Using Time Series Models to Understand Survey Costs

2020 ◽  
Author(s):  
James Wagner ◽  
Heidi Guyer ◽  
Chrissy Evanchek
Keyword(s):  
Time Series ◽  
Time Series Models ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Measurement Issues ◽  
Trade Offs ◽  
Time Period ◽  
Survey Costs ◽  
Over Time

Abstract Survey costs are an understudied area. However, understanding survey costs is critical for making efficient decisions about cost-error trade-offs, as well as to accurately project future costs. In this article, we examine a measure of survey costs—per interview costs—over time in a repeated cross-sectional survey. We examine both measurement issues and variability in costs. The measurement issues relate to the classification of various costs into the appropriate time period. We explore several issues that make this process of classification difficult. A time series analysis is then utilized to examine the trends and seasonality in per interview costs. Under the assumptions of our model, after removing the trend and seasonality components, the remainder is variation in costs. This approach allows us to treat survey cost estimates in a manner similar to any other survey estimate.

Abstract 88: Increasing False Positive Diagnoses May Lead to Overestimation of Stroke Incidence, Particularly in the Young

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Abhinav J Appukutty ◽  
Lesli E Skolarus ◽  
Mellanie V Springer ◽  
William J Meurer ◽  
James F Burke
Keyword(s):  
Older Adults ◽  
False Positive ◽  
Age Groups ◽  
Vascular Risk Factor ◽  
The United States ◽  
Cross Sectional ◽  
Stroke Incidence ◽  
Ed Visits ◽  
Over Time

Introduction: Stroke incidence is reportedly increasing in younger adults. While increasing vascular risk factor prevalence has been suggested as a cause, the reasons for rising stroke incidence in the young are not clear. We explored several alternate explanations: trends in neurologically-focused emergency department (ED) visits, differential diagnostic classification of stroke and TIA over time, and changes in the use of advanced imaging in young and older adults. Methods: We performed a retrospective, serial, cross-sectional study on a nationally representative sample of all ED visits in the United States to quantify changes in patterns of neurologically-focused ED visits, stroke and TIA diagnoses, and rates of MRI utilization for young (18 – 44 years) and older (65+ years) adults over a 17-year period (1995 – 2000; 2005 – 2015) using National Hospital Ambulatory Medical Care Survey (NHAMCS) data. Results: In young adults, 0.4% (95% CI 0.3% – 0.5%) of neurologically-focused ED visits resulted in a primary diagnosis of stroke vs. 6.8% (95% CI 6.2% – 7.5%) for older adults. In both populations, the incidence of neurologically-focused ED visits has increased over time (+111/100,000 population/year, 95% CI +94 – +130 in the young vs. +70/100,000 population/year, 95% CI +34 – +108 in older adults). There was no evidence of differential classification of TIA to stroke over time (OR 1.001 per year, 95% CI 0.926 – 1.083 in the young; OR 1.003 per year, 95% CI 0.982 – 1.026 in older adults) and no evidence of disproportionate rise in MRI utilization for neurologically-focused ED visits in the young (OR 1.057 per year, 95% CI 1.028 – 1.086 in the young; OR 1.095 per year, 95% CI 1.066 – 1.125 in older adults). Conclusions: If the specificity of stroke diagnosis amongst ED visits is similar amongst young and older populations, then the combination of data observed here, including (1) a lower prior probability of stroke diagnoses in the young and (2) an increasing trend in neurologically-focused ED visits in both age groups, suggests that false positive diagnoses will increase over time, with a faster rise in the young compared to older adults. These data suggest a potential explanation that may contribute to higher stroke incidence in the young and merits further scrutiny.

scholarly journals Methods of conduct and reporting of living systematic reviews: a protocol for a living methodological survey

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 221 ◽  
Author(s):  
Assem M. Khamis ◽  
Lara A. Kahale ◽  
Hector Pardo-Hernandez ◽  
Holger J. Schünemann ◽  
Elie A. Akl
Keyword(s):  
Systematic Review ◽  
Systematic Reviews ◽  
Evidence Synthesis ◽  
Cochrane Library ◽  
Cross Sectional Survey ◽  
Systematic Review Methodology ◽  
Cross Sectional ◽  
Prospective Longitudinal ◽  
Over Time

Background: The living systematic review (LSR) is an emerging approach for improved evidence synthesis that uses continual updating to include relevant new evidence as soon as it is published. The objectives of this study are to: 1) assess the methods of conduct and reporting of living systematic reviews using a living study approach; and 2) describe the life cycle of living systematic reviews, i.e., describe the changes over time to their methods and findings. Methods: For objective 1, we will begin by conducting a cross-sectional survey and then update its findings every 6 months by including newly published LSRs. For objective 2, we will conduct a prospective longitudinal follow-up of the cohort of included LSRs. To identify LSRs, we will continually search the following electronic databases: Medline, EMBASE and the Cochrane library. We will also contact groups conducting LSRs to identify eligible studies that we might have missed. We will follow the standard systematic review methodology for study selection and data abstraction. For each LSR update, we will abstract information on the following: 1) general characteristics, 2) systematic review methodology, 3) living approach methodology, 4) results, and 5) editorial and publication processes. We will update the findings of both the surveys and the longitudinal follow-up of included LSRs every 6 months. In addition, we will identify articles addressing LSR methods to be included in an ‘LSR methods repository’. Conclusion: The proposed living methodological survey will allow us to monitor how the methods of conduct, and reporting as well as the findings of LSRs change over time. Ultimately this should help with ensuring the quality and transparency of LSRs.

