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Methods of evaluation in outcomes research.

UNLABELLED: This activity is designed for pharmacists, physicians, physician assistants, nurses, and other healthcare team members; payers for health services; and healthcare executives. GOAL: To provide basic information on the methods used and computer software available for evaluating invariant factorial structures, such as those found in health status measurement tools. OBJECTIVES: 1. Discuss why comparison of mean scores may not be appropriate when interpreting humanistic outcomes results. 2. Identify alternative methods for evaluating data from health status measurement tools, such as the SF-36. 3. Define validity, reliability, and structure. 4. Understand the value of structural equation modeling when using health status measurement tools, such as the SF-36. 5. Describe the statistical software used to perform structural equation modeling.

Data Interpretation, Statistical↗

Developing indicators for European birds.

The global pledge to deliver 'a significant reduction in the current rate of biodiversity loss by 2010' is echoed in a number of regional and national level targets. There is broad consensus, however, that in the absence of conservation action, biodiversity will continue to be lost at a rate unprecedented in the recent era. Remarkably, we lack a basic system to measure progress towards these targets and, in particular, we lack standard measures of biodiversity and procedures to construct and assess summary statistics. Here, we develop a simple classification of biodiversity indicators to assist their development and clarify purpose. We use European birds, as example taxa, to show how robust indicators can be constructed and how they can be interpreted. We have developed statistical methods to calculate supranational, multi-species indices using population data from national annual breeding bird surveys in Europe. Skilled volunteers using standardized field methods undertake data collection where methods and survey designs differ slightly across countries. Survey plots tend to be widely distributed at a national level, covering many bird species and habitats with reasonable representation. National species' indices are calculated using log-linear regression, which allows for plot turnover. Supranational species' indices are constructed by combining the national species' indices weighted by national population sizes of each species. Supranational, multi-species indicators are calculated by averaging the resulting indices. We show that common farmland birds in Europe have declined steeply over the last two decades, whereas woodland birds have not. Evidence elsewhere shows that the main driver of farmland bird declines is increased agricultural intensification. We argue that the farmland bird indicator is a useful surrogate for trends in other elements of biodiversity in this habitat.

Animals↗

Analysing non-compliance in clinical trials: ethical imperative or mission impossible?

Assuming that a drug is active and different from placebo, a patient's gain or loss is likely to depend on how much of the drug is taken and when. The present paper motivates the ethical imperative of statistical compliance analysis by considering important clinical questions, the advent of more precise compliance measuring instruments and new statistical efforts towards well understood analyses that seek to preserve scientific integrity. An extension of Efron and Feldman's approach is developed which exploits the randomization assumption in combination with structural models. It also generates more promising designs and alternative statistical approaches.

Data Interpretation, Statistical↗

An empirical comparison of statistical tests for assessing the proportional hazards assumption of Cox's model.

In the analysis of survival data using the Cox proportional hazard (PH) model, it is important to verify that the explanatory variables analysed satisfy the proportional hazard assumption of the model. This paper presents results of a simulation study that compares five test statistics to check the proportional hazard assumption of Cox's model. The test statistics were evaluated under proportional hazards and the following types of departures from the proportional hazard assumption: increasing relative hazards; decreasing relative hazards; crossing hazards; diverging hazards, and non-monotonic hazards. The test statistics compared include those based on partitioning of failure time and those that do not require partitioning of failure time. The simulation results demonstrate that the time-dependent covariate test, the weighted residuals score test and the linear correlation test have equally good power for detection of non-proportionality in the varieties of non-proportional hazards studied. Using illustrative data from the literature, these test statistics performed similarly.

Bias↗

Statistical analysis of compositional data in anatomy.

BACKGROUND: Variables which describe the composition, or relative size of components, of an organism need to be analysed in an appropriate manner. METHODS: A few of the appropriate descriptive and inferential techniques have been described and applied to a number of anatomical data sets. RESULTS: When applied to data on the composition of the vastus medialis in adults, a small but significant difference in average muscle fibre type distribution was demonstrated between males and females. There was little evidence for a relationship between fibre type distribution and age over the range considered. CONCLUSIONS: Graphical displays via ternary diagrams are a simple way of illustrating compositional data simultaneously between and within groups. Numerical analysis is likely to involve transformation of original variables before standard univariate or multivariate statistical techniques can be used.

Adult↗

Issues in the meta-analysis of cluster randomized trials.

