quota or stratified sampling?

Discussion in 'SPSS' started by wollyka, Nov 29, 2011.

  1. wollyka

    wollyka Guest

    Hello, Everyone.

    I need your help, I have a question regarding quota, stratified
    sampling and area sampling. so it is not directly SPSS related
    If a quota has been picked including key variables such as region,age
    and gender. Then the researcher went to each region and start
    selecting households randomly in that region and filling
    questionnaires with individuals to fill the quota.

    The sampling method here is still quota sampling? or is it a mixed of
    stratified and quota sampling?

    Also, since quota sampling is regarded as stratified sampling with a
    more or less non-random selection of units within strata, sampling
    error formulas cannot be applied to the results of quota samples. And
    I gather we should not apply the stratified random mean calculations
    to results obtained through quota sampling, or can we?

    How do we weight the results when there is now an element of
    randomness in the quota sampling? That is to say, the selection of
    respondents is done randomly until the pre-set quotas are reached.

    I'd love to hear what you think please.
    wollyka, Nov 29, 2011
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  2. wollyka

    Jon Peck Guest

    This is a multi-stage sample. You can define each stage using the Complex Samples wizard either for drawing a sample or preparing for analysis. Thenthe complex samples procedures will use that sample definition to calculate the appropriate standard errors etc.
    Jon Peck, Nov 30, 2011
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  3. wollyka

    wollyka Guest


    But theoretically, (without using SPSS) , it is called quota or multi-
    stage sampling?
    wollyka, Nov 30, 2011
  4. wollyka

    Jon Guest

    Strictly speaking Jon's reply is not entirely correct. It may be
    correct that it is a multi stage sample (assuming that there is random
    selection of regions, if there is not, then it is a stratified quota
    sample. But, you cannot consider the quotas as clusters). However,
    there are two problems with using the complex samples option. The
    first is that you do not know what the inclusions probabilities are,
    although you could fake it by using for example census data for age
    and gender (many will simply assume equal probabilities). The second
    is that it is, after all, a quota sample, and the variance estimation
    is not designed to handle that. There is no obvious way for
    calculating standard errors. That filling the quotas is a more or less
    random process within each quota is fairly common. If the selection is
    truly random, and from a list, one could have considered it a
    stratified sample, but again, the inclusion probabilities pose a
    Jon, Dec 9, 2011
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