scholarly journals Learning longitudinal patterns and identifying subtypes of pediatric Crohn disease treated with infliximab via trajectory cluster analysis of electronic health records

2021 ◽  
Author(s):  
Andrew Chen ◽  
Ronen Stein ◽  
Robert N. Baldassano ◽  
Jing Huang
Keyword(s):  
Electronic Health Records ◽  
Disease Activity ◽  
Crohn Disease ◽  
Cross Sectional ◽  
Health Records ◽  
Disease Evolution ◽  
Current Classification ◽  
Electronic Health ◽  
Over Time

ABSTRACTBackgroundThe current classification of pediatric CD is mainly based on cross-sectional data. The objective of this study is to identify subgroups of pediatric CD through trajectory cluster analysis of disease activity using data from electronic health records.MethodsWe conducted a retrospective study of pediatric CD patients who had been treated with infliximab. The evolution of disease over time was described using trajectory analysis of longitudinal data of C-Reactive Protein (CRP). Patterns of disease evolution were extracted through functional principal components analysis and subgroups were identified based on those patterns using the Gaussian mixture model. We compared patient characteristics, a biomarker for disease activity, received treatments, and long-term surgical outcomes across subgroups.ResultsWe identified four subgroups of pediatric CD patients with differential relapse-and-remission risk profiles. They had significantly different disease phenotype (p < 0.001), CRP (p < 0.001) and calprotectin (p = 0.037) at diagnosis, with increasing percentage of inflammatory phenotype and declining CRP and fecal calprotectin levels from Subgroup 1 through 4. The risk of colorectal surgery within 10 years after diagnosis was significantly different between groups (p < 0.001). We did not find statistical significance in gender or age at diagnosis across subgroups, but the BMI z-score was slightly smaller in subgroup 1 (p =0.055).ConclusionsReadily available longitudinal data from electronic health records can be leveraged to provide a deeper characterization of pediatric Crohn disease. The identified subgroups captured novel forms of variation in pediatric Crohn disease that were not explained by baseline measurements and treatment information.SummaryThe current classification of pediatric Crohn disease mainly relies on cross-sectional data, e.g., the Paris classification. However, the phenotypic classification may evolve over time after diagnosis. Our study utilized longitudinal measures from the electronic health records and stratified pediatric Crohn disease patients with differential relapse-and-remission risk profiles based on patterns of disease evolution. We found trajectories of well-maintained low disease activity were associated with less severe disease at baseline, early initiation of infliximab treatment, and lower risk of surgery within 10 years of diagnosis, but the difference was not fully explained by phenotype at diagnosis.

On the use of structured time-series to detect and test hypotheses about within-lakes relationships

1995 ◽  
Vol 52 (4) ◽  
pp. 799-803 ◽  
Author(s):  
Yves T. Prairie ◽  
C. Tara Marshall
Keyword(s):  
Time Series ◽  
Empirical Data ◽  
Single System ◽  
Empirical Relationships ◽  
Cross Sectional ◽  
Apparent Relationship ◽  
Field Season ◽  
The Relationship ◽  
Over Time ◽  
Chlorophyll Concentrations

Aquatic scientists using empirical relationships developed from point measurements or averages from different lakes often assume that these relationships also apply to individual lakes over time. However, this assumption is difficult to test because the extent of variation within a single system is generally much smaller and the relationship accordingly less defined than across a number of systems. We present a new method to extract empirical relationships from the internal structure of a time-series within a single lake. When we applied the method to an extreme simulation, we were able to recover accurately the parameters of the relationship in spite of the absence of any apparent relationship between the variables. When applied to empirical data for phosphorus and chlorophyll concentrations collected daily over one field season, the estimated structural relationship was nearly identical to that estimated from cross-sectional data even though the empirical trend appeared much shallower and very weak.

scholarly journals The assessment of food security in homeless individuals: a comparison of the Food Security Survey Module and the Household Food Insecurity Access Scale

2011 ◽  
Vol 14 (12) ◽  
pp. 2254-2259 ◽  
Author(s):  
Anna C Holland ◽  
Matthew C Kennedy ◽  
Stephen W Hwang
Keyword(s):  
Food Security ◽  
Food Insecurity ◽  
Homeless Population ◽  
Household Food Insecurity ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Household Food ◽  
The Us ◽  
Food Insecurity Access

