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From Surveys to Surveillance Time Series Analysis

From Surveys to Surveillance Time Series Analysis. Under Construction !. Eric Holowaty, Sr. Scientist, Informatics Unit, CCO Michael Spinks, Sr. Res. Assoc., CCO. Background. 1980s and 1990s - occasional surveys precise estimates of rates, proportions, means, nos. affected

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From Surveys to Surveillance Time Series Analysis

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  1. From Surveys to SurveillanceTime Series Analysis Under Construction ! Eric Holowaty, Sr. Scientist, Informatics Unit, CCO Michael Spinks, Sr. Res. Assoc., CCO.

  2. Background • 1980s and 1990s - occasional surveys • precise estimates of rates, proportions, means, nos. affected • detecting important differences in estimates within survey • 2000s - surveillance systems • continuous, or at least frequent sampling • monitoring and assessing temporal patterns, incl. change point detection and sub-group differences over time

  3. Background • What is desired periodicity of sampling? Depends on: • how rapidly variables actually change • how important it is to detect changes quickly • desired precision in describing temporal patterns, changes and differences

  4. Definitions • Time series • sequence of data points, measured at successive times, and spaced apart at uniform time intervals • Time series analysis • methods and models that describe and explain temporal patterns, and forecast future patterns • Trend • long-term movement in an ordered series; may be temporal or just ordered strata

  5. Typical Time Series for One Participating PHU

  6. Risk Factor Surveillance in Ontariopre-RRFSS • Uncoordinated • Fragmented • Lack of smaller area data • Poorly analysed • Poor dissemination • Not timely • Difficult to access

  7. Pilot tested in Durham Region in 1999 • Available for Individual PHUs in Jan 2001 • 22 PHUs participating as of Dec 2004 • ?Province-wide coverage in 2005/06

  8. RRFSS Population Coverage 87% of pop’n 22/37 PHUs RRFSS (2003) respondents : 25,600 CCHS (2003) resp. : 37,000

  9. Benefits of RRFSS • Monthly data more suitable for detecting temporal changes • More flexibility re. aggregation - before / after comparisons; geographic areas; demographic groups • Seasonal effects can be better described and analysed • (Robust SPC procedures permit timely detection of stat. signif. changes) • LARGE sample size permits more precise analysis • Standard CORE of questions helps ensure comparability over time and with other geo. areas. • Flexible MODULES permit targetted sampling and invest. of local concerns

  10. Fundamental Statistical Issues in Time Series Analysis • Accuracy and precision of estimates • precision ~ sample size and survey design • bias • differential access and response • reporting/measurement bias • changes in the measurement tool, incl. wording importance of bias in time series analysis depends on size and consistency • Statistical power • probability of detecting an important change in time series - slope; seasonality; change points

  11. Estimating the rate of change over time • Estimating that slope differs from the null i.e., zero change • assumption of monotonic relationship e.g., linear or log-linear model or logistic • assumption of no change points in time series

  12. Statistical Power to Detect Slope > Null • Power influenced by: • length of time series (k) • size of each sample (n) • measurement of interest (p or x or x) and its variance • alpha (Type I error) • underlying rate of change/slope (b)

  13. Statistical Power of Trend Tests Sample Size From: MacNeill and Umphrey, 1997.

  14. Statistical Power of Trend Tests Sample Size From: MacNeill and Umphrey, 1997.

  15. Statistical Power of Trend Tests Sample Size From: MacNeill and Umphrey, 1997.

  16. Monthly Estimates of ETS Exposure Trends - RRFSS GTA Aug01-Dec03

  17. Quarterly Estimates of ETS Exposure Trends - RRFSS GTA Aug01-Dec03

  18. Estimates of ETS Exposure Trends - RRFSS GTA Aug01-Dec03

  19. Detecting abrupt changes in lengthy time series • Change-point methods e.g. JoinPoint • Control Charts • conventional p-charts • CUSUM charts • EWMA charts, with residuals

  20. Monthly Estimates of Support for Bylaws - RRFSS GTA Jan02-Dec04

  21. Monthly Estimates of Support for Bylaws - RRFSS GTA Jan02-Dec04 15/35 point estimates in violation of Western Electric rules

  22. Monthly Estimates of Support for Bylaws - RRFSS GTA Jan02-Dec04

  23. Monthly Estimates of Support for Bylaws - RRFSS GTA Jan02-Dec04

  24. Plan • Complete analysis of definitions, incl. temporal consistency and CCHS consistency • Assign final sample weights • Production of point estimates for 2003 and 2004 • Age-standardized comparisons • Time series analysis

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