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Summary of survey software: Designs Accomodated

* This is a summary of the information included under the heading
"Types of designs that can be accommodated" for each of the
software packages described on these pages. Select the appropriate title
for more information on any package.*
Stratified unequal-probability (weighted) cluster or multistage
samples.

The following designs can be accomodated for variance estimation.
- Stratified simple random sampling without replacement.
- Stratified two-stage simple random sampling without replacement.
- Stratified multi-stage sampling with replacement in first stage.

Sample designs ranging from simple random samples of elements to more
complex stratified, multistage cluster designs.
The program computes sampling errors taking into account the actual sample
design. There are no specific restrictions on the designs handled, except the
basic ones of 'large enough' sample size and the availability of two or more
independent primary selections per stratum with replacement. The finite
population correction is disregarded. Flexible facilities for specifying
computing strata, primary units and sample weights are included
Stratified sampling, with or without clustering; multistage samples;
unequal-probability (e.g. pps) samples. Does not calculate finite
population corrections, so either sampling fraction must be small or
sampling must be with replacement.
Stratified one stage element or cluster sampling; two-phase designs.
Complex designs with stratification and clustering.
Designed for multistage stratified samples. Finite population
correction terms can be introduced at two stages.
- Designs incorporating stratification, clustering, and possibly multistage
sampling, allowing unequal sampling probabilities or weights.
- PPS sampling with replacement
- Approximations for multistage PPS without replacement
- Simple two-phase designs
- Multiply-imputed data

For the sample selection procedure, the sample design can be a complex
multistage sample design that includes stratification, clustering,
replication, and unequal probabilities of selection.

For survey data analysis procedures, the sample design can be a
complex survey sample design with stratification, clustering, unequal
weighting, and with or without replacement.

For both design and estimation, accomodates stratification, clustering, and
multistage sampling. Supports a number of unequal-probability without replacement sampling schemes including 2-PSU-per-stratum designs.
- stratified designs;
- cluster sampling;
- unequal probabilities of selection (sampling weights);
- multiple stages of sampling, with stratification, clustering and finite population corrections at each stage;
- finite-population corrections can be calculated for simple
random sampling without replacement of sampling units within
strata.
- post-stratification and direct standardization;
- some designs with a single PSU per stratum

Multiple design options allow users to analyze data from stratified,
cluster sample, or multistage sample designs. Sample members may have
been selected with unequal probabilities, and either with or without
replacement. Any number of strata and stages can be specified. In
addition, different design options may be combined in one study if
different sampling methods were used for parts of the population.
Stratified and clustered designs.
- All variance estimates are based on replicate weights, either generated
within the program user-provided.
- Stratified or unstratified, single- or multistage designs. Finite
population corrections can be accomodated. 2/stratum designs using
BRR or Jackknife, >2/stratum using Jackknife.
- If replicate weights are generated within the program, external
control totals may be provided to be provided to perform
post-stratification or raking of the weights, and nonresponse weighting
adjustment.
- Multiply-imputed datasets can be analyzed.

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