Missing in space: An evaluation of imputation methods for missing data in spatial analysis of risk factors for type II diabetes

Background Spatial analysis is increasingly important for identifying modifiable geographic risk factors for disease. However, spatial health data from surveys are often incomplete, ranging from missing data for only a few variables, to missing data for many variables. For spatial analyses of health outcomes, selection of an appropriate imputation method is critical in order to produce the most accurate inferences. Methods We present a cross-validation approach to select between three imputation methods for health survey data with correlated lifestyle covariates, using as a case study, type II diabetes mellitus (DM II) risk across 71 Queensland Local Government Areas (LGAs). We compare the accuracy of mean imputation to imputation using multivariate normal and conditional autoregressive prior distributions. Results Choice of imputation method depends upon the application and is not necessarily the most complex method. Mean imputation was selected as the most accurate method in this application. Conclusions Selecting an appropriate imputation method for health survey data, after accounting for spatial correlation and correlation between covariates, allows more complete analysis of geographic risk factors for disease with more confidence in the results to inform public policy decision-making.

Changing travel patterns and journeys to health services in Great Britain 1985-2012: An examination health service utilisation using the National Travel Survey

Background This paper examines changing patterns in the utilisation and geographic access to health services in Great Britain using National Travel Survey data (1985-2012). The National Travel Survey (NTS) is a series of household surveys designed to provide data on personal travel and monitor changes in travel behaviour over time. The utilisation rate was derived using the proportion of journeys made to access health services. Geographic access was analysed by separating the concept into its accessibility and mobility dimensions. Methods Variables from the PSU, households, and individuals datasets were used as explanatory variables. Whereas, variables extracted from the journeys dataset were used as dependent variables to identify patterns of utilisation i.e. the proportion of journeys made by different groups to access health facilities in a particular journey distance or time band or by mode of transport; and geographic access to health services. A binary logistic regression analysis was conducted to identify the utilisation rate over the different time periods between different groups. This analysis shows the Odds Ratios (ORs) for different groups making a trip to utilise health services compared to their respective counterparts. Linear multiple regression analyses were conducted to then identify patterns of change in the accessibility and mobility level. Results Analysis of the data has shown that that journey distances to health facilities were signi fi cantly shorter and also gradually reduced over the period in question for Londoners, females, those without a car or on low incomes, and older people. Although rates of utilisation of health services we re Oral Abstracts / Journal of Transport & Health 2 (2015) S5 – S63 S43 signi fi cantly lower because of longer journey times. These fi ndings indicate that the rate of utilisation of health services largely depends on mobility level although previous research studies have traditionally overlooked the mobility dimension. Conclusions This fi nding, therefore, suggests the need to improve geographic access to services together with an enhanced mobility option for disadvantaged groups in order for them to have improved levels of access to health facilities. This research has also found that the volume of car trips to health services also increased steadily over the period 1985-2012 while all other modes accounted for a smaller number of trips. However, it is dif fi cult to conclude from this research whether this increase in the volume of car trips was due to a lack of alternative transport or due to an increase in the level of car-ownership.

Estimating equations with nonignorably missing response data

Troxel, Lipsitz, and Brennan (1997, Biometrics 53, 857-869) considered parameter estimation from survey data with nonignorable nonresponse and proposed weighted estimating equations to remove the biases in the complete-case analysis that ignores missing observations. This paper suggests two alternative modifications for unbiased estimation of regression parameters when a binary outcome is potentially observed at successive time points. The weighting approach of Robins, Rotnitzky, and Zhao (1995, Journal of the American Statistical Association 90, 106-121) is also modified to obtain unbiased estimating functions. The suggested estimating functions are unbiased only when the missingness probability is correctly specified, and misspecification of the missingness model will result in biases in the estimates. Simulation studies are carried out to assess the performance of different methods when the covariate is binary or normal. For the simulation models used, the relative efficiency of the two new methods to the weighting methods is about 3.0 for the slope parameter and about 2.0 for the intercept parameter when the covariate is continuous and the missingness probability is correctly specified. All methods produce substantial biases in the estimates when the missingness model is misspecified or underspecified. Analysis of data from a medical survey illustrates the use and possible differences of these estimating functions.

