statistical methods for comparing of 2 1-year surveys

We would like to compare a percent from a 2013 single year dataset with the same percent from the 2014 single year data set.  Can we use statistical methods that require independent samples like a chi - square test?  Although different people may have been surveyed in the two years, I don't believe one year is independent of the next year because the samples represent the same population.  

 

 

Thank you in advance for your help or thoughts.     

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  • ACS years are independent samples, but, stat_analyst, you are correct that Chi-Square is not an appropriate test of significance because Chi-Square is generally used to test differences across categories (i.e. distinct populations).

    You are also correct that what you'd want to use is the z-score test described by the Census Bureau in this document: www2.census.gov/.../MultiyearACSAccuracyofData2013.pdf
  • Well, at least according to Wikipedia, the formula on page 23 is for an independent 2 sample t test. en.wikipedia.org/.../Student's_t-test So I would think that means independent samples.

    It was explained on another site. Suppose you have students coming in for some kind of randomized trial. Half are assigned to treatment, half to no treatment. This is independent samples, because the students in the treatment condition are independent of the students in the no treatment group, even though they are all students at the same institution.
  • Gene,

    You are right that is a formula for independent samples. Dependent samples would have only one se.

    But your example is very different, it is not survey sampling. The samples are not selected to represent the entire student population. There is no weighting. There really isn't any sampling going on. Those are distinct groups.
  • I was just using the example to illustrate the meaning of "independent", that is, two groups not dependent on each other. The ACS of course involves a lot more, as you indicate weighting, and so forth. I just wanted a simplified example.
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