Mixture of measurement errors and their impact on parameter inferences

A mixture measurement error model built upon skew normal distributions and normal distributions is developed to evaluate various impacts of measurement errors to parameter inferences in logistic regressions. Data generated from survey questionnaires are usually error contaminated. We consider two types of errors: person-specific bias and random errors. Person-specific bias is modelled using skew normal distribution, and the distribution of random errors is described by a normal distribution. Intensive simulations are conducted to evaluate the contribution of each component in the mixture to outcomes of interest. The proposed method is then applied to a questionnaire data set generated from a neural tube defect study. Simulation results and real data application indicate that ignoring measurement errors or misspecifying measurement error components can both produce misleading results, especially when measurement errors are actually skew distributed. The inferred parameters can be attenuated or inflated depending on how the measurement error components are specified. We expect the findings will self-explain the importance of adjusting measurement errors and thus benefit future data collection effort.     

Gauging the Impact of Growing Nonresponse on Estimates from a National RDD Telephone Survey

Declining contact and cooperation rates in random digit dial(RDD) national telephone surveys raise serious concerns aboutthe validity of estimates drawn from such research. While researchin the 1990s indicated that nonresponse bias was relativelysmall, response rates have continued to fall since then. Thecurrent study replicates a 1997 methodological experiment thatcompared results from a "Standard" 5-day survey employing thePew Research Center’s usual methodology with results froma "Rigorous" survey conducted over a much longer field periodand achieving a significantly higher response rate. As withthe 1997 study, there is little to suggest that unit nonresponsewithin the range of response rates obtained seriously threatensthe quality of survey estimates. In 77 out of 84 comparableitems, the two surveys yielded results that were statisticallyindistinguishable. While the "Rigorous" study respondents tendedto be somewhat less politically engaged, they did not reportconsistently different behaviors or attitudes on other kindsof questions. With respect to sample composition, the Standardsurvey was closely aligned with estimates from the U.S. Censusand other large government surveys on most variables. We extendour analysis of nonresponse to include comparisons with thehardest-to-reach respondents and with respondents who terminatedthe interview prior to completion.     

Shipman's statistical legacy

Harold Shipman, who in January committed suicide in prison, has become notorious the world over as one of the most prolific serial killers of all time. His case has also seriously dented public confidence in doctors. David Spiegelhalter and Nicky Best explain how industrial quality control techniques could be adapted to signal when death rates among a doctor's patients are surprisingly high, and the tricky issues that would arise in implementing such a monitoring system.     

GOODNESS-OF-FIT AND DISCORDANCY TESTS FOR SAMPLES FROM THE WATSON DISTRIBUTION ON THE SPHERE

The only parametric model in current use for axial data from a rotationally symmetric bipolar or girdle distribution on the sphere is the Watson distribution. This paper develops methods for evaluating the model as a fit to data using graphical and formal goodness-of-fit tests, and tests of discordancy.     

The value of the aggregate data approach in meta-analysis with time-to-event outcomes

Collecting individual patient data has been described as the 'gold standard' for undertaking meta-analysis. If studies involve time-to-event outcomes, conducting a meta-analysis based on aggregate data can be problematical. Two meta-analyses of randomized controlled trials with time-to-event outcomes are used to illustrate the practicality and value of several proposed methods to obtain summary statistic estimates. In the first example the results suggest that further effort should be made to find unpublished trials. In the second example the use of aggregate data for trials where no individual patient data have been supplied allows the totality of evidence to be assessed and indicates previously unrecognized heterogeneity.     

WinBUGS - A Bayesian modelling framework: Concepts,structure, and extensibility

WinBUGS is a fully extensible modular framework for constructing and analysing Bayesian full probability models. Models may be specified either textually via the BUGS language or pictorially using a graphical interface called DoodleBUGS. WinBUGS processes the model specification and constructs an object-oriented representation of the model. The software offers a user-interface, based on dialogue boxes and menu commands, through which the model may then be analysed using Markov chain Monte Carlo techniques. In this paper we discuss how and why various modern computing concepts, such as object-orientation and run-time linking, feature in the software's design. We also discuss how the framework may be extended. It is possible to write specific applications that form an apparently seamless interface with WinBUGS for users with specialized requirements. It is also possible to interface with WinBUGS at a lower level by incorporating new object types that may be used by WinBUGS without knowledge of the modules in which they are implemented. Neither of these types of extension require access to, or even recompilation of, the WinBUGS source-code.     

Radical Normals: The Moral Career of Straight Parents as Public Advocates for Their Gay Children

Sociological research has examined straight parents in “traditional” family arrangements who become gay rights activists, but pays insufficient attention to how this puzzling identity comes into being. Drawn from observations and interviews of parents participating in a local chapter of Parents and Friends of Lesbians and Gays (PFLAG) (2009 to 2010), this paper analyzes the parenting activities undertaken by straight parents of gay children as a moral career, involving stages of acceptance that can lead to eventual public advocacy. Paradoxically, these parents become radical normals through these stages; that is to say, they “do” the work of parenting by becoming gay rights advocates, motivated by commitments to conventional imperatives of loving and supporting a child. Using the conceptual scaffolding of the moral career, this paper identifies the mechanisms that move parents through these different career stages.     

Extended Analysis of At Least Partially Ordered Multi‐factor ANOVA

For multifactor experimental designs in which the levels of at least one of the factors are ordered we show how to construct components that provide a deep nonparametric scrutiny of the data. The components assess generalised correlations and the resulting tests include and extend the Page and umbrella tests. Application of the tests described is straightforward. Orthonormal polynomials on the ANOVA responses and the factors are required and the formulae needed are given subsequently. These depend on the moments of the responses and of each factor and are easily calculated. Products of at least two of these orthonormal polynomials are then used as inputs into standard ANOVA routines. For example, using the first order orthonormal polynomial on factor A and the second order orthonormal polynomial on the ANOVA response will assess if, with increasing levels of factor A there is an umbrella response with either an increase and then a decrease or a decrease and then an increase.     

GOODNESS-OF-FIT TESTS FOR FISHER'S DISTRIBUTION ON THE SPHERE

A set of three goodness-of-fit procedures is proposed to investigate the adequacy of fit of Fisher's distribution on the sphere as a model for a given sample of spherical data. The procedures are all based on standard tests using the empirical distribution function.