100 Years of U.S. Consumer Spending: Data for the Nation, New York City, and Boston

[From Preface] The Consumer Expenditure Survey is among the oldest publications of the Bureau of Labor Statistics. With information on the expenditures, incomes, and demographic characteristics of households, the survey documents the spending patterns and economic status of American families. This report offers a new approach to the use of Consumer Expenditure Survey data. Normally, the survey presents an indepth look at American households at a specific point in time, the reference period being a calendar year. Here, the authors use consumer expenditure data longitudinally and draw on information from decennial census reports to present a 100-year history of significant changes in consumer spending, economic status, and family demographics in the country as a whole, as well as in New York City and Boston.

Modelling the distribution and relative abundance of feral camels in the Northern Territory using count data

The objectives of this study were to predict the potential distribution, relative abundance and probability of habitat use by feral camels in southern Northern Territory. Aerial survey data were used to model habitat association. The characteristics of ‘used’ (where camels were observed) v. ‘unused’ (pseudo-absence) sites were compared. Habitat association and abundance were modelled using generalised additive model (GAM) methods. The models predicted habitat suitability and the relative abundance of camels in southern Northern Territory. The habitat suitability maps derived in the present study indicate that camels have suitable habitat in most areas of southern Northern Territory. The index of abundance model identified areas of relatively high camel abundance. Identifying preferred habitats and areas of high abundance can help focus control efforts.

Do Households Have Rational Expectations on Future Consumption? Evidence from the Finnish Consumer Survey

Ever since its initial introduction some fifty years ago, the rational expectations paradigm has dominated the way economic theory handles uncertainty. The main assertion made by John F. Muth (1961), seen by many as the father of the paradigm, is that expectations of rational economic agents should essentially be equal to the predictions of relevant economic theory, since rational agents should use information available to them in an optimal way. This assumption often has important consequences on the results and interpretations of the models where it is applied. Although the rational expectations assumption can be applied to virtually any economic theory, the focus in this thesis is on macroeconomic theories of consumption, especially the Rational Expectations–Permanent Income Hypothesis proposed by Robert E. Hall in 1978. The much-debated theory suggests that, assuming that agents have rational expectations on their future income, consumption decisions should follow a random walk, and the best forecast of future consumption level is the current consumption level. Then, changes in consumption are unforecastable. This thesis constructs an empirical test for the Rational Expectations–Permanent Income Hypothesis using Finnish Consumer Survey data as well as various Finnish macroeconomic data. The data sample covers the years 1995–2010. Consumer survey data may be interpreted to directly represent household expectations, which makes it an interesting tool for this particular test. The variable to be predicted is the growth of total household consumption expenditure. The main empirical result is that the Consumer Confidence Index (CCI), a balance figure computed from the most important consumer survey responses, does have statistically significant predictive power over the change in total consumption expenditure. The history of consumption expenditure growth itself, however, fails to predict its own future values. This indicates that the CCI contains some information that the history of consumption decisions does not, and that the consumption decisions are not optimal in the theoretical context. However, when conditioned on various macroeconomic variables, the CCI loses its predictive ability. This finding suggests that the index is merely a (partial) summary of macroeconomic information, and does not contain any significant private information on consumption intentions of households not directly deductible from the objective economic variables. In conclusion, the Rational Expectations–Permanent Income Hypothesis is strongly rejected by the empirical results in this thesis. This result is in accordance with most earlier studies conducted on the topic.

Average Overlap for Clustering Incomplete Data using Symmetric Non-Negative Matrix Factorization

Clustering techniques which can handle incomplete data have become increasingly important due to varied applications in marketing research, medical diagnosis and survey data analysis. Existing techniques cope up with missing values either by using data modification/imputation or by partial distance computation, often unreliable depending on the number of features available. In this paper, we propose a novel approach for clustering data with missing values, which performs the task by Symmetric Non-Negative Matrix Factorization (SNMF) of a complete pair-wise similarity matrix, computed from the given incomplete data. To accomplish this, we define a novel similarity measure based on Average Overlap similarity metric which can effectively handle missing values without modification of data. Further, the similarity measure is more reliable than partial distances and inherently possesses the properties required to perform SNMF. The experimental evaluation on real world datasets demonstrates that the proposed approach is efficient, scalable and shows significantly better performance compared to the existing techniques.

