Factor validation and Rasch analysis of the individual recovery outcomes counter

Objective: The Individual Recovery Outcomes Counter is a 12-item personal recovery self assessment tool for adults with mental health problems. Although widely used across Scotland, limited research into its psychometric properties has been conducted. We tested its' measurement properties to ascertain the suitability of the tool for continued use in its present form.Materials and methods: Anonymised data from the assessments of 1,743 adults using mental health services in Scotland were subject to tests based on principles of Rasch measurement theory, principal components analysis and confirmatory factor analysis.Results: Rasch analysis revealed that the 6-point response structure of the Individual Recovery Outcomes Counter was problematic. Re-scoring on a 4-point scale revealed well ordered items that measure a single, recovery-related construct, and has acceptable fit statistics. Confirmatory factor analysis supported this. Scale items covered around 75% of the recovery continuum; those individuals least far along the continuum were least well addressed.Conclusions: A modified tool worked well for many, but not all, service users. The study suggests specific developments are required if the Individual Recovery Outcomes Counter is to maximise its' utility for service users and provide meaningful data for service providers.*Implications for Rehabilitation*Agencies and services working with people with mental health problems aim to help them with their recovery.*The individual recovery outcomes counter has been developed and is used widely in Scotland to help service users track their progress to recovery.*Using a large sample of routinely collected data we have demonstrated that a number of modifications are needed if the tool is to adequately measure recovery.*This will involve consideration of the scoring system, item content and inclusion, and theoretical basis of the tool

Integrable e-lements for Statistics Education

Without doubt modern education in statistics must involve practical, computer-based data analysis but the question arises whether and how computational elements should be integrated into the canon of methodological education. Should the student see and study high-level programming code right at the beginning of his or her studies? Which technology can be presented during class and which computational elements can re-occur (at increasing level of complexity) during the different courses? In this paper we address these questions and discuss where e-techniques have their limits in statistics education.electronic books, hypertext, e-supported teaching, statistical software

Simple data analysis for biologists

This document provides a simple introduction to research methods and analysis tools for biologists or environmental scientists, with particular emphasis on fish biology in devleoping countries

Statistics E-learning Platforms Evaluation: Case Study

With the increase of e-learning by universities and educational institutes in the world through more electronic platforms, come the questions to researchers, educators and designers of electronic platforms about feasibility and using this method of learning. Are we achieving the desired goals and improving the quality of education? Are we improving their performance and ability to self-study without the need for a teacher? Is e-learning an effective and successful method from the students views? In this paper, we consider evaluate e-learning systems in statistics. We make an evaluation study, we analyze a students sample of the methods: Factor analysis, Logit model. The common aim of this evaluation is to provide data to justify the results or evidence to support that the e-learning platforms are helping the students to learn more effectively. The questionnaire covers information about e-learning evaluation criterias. Some of these criterias are: Navigability, applicability, instructional structure and interactivity.E-learning, Evaluation, Statistical software

BiplotGUI: Interactive Biplots in R

Biplots simultaneously provide information on both the samples and the variables of a data matrix in two- or three-dimensional representations. The BiplotGUI package provides a graphical user interface for the construction of, interaction with, and manipulation of biplots in R. The samples are represented as points, with coordinates determined either by the choice of biplot, principal coordinate analysis or multidimensional scaling. Various transformations and dissimilarity metrics are available. Information on the original variables is incorporated by linear or non-linear calibrated axes. Goodness-of-fit measures are provided. Additional descriptors can be superimposed, including convex hulls, alpha-bags, point densities and classification regions. Amongst the interactive features are dynamic variable value prediction, zooming and point and axis drag-and-drop. Output can easily be exported to the R workspace for further manipulation. Three-dimensional biplots are incorporated via the rgl package. The user requires almost no knowledge of R syntax.

Statistics challenges and opportunities for the twenty first century

The field of statistics has made remarkable contribution to society over several decades its impact is felt across gradually all branches of science, medicine, industries and planning in the government department. The main objectives of this research is to identify forthcoming challenges and enormous opportunities for the professions. I have tried to concentrate not only to scientific research but also cover important related topics such as statistics educations infrastructure science, industry, Pharmaceuticals, Fashion Technology, Information technology, the international perspective and a long term objectives. A substantial proportion of the research is devoted to describing the unique role of statistics as a tool in gaining knowledge, with the goal of making the research more accessible to the statistical community. This was done largely because the role of statistical science is often poorly understood by the rest of the scientific community. Much of the intellectual excitement of the core of the subject comes from the development and use of sophisticated mathematical and computational tools. For this reason there is a potential confusion about how statistics relates to other field , and so a portion of this research dealt with separating the identity of the others

Segmentation of Potential Fraud Taxpayers and Characterization in Personal Income Tax Using Data Mining Techniques

This paper proposes an analytical framework that combines dimension reduction and data mining techniques to obtain a sample segmentation according to potential fraud probability. In this regard, the purpose of this study is twofold. Firstly, it attempts to determine tax benefits that are more likely to be used by potential fraud taxpayers by means of investigating the Personal Income Tax structure. Secondly, it aims at characterizing through socioeconomic variables the segment profiles of potential fraud taxpayer to offer an audit selection strategy for improving tax compliance and improve tax design. An application to the annual Spanish Personal Income Tax sample designed by the Institute for Fiscal Studies is provided. Results obtained confirm that the combination of data mining techniques proposed offers valuable information to contribute to the study of tax frau

Symptoms of poverty within a group of land reform beneficiaries in the Midlands of KwaZulu-Natal: Analysis and policy recommendations

This study identifies different dimensions of poverty affecting the current and future well-being of households within a community of land reform beneficiaries in the Midlands of KwaZulu-Natal. A census survey of the beneficiary households was conducted in May 2002 to gather data on poverty indicators. Principal Component Analysis was used to construct an index of the standard of housing, which was then combined with variables measuring other symptoms of poverty (income, wealth and health) in a Cluster Analysis of the households. The analysis revealed five clusters representing four distinct groups of poverty; households relatively income and asset rich, households relatively income rich but asset poor, households relatively asset rich but income poor and households with the lowest incomes and assets. While income is an important indicator of current poverty, household wealth (measured in terms of saleable assets) indicates ability to cope with adverse shocks – a key issue as life expectancy is declining and old-age pensioners account for a large share of household income in the survey group. It is concluded that child welfare grants could be increased as pension earnings become less effective in combating the symptoms of poverty in this area. In addition, land reform grants may address poverty more effectively when used to purchase equity in joint ventures with commercial farmers than when used to purchase land that many of the beneficiaries cannot use or transact.Food Security and Poverty,