Meta-analyses involving the synthesis of evidence from cluster randomization trials are being increasingly reported. These analyses raise challenging methodologic issues beyond those raised by meta-analyses which include only individually randomized trials. In this paper we review and comment on a selected number of these issues, including problems of study heterogeneity, difficulties in estimating design effects from individual trials and the choice of statistical methods.

Cluster Analysis↗

Testing for baseline balance in clinical trials.

Once the data from a clinical trial are available for analysis it is common practice to carry out 'tests of baseline homogeneity' on prognostic covariates before proceeding to analyse the effects of treatment on outcome variables. It is argued that this practice is philosophically unsound, of no practical value and potentially misleading. Instead it is recommended that prognostic variables be identified in the trial-plan and fitted in an analysis of covariance regardless of their baseline distribution (statistical significance).

Algorithms↗

Estimation in an island model using simulation.

Estimation for an island model where mutation maintains a k-allele neutral polymorphism at a single locus on each island is considered. The likelihood of an observed sample type configuration is obtained by applying a computational algorithm analogous to Griffiths and Tavaré (Theor. Popul. Biol. 46 (1994), 131-159). This allows the computation of sampling distributions in an island model and investigation of their properties. Given a sample type configuration, the maximum likelihood estimate of the migration parameter is obtained by simulating independently the likelihood at a grid of points and, also, using a surface simulation method. The latter method generates the whole likelihood trajectory in a single application of the simulation program. An estimate of variance of the estimate of the migration parameter is obtained using the likelihood trajectory. A comparison of the maximum likelihood estimates of the gene flow between subpopulations is made with those obtained by using Wright's FST statistic.

Algorithms↗

[Quality of data provided by VESKA medical statistics: the case of the fractured proximal femur].

Within the framework of a retrospective study of the incidence of hip fractures in the canton of Vaud (Switzerland), all cases of hip fracture occurring among the resident population in 1986 and treated in the hospitals of the canton were identified from among five different information sources. Relevant data were then extracted from the medical records. At least two sources of information were used to identify cases in each hospital, among them the statistics of the Swiss Hospital Association (VESKA). These statistics were available for 9 of the 18 hospitals in the canton that participated in the study. The number of cases identified from the VESKA statistics was compared to the total number of cases for each hospital. For the 9 hospitals the number of cases in the VESKA statistics was 407, whereas, after having excluded diagnoses that were actually "status after fracture" and double entries, the total for these hospitals was 392, that is 4% less than the VESKA statistics indicate. It is concluded that the VESKA statistics provide a good approximation of the actual number of cases treated in these hospitals, with a tendency to overestimate this number. In order to use these statistics for calculating incidence figures, however, it is imperative that a greater proportion of all hospitals (50% presently in the canton, 35% nationwide) participate in these statistics.

Data Interpretation, Statistical↗

Risk assessment scales for pressure ulcers: a methodological review.

Much is written about risk-assessment scales (RASs) for pressure ulcers (PU) and their properties demonstrating that they are of limited value. Less is known about the reasons for these limitations and the scope for improvement. This review examines issues such as structure and scoring for the Norton, Waterlow and Braden scales, showing that the equal-weighting technique behind the current RASs is too simplistic and leads to limitations. It concludes that properly trained, experienced nurses should conduct PU risk assessments, whilst more robust data-driven RASs should be developed using the differential weighting scoring method together with advanced statistical techniques.

Data Interpretation, Statistical↗

Time-frequency microstructure and statistical significance of ERD and ERS.

ERD and ERS were introduced as the time courses of the average changes of energy in given frequency bands. These curves are naturally embedded in the time-frequency plane. Time-frequency density of signals energy can be estimated by means of a variety of transforms. In general, resolution of these methods depends on a priori choices of parameters regulating the tradeoff between the time and frequency resolutions. As an exception, adaptive time-frequency approximations adapt resolution to the local structures of the analyzed signal. Matching pursuit (MP) algorithm is a reliable implementation of this approach. Its application to the event-related EEG allows for a detailed presentation of the time-frequency microstructure of changes of the average energy density, as well as calculation of high-resolution maps of ERD/ERS in the time-frequency plane. However, even with such a detailed picture of the signal energy changes, their significance remains an open issue. Owing to a stochastic character of the EEG, a visible increase or decrease of energy can occur due to a pure chance or a phenomenon unrelated to the event. For a proper estimation of the statistical significance of ERD/ERS, that is, the average changes of signals energy density in relation to the reference period, we must take into account possibly non-normal distributions of energy, and, especially, the problem of multiple comparisons appearing in hypotheses related to different frequency bands and time epochs. This chapter presents and discusses a complete framework for high-resolution estimation of the ERD/ERS microstructure in the time-frequency regions, revealing statistically significant changes.

