Montana cooperative snow survey data of federal-state-private cooperative snow surveys.

Folded map in pocket.

Flint - Genesee County transportation study : cross-tabulations of survey data.

Mode of access: Internet.

Food and health expenditure patterns in urban and rural Ecuador : analysis of household budget survey data /

"July 1, 1984."

Catalogue of IGY all-sky camera data for United States stations. IGY project no. 45.3. NSF grant no. Y/45.3/240.

Mode of access: Internet.

Space-Time Smoothing Models for Surveillance and Complex Survey Data

Thesis (Ph.D.)--University of Washington, 2016-06

Utilising survey data to inform public policy: Comparison of the cost-effectiveness of treatment of ten mental disorders

Background Mental health survey data are now being used proactively to decide how the burden of disease might best be reduced. Aims To study the cost-effectiveness of current and optimal treatments for mental disorders and the proportion of burden avertable by each. Method Data for three affective, four anxiety and two alcohol use disorders and for schizophrenia were compared in terms of cost, burden averted and efficiency of current and optimal treatment. We then calculated the burden unavertable given current knowledge. The unit of health gain was a reduction in the years lived with disability (YLDs). Results Summing across all disorders, current treatment averted 13% of the burden, at an average cost of AUS$30 000 per YLD gained. Optimal treatment at current coverage could avert 20% of the burden, at an average cost of AUS$18 000 per YLD gained. Optimal treatment at optimal coverage could avert 28% of the burden, at AUS$16 000 per YLD gained. Sixty per cent of the burden of mental disorders was deemed to be unavertable. Conclusions The efficiency of treatment varied more than tenfold across disorders. Although coverage of some of the more efficient treatments should be extended, other factors justify continued use of less-efficient treatments for some disorders. Declaration of interest None. Funding detailed in Acknowledgements.

Assessing the quality of risk factor survey data: lessons from the WHO MONICA Project

Background and purpose Survey data quality is a combination of the representativeness of the sample, the accuracy and precision of measurements, data processing and management with several subcomponents in each. The purpose of this paper is to show how, in the final risk factor surveys of the WHO MONICA Project, information on data quality were obtained, quantified, and used in the analysis. Methods and results In the WHO MONICA (Multinational MONItoring of trends and determinants in CArdiovascular disease) Project, the information about the data quality components was documented in retrospective quality assessment reports. On the basis of the documented information and the survey data, the quality of each data component was assessed and summarized using quality scores. The quality scores were used in sensitivity testing of the results both by excluding populations with low quality scores and by weighting the data by its quality scores. Conclusions Detailed documentation of all survey procedures with standardized protocols, training, and quality control are steps towards optimizing data quality. Quantifying data quality is a further step. Methods used in the WHO MONICA Project could be adopted to improve quality in other health surveys.

Methods for Categorical Longitudinal Survey Data: Understanding Employment Status of Australian Women

Many variables that are of interest in social science research are nominal variables with two or more categories, such as employment status, occupation, political preference, or self-reported health status. With longitudinal survey data it is possible to analyse the transitions of individuals between different employment states or occupations (for example). In the statistical literature, models for analysing categorical dependent variables with repeated observations belong to the family of models known as generalized linear mixed models (GLMMs). The specific GLMM for a dependent variable with three or more categories is the multinomial logit random effects model. For these models, the marginal distribution of the response does not have a closed form solution and hence numerical integration must be used to obtain maximum likelihood estimates for the model parameters. Techniques for implementing the numerical integration are available but are computationally intensive requiring a large amount of computer processing time that increases with the number of clusters (or individuals) in the data and are not always readily accessible to the practitioner in standard software. For the purposes of analysing categorical response data from a longitudinal social survey, there is clearly a need to evaluate the existing procedures for estimating multinomial logit random effects model in terms of accuracy, efficiency and computing time. The computational time will have significant implications as to the preferred approach by researchers. In this paper we evaluate statistical software procedures that utilise adaptive Gaussian quadrature and MCMC methods, with specific application to modeling employment status of women using a GLMM, over three waves of the HILDA survey.

Teaching Ethics Using Tax Evasion Survey Data as a Case Study

This paper briefly discusses the three views that have emerged over the centuries on the ethics of tax evasion, then summarizes the results of several opinion surveys that were conducted on the topic. The paper concludes with a discussion of how these study results may be used in the classroom.

A Comparative Study of Concurrent Acoustic and Diver Survey Data, and Fish Community Descriptions of a High Latitude Coral Reef, Florida, USA

Fisheries independent data on relatively unstudied nekton communities were used to explore the efficacy of new tools to be applied in the investigation of shallow coastal coral reef habitats. These data obtained through concurrent diver visual and acoustic surveys provided descriptions of spatial community distribution patterns across seasonal temporal scales in a previously undocumented region. Fish density estimates by both diver and acoustic methodologies showed a general agreement in ability to detect distributional patterns across reef tracts, though magnitude of density estimates were different. Fish communities in southeastern Florida showed significant trends in spatial distribution and seasonal abundance, with higher estimates of biomass obtained in the dry season. Further, community composition shifted across reef tracts and seasons as a function of the movements of several key reef species.

Assessing consistency of fish survey data : uncertainties in the estimation of mackerel icefish (Champsocephalus gunnari) abundance at South Georgia

Acknowledgments The authors wish to thank the crews, fishermen and scientists who conducted the various surveys from which data were obtained, and Mark Belchier and Simeon Hill for their contributions. This work was supported by the Government of South Georgia and South Sandwich Islands. Additional logistical support provided by The South Atlantic Environmental Research Institute with thanks to Paul Brickle. Thanks to Stephen Smith of Fisheries and Oceans Canada (DFO) for help in constructing bootstrap confidence limits. Paul Fernandes receives funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland), and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions. We also wish to thank two anonymous referees for their helpful suggestions on earlier versions of this manuscript.

Drivers' Behavior at Railroad Grade Crossings: Before and After Safety Campaign, HR-335, Survey Data Summaries, 1992

Summaries of the data gathered for this project.