The distribution and size composition of finfish, American lobster, and long-finned squid in Long Island Sound based on the Connecticut Fisheries Division Bottom Trawl Survey, 1984–1994

The distribution, abundance, and length composition of marine finfish, lobster, and squid in Long Island Sound were examined relative to season and physical features of the Sound, using Connecticut Department of Environmental Protection trawl survey data collected from 1984 to 1994. The following are presented: seasonal distribution maps for 59 species, abundance indices for 41 species, and length frequencies for 26 species. In addition, a broader view of habitat utilization in the Sound was examined by mapping aggregated catches (total catch per tow, demersal catch per tow, and pelagic catch per tow) and by comparing species richness and mean aggregate catch/tow by analysis of variance (ANOVA) among eight habitat types defined by depth interval and bottom type. For many individual species, seasonal migration patterns and preference for particular areas within Long Island Sound were evident. The aggregate distribution maps show that overall abundance was lower in the eastern Sound than the central and western portions. Demersal and pelagic temporal abundance show opposite trends—demersals were abundant in spring and declined through summer and fall, whereas pelagic abundance was low in spring and increased into fall. The analysis of habitat types revealed significant differences for both species richness and mean catch per tow. Generally, species richness was highest in habitats within the central area of the Sound and lowest in eastern habitats. The aggregate mean catch was highest in the western and central habitats, and declined eastward. (PDF file contains 199 pages.)

Observational and theoretical advances in cosmological foreground emission

Observational and theoretical work towards the separation of foreground emission from the cosmic microwave background is described. The bulk of this work is in the design, construction, and commissioning of the C-Band All-Sky Survey (C-BASS), an experiment to produce a template of the Milky Way Galaxy's polarized synchrotron emission. Theoretical work is the derivation of an analytical approximation to the emission spectrum of spinning dust grains.

The performance of the C-BASS experiment is demonstrated through a preliminary, deep survey of the North Celestial Pole region. A comparison to multiwavelength data is performed, and the thermal and systematic noise properties of the experiment are explored. The systematic noise has been minimized through careful data processing algorithms, implemented both in the experiment's Field Programmable Gate Array (FPGA) based digital backend and in the data analysis pipeline. Detailed descriptions of these algorithms are presented.

The analytical function of spinning dust emission is derived through the application of careful approximations, with each step tested against numerical calculations. This work is intended for use in the parameterized separation of cosmological foreground components and as a framework for interpreting and comparing the variety of anomalous microwave emission observations.

Removing observational noise from fisheries-independent time series data using ARIMA models

Abundance indices derived from fishery-independent surveys typically exhibit much higher interannual variability than is consistent with the within-survey variance or the life history of a species. This extra variability is essentially observation noise (i.e. measurement error); it probably reflects environmentally driven factors that affect catchability over time. Unfortunately, high observation noise reduces the ability to detect important changes in the underlying population abundance. In our study, a noise-reduction technique for uncorrelated observation noise that is based on autoregressive integrated moving average (ARIMA) time series modeling is investigated. The approach is applied to 18 time series of finfish abundance, which were derived from trawl survey data from the U.S. northeast continental shelf. Although the a priori assumption of a random-walk-plus-uncorrelated-noise model generally yielded a smoothed result that is pleasing to the eye, we recommend that the most appropriate ARIMA model be identified for the observed time series if the smoothed time series will be used for further analysis of the population dynamics of a species.

Final report of the Fisheries Catch Assessment Survey in the Ugandan waters of Lake Victoria for the May 2011 survey

This report presents findings of the CAS conducted in the Ugandan waters of Lake Victoria in May 2011. The results of the previous eleven CASs conducted under the IFMP of the LVFO programme in July, August, September and November 2005; in March, August and December 2006; in March and August 2007; in February and December 2008; and March 2010 are included to show the emerging trends. The report also presents annual catch estimates for the Ugandan part of the lake from 2005 to 2011. Through these CASs, information is building up to show the emerging picture of fish production in the Ugandan waters of the lake. Similar surveys are conducted in the Kenyan and Tanzanian parts of the lake, which provide the lake wide perspective of fisheries production but this time not simultaneously as under the LVFO effort due to different sources and timing of funding. These data can now be utilised together with other Resource and Socio-economic Monitoring survey data for a stock assessment of the lake to provide a firm basis for planning and management of the fisheries resources.