AbstractObjectiveTo compare the Household Food Insecurity Access Scale (HFIAS), the US Food Security Survey Module (US FSSM) and a modified version of the US FSSM in which references to buying food were changed to references to getting food, in terms of their classification of food security levels among homeless individuals, and to determine which of these instruments was most preferred by homeless individuals.DesignA cross-sectional survey.SettingRecruitment of participants took place at seven shelters and from three drop-in programmes that serve homeless individuals in Toronto, Canada.SubjectsFifty individuals who were ≥18 years of age, able to communicate in English and currently homeless.ResultsThe modified US FSSM assigned 20 % of participants to a lower ordinal food security category compared with the US FSSM, and only 8 % to a higher food security category. The HFIAS assigned 30 % of participants to a lower food security category compared with either the US FSSM or the modified US FSSM, and only 10–16 % of participants to a higher food security category. When asked to compare all three instruments, the majority of respondents (62 %) selected the HFIAS as the best instrument for people who are homeless.ConclusionsA majority of homeless individuals selected the HFIAS as the best food security instrument for people who are homeless. Our findings suggest that the HFIAS is a more appropriate instrument than the US FSSM for measuring food security in the homeless population.

Time Series Model Based Earning Forecasting

2013 ◽  
Vol 791-793 ◽  
pp. 2147-2150
Author(s):  
Xiang Rong Jiang ◽  
Ying Ying Cui
Keyword(s):  
Time Series ◽  
Empirical Study ◽  
Relative Stability ◽  
Listed Companies ◽  
Time Series Model ◽  
New Method ◽  
Time Series Models ◽  
Seasonal Patterns ◽  
Model Based ◽  
Over Time

We propose a procedure to forecast earning of listed companies. It is a modification of method developed for forecasting series with stable seasonal patterns. The new method is motivated by the observations that seasonal patterns, which may be evolving over time and remain relative stability, arise in finance market. The method can be applied to forecast individual observations as well as the end-of-season totals. Empirical study will be conducted with data from finance market to evaluate the performance of the proposed method. The new method is proved more effective than traditional time series models.

How Do Adolescents Get Their E-Cigarettes and Other Electronic Vaping Devices?

2018 ◽  
Vol 33 (3) ◽  
pp. 420-429 ◽  
Author(s):  
Jessica K. Pepper ◽  
Ellen M. Coats ◽  
James M. Nonnemaker ◽  
Brett R. Loomis
Keyword(s):  
Social Media ◽  
Logistic Regression ◽  
Social Experience ◽  
Completion Rate ◽  
Future Research ◽  
Social Situations ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
The Past ◽  
Over Time

Purpose: More adolescents “vape” (use e-cigarettes and similar devices) than smoke, but little is known about how underage users obtain vaping devices. This knowledge could inform efforts to prevent youth access. Design: Original cross-sectional survey with social media recruitment. Settings: Online. Participants: A total of 1729 adolescents (2809 qualified on screener; completion rate 61.6%) aged 15 to 17 years who vaped in the past 30 days. Measures: Adolescents’ vaping attitudes, ownership of vaping devices, how they obtain devices, and frequency of borrowing others’ devices. Analysis: Logistic regression. Results: Most adolescents (78.2%) owned a vaping device. The most common sources were purchasing from a store or online (31.1%), buying from another person (16.3%), or giving someone money to purchase for them (15.0%). The majority (72.8%) had used someone else’s vaping device in the past 30 days. Adolescents who vaped more often, did not own a vaping device, vaped in social situations, and had previously been refused purchase were more likely to frequently borrow others’ devices. Conclusions: Despite high rates of ownership, many adolescents borrowed devices, suggesting that borrowing is part of users’ social experience, not just a means of acquisition. Although better enforcement of age restrictions could lessen purchasing, future research is needed to understand why adolescents borrow and how their acquisition sources shift over time. That information could be harnessed for targeted, borrowing-related antivaping campaigns.

scholarly journals Comparing Dynamic Pies: A Strategy for Modeling Compositional Variables in Time and Space

2017 ◽  
Vol 7 (3) ◽  
pp. 523-540 ◽  
Author(s):  
Christine S. Lipsmeyer ◽  
Andrew Q. Philips ◽  
Amanda Rutherford ◽  
Guy D. Whitten
Keyword(s):  
Time Series ◽  
Political Science ◽  
Recent Work ◽  
Spatial Relationships ◽  
Contextual Variables ◽  
Cross Sectional ◽  
Us States ◽  
The Us ◽  
Dependent Variables ◽  
Over Time

Across a broad range of fields in political science, there are many theoretically interesting dependent variables that can be characterized as compositions. We build on recent work that has developed strategies for modeling variation in such variables over time by extending them to models of time series cross-sectional data. We discuss how researchers can incorporate the influence of contextual variables and spatial relationships into such models. To demonstrate the utility of our proposed strategies, we present a methodological illustration using an analysis of budgetary expenditures in the US states.

Roughness/error trade-offs in neural network time series models

1997 ◽  
Author(s):  
Steven C. Gustafson ◽  
Gordon R. Little ◽  
John S. Loomis ◽  
Theresa A. Tuthill
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Time Series Models ◽  
Trade Offs ◽  
Network Time
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