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Agenda

Agenda. Review assignment three More on sampling Survey design Implementing surveys. More on sampling. How do we determine the accuracy of sample estimates? How do we determine how large a sample we should draw?. Respondent. Age. 1 2 3 4 5 6 7 8 9 10. 20 22 22 23 24 24 24

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Agenda

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  1. Agenda • Review assignment three • More on sampling • Survey design • Implementing surveys

  2. More on sampling • How do we determine the accuracy of sample estimates? • How do we determine how large a sample we should draw?

  3. Respondent Age 1 2 3 4 5 6 7 8 9 10 20 22 22 23 24 24 24 25 28 30

  4. Respondent Age Mean: n i=1  xi 1 2 3 4 5 6 7 8 9 10 20 22 22 23 24 24 24 25 28 30 (20+22+22+23 … +30) 242 x = = = = 24.2 N 10 10

  5. Respondent Age Mean: n i=1  xi 1 2 3 4 5 6 7 8 9 10 20 22 22 23 24 24 24 25 28 30 (20+22+22+23 … +30) 242 x = = = = 24.2 N 10 10 Variance: n i=1  (xi – x)2 s2= = (20-24.2)2 + (22-24.2)2 … 77.6 = = 8.62 N-1 10 - 1 9

  6. Respondent Age Mean: n i=1  xi 1 2 3 4 5 6 7 8 9 10 20 22 22 23 24 24 24 25 28 30 (20+22+22+23 … +30) 242 x = = = = 24.2 N 10 10 Variance: n i=1  (xi – x)2 s2= = (20-24.2)2 + (22-24.2)2 … 77.6 = = 8.62 N-1 10 - 1 9 Standard Deviation: __ s = s2  =  8.62 = 2.94

  7. Respondent Age Mean: n i=1  xi 1 2 3 4 5 6 7 8 9 10 20 22 22 23 24 24 24 25 28 30 (20+22+22+23 … +30) 242 x = = = = 24.2 N 10 10 Variance: n i=1  (xi – x)2 s2= = (20-24.2)2 + (22-24.2)2 … 77.6 = = 8.62 N-1 10 - 1 9 Standard Deviation: __ s = s2  =  8.62 = 2.94 Standard Error: s 2.94 s.e. = ___ = = .93  N  10

  8. Respondent Age Mean: n i=1  xi 1 2 3 4 5 6 7 8 9 10 20 22 22 23 24 24 24 25 28 30 (20+22+22+23 … +30) 242 x = = = = 24.2 N 10 10 Variance: n i=1  (xi – x)2 s2= = (20-24.2)2 + (22-24.2)2 … 77.6 = = 8.62 N-1 10 - 1 9 Standard Deviation: __ s = s2  =  8.62 = 2.94 Standard Error: s 2.94 s.e. = ___ = = .93  N  10

  9. Respondent Age Mean: n i=1  xi 1 2 3 4 5 6 7 8 9 10 20 22 22 23 24 24 24 25 28 30 (20+22+22+23 … +30) 242 x = = = = 24.2 N 10 10 Variance: n i=1  (xi – x)2 s2= = (20-24.2)2 + (22-24.2)2 … 77.6 = = 8.62 N-1 10 - 1 9 Standard Deviation: __ s = s2  =  8.62 = 2.94 Standard Error: s 2.94 s.e. = ___ = = .93  N  10 95% Confidence Interval: 24.2 +/- (1.96 x .93) = 24.2 +/- 1.82 = 22.4 to 26.0

  10. Respondent Age Mean: n i=1  xi 1 2 3 4 5 6 7 8 9 10 20 22 22 23 24 24 24 25 28 30 (20+22+22+23 … +30) 242 x = = = = 24.2 N 10 10 Variance: n i=1  (xi – x)2 s2= = (20-24.2)2 + (22-24.2)2 … 77.6 = = 8.62 N-1 10 - 1 9 Standard Deviation: __ s = s2  =  8.62 = 2.94 Standard Error: s 2.94 s.e. = ___ = = .93  N  10 95% Confidence Interval: 24.2 +/- (1.96 x .93) = 24.2 +/- 1.82 = 22.4 to 26.0

  11. Results of 100 Samples of N = 500 25 20 15 10 5 Std. Dev = 2.39 Mean = 45 0 N = 100.00 25 35 45 55 65 75 SAMPL500 The standard deviation of all sample estimates of a given mean is the is the STANDARD ERROR of the mean The CONFIDENCE INTERVAL -- plus or minus 2 S.E.s -- is the range within which 95 percent of all sample means of a given size will fall

  12. Survey designs • Mail • Telephone • Face to Face • Electronic

  13. Mail surveys • Advantages • Cost effective • Minimizes social desirability effects • Permits complex question formats • Disadvantages • Coverage and response-rate problems • Dillman’s Total Design Method can help • No direct monitoring of interview

  14. Telephone surveys • Advantages • Cost effective • Interviews can be monitored • Generally good coverage (with RDD methods) • CATI standardizes and eases data entry • Disadvantages • Phone response rates may be declining • Long phone interviews can be burdensome • Some complex question formats difficult

  15. Face-to-face surveys • Advantages • Interviewers can insure higher data quality • Can produce high response rates • CAPI standardizes and eases data entry • Disadvantages • Very expensive • Interviewer effects • Requires very well trained field interviewers

  16. Electronic surveys • E-mail and Web surveys • Advantages • Very cost effective • Permits very complex question formats • Automatic data entry • Disadvantages • Often involve severe coverage problems • No direct monitoring of interview

  17. Mixed-mode designs • Mail or E-mail with phone follow-ups • Motivated by desire to increase response rates • Introduces mode-of-interview bias • May confound respondent accessibility with mode-of-interview • Mode-effect problems can be reduced (though usually not eliminated) though careful design choices

  18. Design considerations • Coverage issues • Sampling design • Sample non-response

  19. Coverage issues • Problematic commercial sampling pools • Missing eligible sample elements • Unlisted phone numbers • Mobile respondents • Selection of respondents within households • Enumeration of household (Kish method) • Last-birthday method

  20. Sampling design • Simple random samples not so simple! • RDD telephone surveys need to be weighted for number of phones per household • Cluster samples • Select from primary sampling units (e.g., metro areas); then secondary units (census tracts, households, etc.) • The smaller the number of units sampled at each stage, the larger the sample variances (and standard errors)

  21. Sample nonresponse • Response rate: Completed interviews -------------------------------------------------------------- All respondents drawn in sample • Rate depends upon • Non-contacts • Refusals • Breakoffs • High response rates require persistence • Callbacks and refusal conversion

  22. For Tuesday • Archival research and secondary analysis • Schutt, Ch. 11 • Begin thinking about your group research designs • Group workshops on Thursday

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