A report of the Fisheries Catch Assessment Survey in the Ugandan waters of Lake Victoria for the August 2006 survey

This report presents findings of the CAS conducted in the Ugandan waters of Lake Victoria in August 2006. The results of the previous five CASs conducted under the same programme in July, August, September, and November 2005, and March 2006 are included to show the emerging trends. The results of the preceding CASs, which were hitherto estimated using raising factors from the 2004 Frame survey data, are updated in this report using raising factors based on the 2006 Frame survey data. Through regular CASs, information is building up to show the new picture of fish production in the Ugandan waters of the lake which is based on field observations. Similar surveys are simultaneously conducted in the Kenyan and Tanzanian parts of the lake which provide the lake wide perspective of fisheries production.

Cross-cultural dimensions of meaning in the evaluation of events in world history? Perceptions of historical calamities and progress in cross-cultural data from 30 societies

The universality versus culture specificity of quantitative evaluations (negative-positive) of 40 events in world history was addressed using World History Survey data collected from 5,800 university students in 30 countries/societies. Multidimensional scaling using generalized procrustean analysis indicated poor fit of data from the 30 countries to an overall mean configuration, indicating lack of universal agreement as to the associational meaning of events in world history. Hierarchical cluster analysis identified one Western and two non-Western country clusters for which adequate multidimensional fit was obtained after item deletions. A two-dimensional solution for the three country clusters was identified, where the primary dimension was historical calamities versus progress and a weak second dimension was modernity versus resistance to modernity. Factor analysis further reduced the item inventory to identify a single concept with structural equivalence across cultures, Historical Calamities, which included man-made and natural, intentional and unintentional, predominantly violent but also nonviolent calamities. Less robust factors were tentatively named as Historical Progress and Historical Resistance to Oppression. Historical Calamities and Historical Progress were at the individual level both significant and independent predictors of willingness to fight for one’s country in a hierarchical linear model that also identified significant country-level variation in these relationships. Consensus around calamity but disagreement as to what constitutes historical progress is discussed in relation to the political culture of nations and lay perceptions of history as catastrophe.

Going Global: planning the next 80 years of the Continuous Plankton Recorder Survey

Going Global: planning the next 80 years of the Continuous Plankton Recorder Survey. Operated by the Sir Alister Hardy Foundation for Ocean Science (SAHFOS), the Continuous Plankton Recorder (CPR) survey is the world’s largest, sampling 4 ocean basins, and longest running (since 1931) plankton biodiversity monitoring programme. Having sampled enough miles to circumnavigate the globe over 200 times, the CPR database houses over 2.5 million entries, describing the distribution of 500 phytoplankton and zooplankton taxa. Routinely sampling in the Arctic, Atlantic, Pacific and Southern Oceans, the survey analyses 4000 samples yearly. Data collected from these samples are made freely available for bona fide scientific purposes. The CPR survey data is used to generate a better understanding of changes in the plankton and to date some 1000 papers have been published on plankton biodiversity. This year sees the 80th anniversary of the CPR survey and to celebrate and build upon this unique monitoring programme, SAHFOS intends to further develop its global plankton perspective. Work will be extended into the South Atlantic and Indian Ocean and an international partnership with complementary surveys in Australia, Canada, America, Japan and South Africa will be implemented. The Digital Object will describe the CPR survey using compilations made by Plymouth Art College and BBC film footage.

A fast hybrid algorithm for exoplanetary transit searches

We present a fast and efficient hybrid algorithm for selecting exoplanetary candidates from wide-field transit surveys. Our method is based on the widely used SysRem and Box Least-Squares (BLS) algorithms. Patterns of systematic error that are common to all stars on the frame are mapped and eliminated using the SysRem algorithm. The remaining systematic errors caused by spatially localized flat-fielding and other errors are quantified using a boxcar-smoothing method. We show that the dimensions of the search-parameter space can be reduced greatly by carrying out an initial BLS search on a coarse grid of reduced dimensions, followed by Newton-Raphson refinement of the transit parameters in the vicinity of the most significant solutions. We illustrate the method's operation by applying it to data from one field of the SuperWASP survey, comprising 2300 observations of 7840 stars brighter than V = 13.0. We identify 11 likely transit candidates. We reject stars that exhibit significant ellipsoidal variations caused indicative of a stellar-mass companion. We use colours and proper motions from the Two Micron All Sky Survey and USNO-B1.0 surveys to estimate the stellar parameters and the companion radius. We find that two stars showing unambiguous transit signals pass all these tests, and so qualify for detailed high-resolution spectroscopic follow-up.