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svyplan: Survey Sample Size Determination and Precision Analysis

Source: R/svyplan-package.R
svyplan-package.Rd

Tools for survey sample size determination, precision analysis, optimal allocation, joint multivariate and multidomain allocation, two-phase allocation, stratification, power analysis, and planning for surveys repeated over time. Computes sample sizes for proportions and means, evaluates sampling precision for a given design, optimizes multistage cluster allocations, estimates variance components from frame data, computes design effects, constructs strata boundaries, allocates two-phase designs, sizes the change between two occasions, derives the sample overlap a rotation schedule produces, sizes the recruitment a panel needs to hold a responding sample against attrition, constructs explicit rotating-panel fieldwork schedules, and performs statistical power analysis for two-sample tests. Sample size and precision functions support response rate adjustment and bidirectional round-trip via S3 dispatch. Sensitivity analysis is available through predict methods. Based on methods from Cochran (1977, ISBN:978-0-471-16240-7), Kish (1965, ISBN:978-0-471-48900-9), Saerndal, Swensson, and Wretman (1992, ISBN:978-0-387-40620-6), Fuller (2009, ISBN:978-0-470-45460-2), and Valliant, Dever, and Kreuter (2018, ISBN:978-3-319-93630-4).

Notation

Argument names spell out what a quantity is rather than reproducing the symbol used in any one textbook. Readers coming from the standard references can map them as follows.

ArgumentSymbolMeaning
icc\(\delta\)Design-based measure of homogeneity within clusters, \(V_b/(V_b+V_w)\). Constrained to \([0, 1]\), so it is not interchangeable with a mixed-model ICC, which can be negative. Written \(\delta\) by Valliant, Dever and Kreuter (2018) and related to Kish's roh.
var_ratio\(k\)Ratio of the stage components' unit variance to the analysis variable's. Defaults to 1.
unit_relvar\(V\)Unit relvariance, \(S^2/\bar{y}^2\), that is the squared population coefficient of variation.
deff\(DEFF\)Design effect.
n_psu\(n_1\)Number of PSUs selected.
n_per_psu\(n_2\)Units selected per PSU, which is a sample take, not the PSU's population size.
n_per_ssu\(n_3\)Units selected per SSU.
moe\(e\)Margin of error, the half-width of the confidence interval.
cv\(CV\)Coefficient of variation, the relative standard error.
overlap, overlap_cor\(\gamma\), \(\rho\)Panel overlap fraction and the correlation between occasions.
alloc_q\(q\)Bankier power-allocation exponent, used only when alloc = "power". It is unrelated to statistical power.

Dispersion may be given as either var or sd wherever a mean is being planned; supply exactly one. The exception is n_twophase(), whose frame takes sd only.

References

Cochran, W. G. (1977). Sampling Techniques, 3rd edition. Wiley.

Kish, L. (1965). Survey Sampling. Wiley.

Valliant, R., Dever, J. A., and Kreuter, F. (2018). Practical Tools for Designing and Weighting Survey Samples, 2nd edition. Springer.

See also

Useful links:

Author

Maintainer: Ahmadou Dicko mail@ahmadoudicko.com (ORCID)

Authors: