The Experts below are selected from a list of 315 Experts worldwide ranked by ideXlab platform
Reka Gustafson - One of the best experts on this subject based on the ideXlab platform.
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Impact of Statistical Adjustment for frequency of venue attendance in a venue-based survey of men who have sex with men.
American journal of epidemiology, 2013Co-Authors: Paul Gustafson, Mark Gilbert, Michelle Xia, Warren Michelow, Wayne Robert, Terry Trussler, Marissa Mcguire, Dana Paquette, David M. Moore, Reka GustafsonAbstract:Venue sampling is a common sampling method for populations of men who have sex with men (MSM); however, men who visit venues frequently are more likely to be recruited. While Statistical Adjustment methods are recommended, these have received scant attention in the literature. We developed a novel approach to adjust for frequency of venue attendance (FVA) and assess the impact of associated bias in the ManCount Study, a venue-based survey of MSM conducted in Vancouver, British Columbia, Canada, in 2008-2009 to measure the prevalence of human immunodeficiency virus and other infections and associated behaviors. Sampling weights were determined from an abbreviated list of questions on venue attendance and were used to adjust estimates of prevalence for health and behavioral indicators using a Bayesian, model-based approach. We found little effect of FVA Adjustment on biological or sexual behavior indicators (primary outcomes); however, Adjustment for FVA did result in differences in the prevalence of demographic indicators, testing behaviors, and a small number of additional variables. While these findings are reassuring and lend credence to unadjusted prevalence estimates from this venue-based survey, Adjustment for FVA did shed important insights on MSM subpopulations that were not well represented in the sample.
Benoit De Thoisy - One of the best experts on this subject based on the ideXlab platform.
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estimation of the nesting season of marine turtles from incomplete data Statistical Adjustment of a sinusoidal function
Animal Conservation, 2006Co-Authors: Nicolas Gratiot, Julien Gratiot, Laurent Kelle, Benoit De ThoisyAbstract:Because of logistical and financial constraints, nest counts of marine turtles are often limited in time and space. To overcome this difficulty, we developed a numerical model that fits the seasonal pattern of marine turtles nesting from complete or fragmented datasets. The duration of the main nesting season, the position and amplitude of its maximum as well as the residual number of nests, outside of the main season are obtained numerically by a least square Adjustment. For the seven complete time series at our disposal (Dermochelys coriacea and Lepidochelys olivacea turtles, coast of French Guiana), the model reproduces the seasonal pattern with a correlation of r≥0.97. When applied on a fragmented dataset, the model accuracy depends on the duration and on the temporal distribution of the monitoring (effort equally distributed during the entire season or concentrated on a part of it only). As a result of this study, we clearly advocate a strategy of monitoring distributed all over the nesting season. Following this recommendation, the model estimates the annual number of nests with a median error lower than 10% when considering only 50 days of monitoring.
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Estimation of the nesting season of marine turtles from incomplete data: Statistical Adjustment of a sinusoidal function
Animal Conservation, 2006Co-Authors: Nicolas Gratiot, Julien Gratiot, Laurent Kelle, Benoit De ThoisyAbstract:International audienceBecause of logistical and financial constraints, nest counts of marine turtles are often limited in time and space. To overcome this difficulty, we developed a numerical model that fits the seasonal pattern of marine turtles nesting from complete or fragmented datasets. The duration of the main nesting season, the position and amplitude of its maximum as well as the residual number of nests, outside of the main season are obtained numerically by a least square Adjustment. For the seven complete time series at our disposal (Dermochelys coriacea and Lepidochelys olivacea turtles, coast of French Guiana), the model reproduces the seasonal pattern with a correlation of r≥0.97. When applied on a fragmented dataset, the model accuracy depends on the duration and on the temporal distribution of the monitoring (effort equally distributed during the entire season or concentrated on a part of it only). As a result of this study, we clearly advocate a strategy of monitoring distributed all over the nesting season. Following this recommendation, the model estimates the annual number of nests with a median error lower than 10% when considering only 50 days of monitoring
Terry L Thomas - One of the best experts on this subject based on the ideXlab platform.
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impact of sociodemographic factors hormone receptor status and tumor grade on ethnic differences in tumor stage and size for breast cancer in us women
American Journal of Epidemiology, 2002Co-Authors: Barry A Miller, Benjamin F Hankey, Terry L ThomasAbstract:The importance of sociodemographic factors and tumor biomarkers in explaining ethnic differences in tumor stage and size at diagnosis was investigated in over 106,000 female breast cancer patients reported during 1992-1996 from 11 US population-based cancer registries. Japanese and non-Hispanic White women tended to be diagnosed at an earlier stage, with smaller diameter tumors and with a lower tumor grade than women from seven other ethnic groups. Statistical Adjustment for individual- and group-level sociodemographic factors produced 50-80% reductions in the odds ratios for distant (vs. localized) stage and larger (vs. <1 cm) tumor size among Black women and Hispanic women. These factors also helped to account for tumor stage and size variation among most other ethnic groups. Consideration of hormone receptor status and tumor grade had little effect on the ethnic patterns. Although small, elevated odds ratios remained for some groups, our results suggest that sociodemographic factors accounted for many of the observed ethnic differences in breast cancer stage and tumor size at the time of diagnosis. Because most of the sociodemographic variables were aggregate measures, it is possible that residual confounding by socioeconomic position could explain the persistence of slightly elevated odds ratios in some ethnic groups.
