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State licensing requirements

State licensing requirements should ensure that practitioners demonstrate knowledge of scientific and professional issues regarding use of computer-based products involving test interpretation and clinical decision making. Current requirements for continuing education may promote greater participation in relevant learning experiences. However, substantive changes in longstanding trends within the discipline of psychological assessment will require front-end commitment to improved training of tomorrow’s scientists and practitioners.

For example, assessment training should emphasize limitations in clinical judgment and methods of reducing cognitive-processing errors as heavily as proficiency in specific assessment techniques. Training programs should prepare students to be more sophisticated consumers of practice-relevant technologies not yet conceived. Curricula should undergo regular revision to integrate innovative methodologies relevant to the development and validation of new computer-assisted assessment and decision-making procedures.

Computers will become increasingly important for psychological assessment. As a discipline, we should ensure that there is everything right with that! (Udo 2002) Since the process will improve in the result of the enhanced outcomes, non-inclusion of the valid process, as well as, improvement tests will incomplete a study. In short, the use of multiple criteria is involved in the evaluation of the DMSS effectiveness. In addition, the nature of the needed outcomes has also been determined by the corresponding model.

It has also been suggested by the examinations of the paper that DMSS effectiveness will be assessed properly by a multiple criteria evaluation model. The steps and phases of the process will be improved by the ability of the DMSS, which will be the reliable source for the decision value, as shown by this model. The activities for the proper determination of the DMSS value have been identified by the model, as specified by the improvement of these steps and phases. Estimations of the model can be done in the following ways. (i) Separate outcomes and process assessments can be analyzed statistically.

(ii) A joint decision value function can be analyzed by econometric or multiple criteria in the decision-making. Moreover, a relatively transparent manner can be considered for the delivery of the DMSS evaluation model to the evaluator with the help of the decision-making support system. (Balasubramanian 1999) While these conclusions have been supported by the recent experiments, the findings of these papers have to be refuted or confirmed by further empirical and case studies. Alternatives would have to be developed, and test by the additional research in the following ways.

(i) Set component measures will be process, and outcomes will be evaluated. (ii) Functions will be valued, and outcomes will be used for the decision. (iii) The sets and functions will be used for the estimation methodologies. Added development and empirical efficacy testing can be used by the conceptual evaluation DMSS. A standard for the DMSS effectiveness studies can be considered a successfully tested evaluation model. In addition, the normal delivery mechanism role can be played by a tested evaluation DMSS for the model.

Process capability indices are useful management tools, particularly in the manufacturing industry, which provide common quantitative measures of manufacturing capability and production quality. Most supplier certification manuals include a discussion of process capability analysis and describe the recommended procedure for computing a process capability index. In spite of the introductions of many process capability indices, the index remains the most popular one because it provides quantitative measures of process yield and upper bound on product fraction of defectives.

Acceptance sampling plans are practical tools for quality assurance applications. It provides the buyer and the vendor a decision rule for product sentencing to meet their needs. Since the sampling cannot guarantee that the defective items in a lot will be sampled and inspected, then the sampling involves risks of not adequately reflecting the quality conditions of the lot. Such a risk is even more significant as the rapid advancement of the manufacturing technology and stringent customers demand is enforced.

Particularly, when the product fraction of defectives is very low and measured in parts per million (PPM), the required number of inspection items must be enormously large in order to adequately reflect the actual lot quality. In this paper, an effective sampling plan was developed. Process capability index was considered the base for the plan, by which, product acceptance problem will be dealt for the processes, which will be having very low fraction in terms of the defectives.

The proposed sampling plan provides a feasible inspection policy, which can be applied to products with very low fraction of defectives where classical sampling plans cannot be applied. The exact sampling distribution was considered the base for the new proposed sampling plan, rather than the approximation. We developed a method to determine the sample size required for inspection and the corresponding acceptance criterion, to provide the desired levels of protection to both producers and consumers.

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