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 ConferenceJuly 15-17, 2002Washington, DC

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)

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

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

Sample Design

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

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

Sample Design

Sample Design

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

Domain Population(%)

Sample (%)

18-44 yrs MaleFemale

25.8%25.6%

25.1%25.1%

45-64 yrs MaleFemale

14.7%15.2%

14.3%14.7%

65 and older MaleFemale

7.3%11.4%

9.3%12.1%

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

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.

Data Release

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

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

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

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%

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 withwarning cautioning users of the highsampling variablitity.

Unacceptable > 33.3 No release.

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

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