditions. It was found that some significant spectral changes induced by glucose were taking place during the stimulation time course. The most noticeable changes were the increase of spectral intensity at the 1002, 1085, 1445, and 1655 cm,1 peaks, mainly corresponding to protein and lipid. We speculate that these changes might have to do with ,-cell protein and lipid synthesis. Using laser tweezers Raman spectroscopy in combination with glucose stimulation, optical spectral information from rat ,-cells was received and analyzed. © 2010 Wiley Periodicals, Inc. Biopolymers 93: 587,594, 2010. This article was originally published online as an accepted preprint. The "Published Online" date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com [source] | |||||||||||||