RAND Corporation

About: RAND Corporation is a nonprofit organization based out in Santa Monica, California, United States. It is known for research contribution in the topics: Health care & Population. The organization has 9602 authors who have published 18570 publications receiving 744658 citations.

The rand 36-item health survey 1.0

Abstract: Recently, Ware and Sherbourne published a new short-form health survey, the MOS 36-Item Short-Form Health Survey (SF-36), consisting of 36 items included in long-form measures developed for the Medical Outcomes Study. The SF-36 taps eight health concepts: physical functioning, bodily pain, role limitations due to physical health problems, role limitations due to personal or emotional problems, general mental health, social functioning, energy/fatigue, and general health perceptions. It also includes a single item that provides an indication of perceived change in health. The SF-36 items and scoring rules are distributed by MOS Trust, Inc. Strict adherence to item wording and scoring recommendations is required in order to use the SF-36 trademark. The RAND 36-Item Health Survey 1.0 (distributed by RAND) includes the same items as those in the SF-36, but the recommended scoring algorithm is somewhat different from that of the SF-36. Scoring differences are discussed here and new T-scores are presented for the 8 multi-item scales and two factor analytically-derived physical and mental health composite scores.

Decomposition Principle for Linear Programs

Abstract: A technique is presented for the decomposition of a linear program that permits the problem to be solved by alternate solutions of linear sub-programs representing its several parts and a coordinating program that is obtained from the parts by linear transformations. The coordinating program generates at each cycle new objective forms for each part, and each part generates in turn from its optimal basic feasible solutions new activities columns for the interconnecting program. Viewed as an instance of a “generalized programming problem” whose columns are drawn freely from given convex sets, such a problem can be studied by an appropriate generalization of the duality theorem for linear programming, which permits a sharp distinction to be made between those constraints that pertain only to a part of the problem and those that connect its parts. This leads to a generalization of the Simplex Algorithm, for which the decomposition procedure becomes a special case. Besides holding promise for the efficient computation of large-scale systems, the principle yields a certain rationale for the “decentralized decision process” in the theory of the firm. Formally the prices generated by the coordinating program cause the manager of each part to look for a “pure” sub-program analogue of pure strategy in game theory, which he proposes to the coordinator as best he can do. The coordinator finds the optimum “mix” of pure sub-programs using new proposals and earlier ones consistent with over-all demands and supply, and thereby generates new prices that again generates new proposals by each of the parts, etc. The iterative process is finite.

Smearing Estimate: A Nonparametric Retransformation Method

Abstract: The smearing estimate is proposed as a nonparametric estimate of the expected response on the untransformed scale after fitting a linear regression model on a transformed scale. The estimate is consistent under mild regularity conditions, and usually attains high efficiency relative to parametric estimates. It can be viewed as a low-premium insurance policy against departures from parametric distributional assumptions. A real-world example of predicting medical expenditures shows that the smearing estimate can outperform parametric estimates even when the parametric assumption is nearly satisfied.

Analyzing Qualitative Data: Systematic Approaches

Abstract: Preface Acknowledgments PART I. THE BASICS Chapter 1. Introduction to Text: Qualitative Data Analysis Chapter 2. Collecting Data Chapter 3. Finding Themes Chapter 4. Codebooks and Coding Chapter 5. Introduction to Data Analysis Chapter 6. Conceptual Models PART II. THE SPECIFICS Chapter 7. First Steps in Analysis: Comparing Attributes of Variables Chapter 8. Cultural Domain Analysis: Free Lists, Judged Similarities, and Taxonomies Chapter 9. KWIC Analysis, Word Counts, and Semantic Network Analysis Chapter 10. Discourse Analysis: Conversation and Performance Chapter 11. Narrative Analysis Chapter 12. Grounded Theory Chapter 13. Content Analysis Chapter 14. Schema Analysis Chapter 15. Analytic Induction and Qualitative Comparative Analysis Chapter 16. Ethnographic Decision Models Chapter 17. Sampling Appendix: Resources for Analyzing Qualitative Data References Author Index Subject Index About the Authors