Joint Canada/U.S. Health Survey

1. Joint Canada/U.S. Health Survey Catherine Simile, National Center for Health Statistics Patrice Mathieu, Statistics Canada Ed Rama, Statistics Canada NCHS 2002 Data Users Conference July 15-17, 2002 Washington, DC

2. Sample Parameters • Target Population: Household residents aged 18 and older in Canada and in United States • Produce reliable estimates at the national level for 6 domains : • 3 age groups (18-44, 45-64, 65 and older) • by gender (F, M)

3. Sample Design • Sample size: • about 5,000 respondents in the U.S. • about 3,500 respondents in Canada • Random digit dialing (RDD) method used: • Telephone numbers are randomly selected • 1 respondent per household (18 and older) is then selected

4. Sample Design • Why use the RDD method? • The most similar method existing in both countries • Simple method • Less expensive • Limitations with RDD: • Some households don’t have telephone • 4% - 5% in the U.S. , less than 2% in Canada • The age and sex of the household members are unknown beforehand

5. Sample Design • Selection process: • List all the household members • When 65 and older are presentrandomly select the respondent among the 65 and older only • When no 65 and older randomly select the respondent among all the members

6. Sample Design • Why increasing the probabilities of selection for the 65 and older ? The group “65 and older” is less common in the population (in about 13% of the households) Not enough “65 and older” in the sample

7. Sample Design • Sample Composition - Canada (similar in the U.S.)

8. Data Collection • Computer Assisted Telephone Interviewing (CATI) • All interviews conducted from Statistics Canada regional offices (Toronto, Vancouver, Edmonton and Montreal) • Interviews in 3 languages (Eng., Spanish, French) • 20 minutes interviews • Collection period: November 2002 to March 2003 • Targeted response rate: 75% • No proxy interviews

9. Data Release • Public Use File to be released in the fall of 2003. (No Master file, for confidentiality reasons) • A users manual and initial publication outlining major findings of the survey will be released • Information about the survey and the data will be made available on the NCHS and STC websites.

10. Weighting & Estimation • Estimation relates sample back to population • Must use weights in calculation of estimates to correctly draw conclusions about pop’n of interest • Sampling weight is related to the probability of selecting a unit in the sample • Respondents selected with unequal probabilities therefore have varying weights

11. Weighting & Estimation • Same method for both countries, but applied separately for each • Basic weight: inverse of the probability of selecting the telephone line • Some weight adjustments: • households with more than one phone line • non-response (household and respondent levels) • etc… • Post-stratify to 2002 population estimates based on last Census counts

12. Effect of Weighting • Comparison of males and females who reported being in excellent or very good health: • Weighted difference: 65.3–61.6 = 3.7% • Unweighted difference: 62.6–60.8 = 1.8% Source: National Population Health Survey, Statistics Canada

13. Sampling Error • Measure of precision, reliability of the estimates • Variance (standard deviation) • Coefficient of variation • Standard deviation of estimate x 100% / estimate itself • Example: • 24% of population are daily smokers, std dev. = 0.003 • CV=0.003/0.24 x 100%=1.25%

14. Sampling Variability Guidelines Type of estimate CV Guidelines Acceptable 0.0-16.5 General unrestricted release Marginal 16.6-33.3 General unrestricted release but with warning cautioning users of the high sampling variablitity. Unacceptable > 33.3 No release.

15. CV Look-up Tables—Example • National Population Health Survey ‑ 1996/1997 • Approximate Sampling Variability Tables for Ontario Health Area:OTTAWA CARLETON ‑ Selected members • NUMERATOR OF ESTIMATED PERCENTAGE • PERCENTAGE • ('000) 0.1% 1.0% 2.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 40.0% 50.0% 70.0% 90.0% • 1 ******** 48.6 48.4 47.6 46.4 45.0 43.7 42.3 40.9 39.4 37.8 34.5 26.8 15.5 • 2 ******** 34.4 34.2 33.7 32.8 31.9 30.9 29.9 28.9 27.9 26.8 24.4 18.9 10.9 • 3 ******** 28.1 27.9 27.5 26.8 26.0 25.2 24.4 23.6 22.7 21.9 19.9 15.5 8.9 • 4 ******** 24.3 24.2 23.8 23.2 22.5 21.9 21.2 20.4 19.7 18.9 17.3 13.4 7.7 • 5 ******** 21.7 21.6 21.3 20.7 20.1 19.5 18.9 18.3 17.6 16.9 15.5 12.0 6.9 • 6 ******** 19.8 19.7 19.4 18.9 18.4 17.8 17.3 16.7 16.1 15.5 14.1 10.9 6.3 • 7 ******** 18.4 18.3 18.0 17.5 17.0 16.5 16.0 15.5 14.9 14.3 13.1 10.1 5.8 • 8 **************** 17.1 16.8 16.4 15.9 15.5 15.0 14.5 13.9 13.4 12.2 9.5 5.5 • 9 **************** 16.1 15.9 15.5 15.0 14.6 14.1 13.6 13.1 12.6 11.5 8.9 5.2 • 10 **************** 15.3 15.1 14.7 14.2 13.8 13.4 12.9 12.5 12.0 10.9 8.5 4.9 • ... • ... • 300 **************************************************************************************** 2.0 1.5 0.9 • 350 **************************************************************************************** 1.8 1.4 0.8 • 400 ************************************************************************************************ 1.3 0.8 • 450 ************************************************************************************************ 1.3 0.7 • 500 ************************************************************************************************ 1.2 0.7 • NOTE: FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION

16. CV Look-up Tables • Appoximate • Can only use for categorical variables, and for estimations of totals and proportions • Provided with PUF • Easy to use • The CVs in the table take into account the design effect and the weights adjustments