Jed Friedman - One of the best experts on this subject based on the ideXlab platform.
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family size and children s education in vietnam
Demography, 1998Co-Authors: John Knodel, Jed FriedmanAbstract:Data from the nationally representative 1994 Inter-Censal Demographic Survey are used to examine the association between family size and children s schooling in Vietnam. The data provide information on several education measures for all children over age 10, including children no longer residing in the household. Although a clear inverse bivariate association between family size and children s school attendance and educational attainment is evident, multivariate analysis controlling for urban/rural residence, region, parents’ education, household wealth, and child’s age, reveals that much of this association, especially that predicting educational attainment, is attributable to these other influences. Moreover, much of the effect that remains after Statistical Adjustment for the other influences is seen mainly at the largest family sizes. We consider the implications of these findings for current population policy in Vietnam and the possible features of the Vietnamese context that might account for the modest association.
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Family size and children’s education in Vietnam
Demography, 1998Co-Authors: John Knodel, Jed FriedmanAbstract:Data from the nationally representative 1994 Inter-Censal Demographic Survey are used to examine the association between family size and children s schooling in Vietnam. The data provide information on several education measures for all children over age 10, including children no longer residing in the household. Although a clear inverse bivariate association between family size and children s school attendance and educational attainment is evident, multivariate analysis controlling for urban/rural residence, region, parents’ education, household wealth, and child’s age, reveals that much of this association, especially that predicting educational attainment, is attributable to these other influences. Moreover, much of the effect that remains after Statistical Adjustment for the other influences is seen mainly at the largest family sizes. We consider the implications of these findings for current population policy in Vietnam and the possible features of the Vietnamese context that might account for the modest association.
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Family size and childrens education in Vietnam.
1996Co-Authors: John Knodel, Jed FriedmanAbstract:The government of Vietnam gives high priority to the promotion of lower fertility to reduce the rate of population growth and to increase schooling. This study examines the association between family size and childrens school enrollment in Vietnam. Data are obtained from the 1994 Intercensal Demographic Survey among a nationally representative sample of currently married women 15-49 years old and children 10-24 years old. Findings indicate that current enrollments among children 10-14 years 15-19 years and 20-24 years old were strongly associated with each separate independent variable: family size region parents education and household wealth. Statistical Adjustment reduced the strength of the relationship. Family size remained "reasonably consistently" negatively related to each age group enrolled without controls for other factors. The enrollment of children 15-19 years old was particularly enhanced by small family size. Urban residence effects were eliminated and regional differences reduced when controls for other factors were included in the model. In the multivariate analysis increased levels of parents education had a strong positive effect and children of parents with no schooling were particularly disadvantaged. Increased wealth was positively associated with higher enrollment of all three age groups particularly for primary enrollment. Girls tended to be more disadvantaged than boys. Family size in both urban and rural areas appeared to limit the level of schooling.
Anca Brookshaw - One of the best experts on this subject based on the ideXlab platform.
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Statistical Adjustment, calibration and downscaling of seasonal forecasts: a case-study for Southeast Asia
Climate Dynamics, 2020Co-Authors: R. Manzanas, José M. Gutiérrez, Jonas Bhend, Stephan Hemri, Francisco J. Doblas-reyes, E. Penabad, Anca BrookshawAbstract:The present paper is a follow-on of the work presented in Manzanas et al. (Clim Dyn 53(3–4):1287–1305, 2019) which provides a comprehensive intercomparison of alternatives for the post-processing (Statistical Adjustment, calibration and downscaling) of seasonal forecasts for a particularly interesting region, Southeast Asia. To answer the questions that were raised in the preceding work, apart from Bias Adjustment (BA) and ensemble Re-Calibration (RC) methods—which transform directly the variable of interest,—we include here more complex Perfect Prognosis (PP) and Model Outputs Statistics (MOS) downscaling techniques—which operate on a selection of large-scale model circulation variables linked to the local observed variable of interest. Moreover, we test the suitability of BA and PP methods for the post-processing of daily—not only seasonal—time-series, which are often needed in a variety of sectoral applications (crop, hydrology, etc.) or to compute specific climate indices (heat waves, fire weather index, etc.). In addition, we also undertake an assessment of the effect that observational uncertainty may have for Statistical post-processing. Our results indicate that PP methods (and to a lesser extent MOS) are highly case-dependent and their application must be carefully analyzed for the region/season/application of interest, since they can either improve or degrade the raw model outputs. Therefore, for those cases for which the use of these methods cannot be carefully tested by experts, our overall recommendation would be the use of BA methods, which seem to be a safe, easy to implement alternative that provide competitive results in most situations. Nevertheless, all methods (including BA ones) seem to be sensitive to observational uncertainty, especially regarding the reproduction of extremes and spells. For MOS and PP methods, this issue can even lead to important regional differences in interannual skill. The lessons learnt from this work can substantially benefit a wide range of end-users in different socio-economic sectors, and can also have important implications for the development of high-quality climate services.
