Strategies for Reining In Medicare Spending Through Delivery System Reforms: Assessing the Evidence and Opportunities

Outlines promising measures to achieve savings in Medicare costs by reducing the need for hospitalization and readmission and by reducing disparities across physicians and geographic areas in care delivery, utilization, and expenditures

Reducing Nursing Home Use Through Consumer-Directed Personal Care Services

Highlights findings on how the Cash and Counseling program, which allows Medicaid enrollees with personal care services to hire their own care workers, affected nursing facility use and expenditures as well as personal care and Medicaid costs in Arkansas

Rational Arithmetic Mathematica Functions to Evaluate the One-sided One-sample K-S Cumulative Sample Distribution

One of the most widely used goodness-of-fit tests is the Kolmogorov-Smirnov (KS) family of tests which have been implemented by many computer statistical software packages. To calculate a p value (evaluate the cumulative sampling distribution), these packages use various methods including recursion formulae, limiting distributions, and approximations of unknown accuracy developed over thirty years ago. Based on an extensive literature search for the one-sided one-sample K-S test, this paper identifies two direct formulae and five recursion formulae that can be used to calculate a p value and then develops two additional direct formulae and four iterative versions of the direct formulae for a total of thirteen formulae. To ensure accurate calculation by avoiding catastrophic cancelation and eliminating rounding error, each formula is implemented in rational arithmetic. Linear search is used to calculate the inverse of the cumulative sampling distribution (find the confidence interval bandwidth). Extensive tables of bandwidths are presented for sample sizes up to 2, 000. The results confirm the hypothesis that as the number of digits in the numerator and denominator integers of the rational number test statistic increases, the computation time also increases. In comparing the computational times of the thirteen formulae, the direct formulae are slightly faster than their iterative versions and much faster than all the recursion formulae. Computational times for the fastest formula are given for sample sizes up to fifty thousand.

Rational Arithmetic Mathematica Functions to Evaluate the Two-Sided One Sample K-S Cumulative Sampling Distribution

One of the most widely used goodness-of-fit tests is the two-sided one sample Kolmogorov-Smirnov (K-S) test which has been implemented by many computer statistical software packages. To calculate a two-sided p value (evaluate the cumulative sampling distribution), these packages use various methods including recursion formulae, limiting distributions, and approximations of unknown accuracy developed over thirty years ago. Based on an extensive literature search for the two-sided one sample K-S test, this paper identifies an exact formula for sample sizes up to 31, six recursion formulae, and one matrix formula that can be used to calculate a p value. To ensure accurate calculation by avoiding catastrophic cancelation and eliminating rounding error, each of these formulae is implemented in rational arithmetic. For the six recursion formulae and the matrix formula, computational experience for sample sizes up to 500 shows that computational times are increasing functions of both the sample size and the number of digits in the numerator and denominator integers of the rational number test statistic. The computational times of the seven formulae vary immensely but the Durbin recursion formula is almost always the fastest. Linear search is used to calculate the inverse of the cumulative sampling distribution (find the confidence interval half-width) and tables of calculated half-widths are presented for sample sizes up to 500. Using calculated half-widths as input, computational times for the fastest formula, the Durbin recursion formula, are given for sample sizes up to two thousand.

Arbitrary Precision Mathematica Functions to Evaluate the One-Sided One Sample K-S Cumulative Sampling Distribution

Efficient rational arithmetic methods that can exactly evaluate the cumulative sampling distribution of the one-sided one sample Kolmogorov-Smirnov (K-S) test have been developed by Brown and Harvey (2007) for sample sizes n up to fifty thousand. This paper implements in arbitrary precision the same 13 formulae to evaluate the one-sided one sample K-S cumulative sampling distribution. Computational experience identifies the fastest implementation which is then used to calculate confidence interval bandwidths and p values for sample sizes up to ten million.

Now, That\u27s a Sign

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Asthma Patient Education: Partnership in Care

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/113672/1/alr21596.pd

Organizational commitment and its effects on behavior.

This study is an investigation into the complexities of organizational commitment and its effect(s) on people\u27s behaviors. In recent management literature, the concept of organizational commitment has developed along two separate lines of research. One holds commitment to be a set of positive attitudes towards an organization with motivational effects on performance and membership. The other views commitment as an outcome of investments in a relationship which retrospectively bind the individual to continued membership. Following an exploratory study into managers\u27 views on commitment , a measure of commitment to goals was added. All three types were compared to hypothesized outcome behaviors. An interactive effect between calculative commitment and job alternatives on intent to remain was included. A questionnaire was used to measure individual commitment on the three commitment scales and reported behavior on seven outcome variables. All ten measures were operationalized by combining existing measure with ideas drawn from the exploratory study. The questionnaire was administered to 250 people at two private companies. Factor analysis was conducted on related variable measures in order to examine discriminant validity. Correlation analysis, multiple regression, and LISREL analysis were conducted in order to test 26 separate hypotheses derived from two models. All three types of commitment were confirmed as separate constructs. As expected, both affective commitment and goal commitment appeared to have positive relationships with performance variables. Also as expected, affective and calculative commitment proved to be strong predictors of intent to remain . Affective commitment also a predicted low search behavior and high desire to remain . Contrary to expectations, the effect of affective commitment on performance variables was stronger than that of goal commitment . Also contrary, calculative commitment had a positive relationship with desire to remain and low search behavior . There was no evidence of an interactive effect between calculative commitment and job alternatives . The results confirm the power of affective commitment as a motivating phenomenon and suggest that its power exceeds that of commitment to goals . Results also suggest that calculative commitment is related to desire to remain a member, though not with a willingness to expend extra job effort

The algorithm designer project : a visual programming environment for data structure demonstration

Previous work on pedagogical tools for teaching students algorithms has focused on high level animations of the algorithms. This dissertation describes a tool that gives instructors the ability to pictorially demonstrate the implementation of algorithms at the data structure level.The Algorithm Designer Project explores the use of a computer as an electronic whiteboard for instruction of computer science. It improves upon the traditional physical blackboardenvironment by providing syntactic and semantic support for data structure design and algorithm demonstration. The ultimate goal of this project is to provide an attractive, easy to use, system through which users can demonstrate simple algorithms and data structures,such as those presented in data structures textbooks. The project consists of three components: Data Structure Designer, Algorithm Designer, and Rule Designer. DataStructure Designer allows users to design and customize the appearance of data structures that they intend to use to create visual programs. Concrete examples of these data structures can be placed into Algorithm Designer and directly manipulated to demonstrate algorithms.Visual programs are programs written using pictures instead of, or in conjunction with,text. Rule Designer allows the creation and manipulation of transition rules to define visual program scripts to act upon Algorithm Designer objects. The project was implemented using the Amulet toolkit and runs on Macintosh, Windows, and UNIX platforms.A key insight discovered during development of the Algorithm Designer Project was that although textbooks employ a wide variety of data structure visualizations, the differences between these visualizations can be grouped into a small number of categories. Two unique interface items were developed during the course of the research: 1) a color mapping widget interface item that provides an easy way for the user to associate a set of colors with a range of values in a data structure visualization and 2) seeds\u27\u27 and holes, a mechanism for visually identifying and supporting type-specific semantic behavior for edge-based data structures. Finally, this dissertation describes a novel use of imperative programming constructs within a pictorial rewrite rule-based scripting system and a novel use of these rules for teaching conventional imperative programming