Sampling Bias and Nonprobability
Diapositivas del conjunto (7)
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- MUST ELIMINATE BIAS
- Only without bias can researchers be confident in their findings
- Bias occurs when respondents are not selected through true random sampling
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- invitation preferred over "opt-in" - but it generates a low response rate
- professional respondents are undesirable
- verify your respondents are real
- Panel should represent US population
- Monitor Response Rates - low response rates means people are turning away
- Poor panelists removed (the people who press the same button or answer crazy)
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- Convenience
- Judgement
- Quota
- Snowball
- Not good for generalization, only for quick, preliminary results
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- respondents are selected because they are convenient and accessible.
- will most likely provide biased and unreliable information.
- should only be used when there is no need to generalize to the broader population
- appropriate for exploratory research or quick information such as questionnaire pretesting
- times and conditions can change a sample DRAMATICALLY
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- respondents selected based on an expert's decision on who is best to interview.
- the greater the expertise, the greater the confidence in the results of the research (directly related)
- only recommended when the is immense confidence in the expert opinion or only when preliminary, exploratory information is needed
- Approaches include:
- extreme cases
- typical cases
- intense or passionate cases
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- Extension of judgement sampling
- attempts to represent demographics of the sample equal to that of the broader target population
- obtained in 5 steps:
- Determine the defining characteristics of the key subgroups
- Determine the percent of the total population represented by each defining charateristic
- Determine the percent of the total population represented by each quota cell.
- translate the percent into a sample size
- Sample population
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- Uses current participants to recruit new participants
- used for populations where access is through personal introductions
- subject to numerous biases
- can be caused by a reposting or forwarding of surveys by a current participant
- Can be inaccurate because you have no idea who is answering the survey
Información
- Descripción
- Advertising Diapositivas sobre Sampling Bias and Nonprobability, creado por Roxanne V Springman el 13/09/2017.
- Creado por
- Roxanne V Springman
- Visitas
- 43
- Valoración