Comments (2)
Hi @meh-wzdech
I do not fully understand your question. Let me know if this is what you want to achieve. You have a total sample size of 2,000 and you want to allocate it across the 18 strata formed by gender, age, and education? If so, do you want allocate proportionally or else?
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Hello @MamadouSDiallo. Yes, I would like to create a sample design with those strata (e.g. woman, 18-30, lower education; man, 50+, higher education etc.). The problem is to allocate each strata in a way that, as a result, in the total sample there would be roughly 64% women, 36% men; 20% aged 18-30, 50% aged 31-50, 30% aged 50+; 30% with lower education, 50% with middle education and 20% with higher education.
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Related Issues (20)
- Same sample size across strata
- cluster sample size
- Add datasets referenced in tutorial notebooks as part of the repo HOT 2
- fix use of some deprecated things HOT 1
- testing HOT 1
- comm. guidelines HOT 1
- minor issues w/ writing HOT 1
- Estimation problem: 'division by 0' HOT 7
- Documentation outdated in README and ReadTheDocs HOT 1
- RuntimeWarning: divide by zero encountered in log ll_term1 = np.log(np.linalg.det(V)) HOT 1
- "cannot reshape array" error message with crosstabs containing 0-value cells (samplics 0.3.12 and 0.3.13) HOT 28
- Enhancements for sample estimation - response rate and sampling
- LinAlgError: Singular matrix when running EBLUP Area Model HOT 3
- Reference formulas for four main types of comparisons, in particular "comparison of two groups from the same sample"?
- Enhancement: Add MIVQUE0 estimation method for EBLUP area model HOT 1
- Preserve the GLM model information
- Question: Is it possible to draw a one-stage PPS sample? (no stratum) HOT 3
- design effect
- Design effect for cross-tabulation APIs
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