Cortical Synchronization↗

Common statistical errors in morphometry.

Morphometry is the quantitative measurement of morphological features. Data is usually obtained by probabilistic sampling techniques and is often markedly variable due to intrinsic variations in sampled specimens. Statistical analyses are required both to allow for and to control such variability. Care is needed in the analysis of morphometric data if false conclusions are to be avoided. Examination of any reasonably sized sample of publications in morphometry usually results in the detection of at least several common errors of statistical practice. Commonest errors involve statistics being carried out on untransformed percentage data, statistics on ratios, repeated multiple applications of tests designed for single comparisons, misuse of correlation and violations of statistical assumptions.

Analysis of Variance↗

Diagnosing item score patterns on a test using item response theory-based person-fit statistics.

Person-fit statistics have been proposed to investigate the fit of an item score pattern to an item response theory (IRT) model. The author investigated how these statistics can be used to detect different types of misfit. Intelligence test data were analyzed using person-fit statistics in the context of the G. Rasch (1960) model and R. J. Mokken's (1971, 1997) IRT models. The effect of the choice of an IRT model to detect misfitting item score patterns and the usefulness of person-fit statisticsfor diagnosis of misfit are discussed. Results showed that different types of person-fit statistics can be used to detect different kinds of person misfit. Parametric person-fit statistics had more power than nonparametric person-fit statistics.

Adult↗

Path model analyzed with ordinary least squares multiple regression versus LISREL.

The data of a specified path model using the variables of voice, perceived organizational support, being heard, and procedural justice were subjected to the two separate structural equation modeling analytic techniques--that of ordinary least squares regression and LISREL. A comparison of the results and differences between the analyses is discussed, with the LISREL approach being stronger from both theoretical and statistical perspectives.

Data Interpretation, Statistical↗

Continuous quality improvement in health maintenance organizations: an application of the HEDIS model.

One aspect of the Clinton Healthcare Reform programme is to assist health maintenance organizations (HMOs) in collecting and analysing data for the purpose of continuous quality improvement. The HEDIS 2.0 quality performance measurement model is currently in use and endorsed by the National Committee for Quality Assurance (NCQA). Outlines a process using HEDIS 2.0 by which an HMO can identify crucial problem areas and track the success of the solution process. Discusses the use of other relevant statistical tools.

Data Interpretation, Statistical↗

Smooth tests for the zero-inflated poisson distribution.

In this article we construct three smooth goodness-of-fit tests for testing for the zero-inflated Poisson (ZIP) distribution against general smooth alternatives in the sense of Neyman. We apply our tests to a data set previously claimed to be ZIP distributed, and show that the ZIP is not a good model to describe the data. At rejection of the null hypothesis of ZIP, the individual components of the test statistic, which are directly related to interpretable parameters in a smooth model, may be used to gain insight into an alternative distribution.

Animals↗

Consistency of pseudolikelihood estimation of fully visible Boltzmann machines.

A Boltzmann machine is a classic model of neural computation, and a number of methods have been proposed for its estimation. Most methods are plagued by either very slow convergence or asymptotic bias in the resulting estimates. Here we consider estimation in the basic case of fully visible Boltzmann machines. We show that the old principle of pseudolikelihood estimation provides an estimator that is computationally very simple yet statistically consistent.

Algorithms↗

A nurse-statistician reanalyzes data from the Rosa therapeutic touch study.

This article presents a reanalysis of data used to support the work of Emily Rosa's Therapeutic Touch (TT) science fair project published as an article in the Journal of the American Medical Association (JAMA) in 1998. The purpose of this article is to take a closer look at the assumptions, data, statistical procedures, and conclusions of the JAMA article. This is accomplished by focusing on (1) the conclusion that there was no overall effect of TT, (2) the conclusion that TT practitioners did not perform better depending on which hand was used, and (3) the assumptions about the capability of Rosa's experiment to validate an existing skill. Reanalysis of the Rosa data suggests contradictions to the authors' conclusions. Based on this reanalysis, the authors' recommendations against the use of TT can and should be challenged because of inappropriate design and analysis as well as incorrect statistical assumptions and conclusions.

Confidence Intervals↗