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The SPSS Complex Samples add-on module for SPSS gives you everything you need for working with complex samples—from the planning stage and sampling through to the analysis stage.

With SPSS Complex Samples you can:
 

  • Get a more accurate picture of your data when working with large-scale surveys.

  • Achieve more statistically valid inferences for populations.

  • