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Randomisation

Randomisation. Surveys should use some form of random sampling to obtain a representative sample Randomisation avoids subjective and other biases Randomisation allows the calculation of likely size of the sampling error estimates. Simple Random Sampling(SRS).

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Randomisation

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  1. Randomisation • Surveys should use some form of random sampling to obtain a representative sample • Randomisation avoids subjective and other biases • Randomisation allows the calculation of likely size of the sampling error estimates. Simple Random Sampling(SRS) • Label each population member from 1 to N and sample without replacement in a random way using a • Lottery method • Random Number tables • Computer

  2. Other types of sampling • Stratified sampling • Population is made up of different strata • A sub sample is selected from each stratum using SRS • The combined sub samples form your sample E.g. Looking at average net profit of companies listed on the NZSE. Using annual reports we can classify the companies into large, medium and small. These categories form our strata • Cluster sampling • Population is made up of distinct “clusters” • Randomly select some clusters and then sample from each cluster • E.g. Take a list of towns in NZ (pop. < 20,000) and choose some at random • In each selected town get a list of streets and choose some at random • In each selected street get a list of the houses and choose some at random • Ask each selected household some questions • Systematic sampling • Take every kth unit. • Often used in biological sciences

  3. Errors in surveys • Sampling errors are • Errors caused by the act of take the sample • The difference between the sample values and the population value • Bigger in smaller samples than in larger ones • Unavoidable (the cost of taking a sample) • Can be minimised (but never removed) by careful design of the sampling scheme • E.g. TV3/CM Research Poll sample 1,500 people with a 3% margin of error • The margin of error is an estimate of how large the sampling error is likely to be

  4. Non-sampling errors • Can be much larger than sampling errors • Always present • It is virtually impossible to determine how badly they will affect the results • It is almost impossible to correct for non-sampling errors after the survey has been completed • Therefore, we must try to minimise non-sampling errors when designing the survey • That is we use a pilot survey (if possible) to expose the flaws or potential flaws in the survey design

  5. Selection bias • The sampling mechanism does not allow every unit in the population to be selected • E.g. A telephone survey is a possible source of selection bias because the selection method excludes all those people not in the phone book Self-Selection bias • The sampling mechanism allows units to select themselves for the survey • A suggestion box is an example of self-selection bias • Many behavioural research studies, especially those concerning areas such as sexual habits have selection biases

  6. Non-response bias • Non-response occurs in three ways • Non-coverage  Selection bias • Item non-response – failure to answer a question on a survey • Unit non-response – failure to respond to the whole survey • Item non-response usually occurs when questions are of a sensitive nature. • E.g. “Please state your income so we can see whether you owe more tax than you paid” • Unit non-response usually occurs when there is little or no incentive to respond. • Mail-in surveys often suffer from unit non-response • Telephone surveys

  7. Question effects • 18 Aug 1980, NY Times/CBS News Poll “Do you think there should be an amendment to the constitution prohibiting abortions?” • 29% Yes, 62% No • Later the sample people were asked “Do you think there should be an amendment to the constitution protecting the life of the unborn child?” • 50% Yes, 39% No

  8. Interviewer effects • In 1968, one year after a major racial disturbance in Detroit, a sample of black residents were asked: “Do you personally feel that you can trust most white people, some white people or none at all?” • White interviewer: 35% answered “most” • Black interviewer: 7% answered “most” • Interviewers should be non-threatening. • Studies have shown that women make the best interviewers

  9. Behavioural considerations • People may behave differently because they think they will get in trouble E.g. Official vote counts show 86.5 million people voted in the 1980 US presidential elections A Census Bureau survey of 64,000 households some weeks later estimated 93.1 million people voted. Transfer of findings • Is it valid to apply the findings of a survey conducted on one population to another? • Generally not. • E.g if a survey about the amount of fruit eaten is conducted in the US could we use the results for New Zealand?

  10. Survey format • Consider a subject you find embarrassing. • Now suppose you’re involved in a survey about that subject • Will your answer to various questions differ if the survey uses: • A face to face interview • A telephone poll • questionnaires to be mailed back

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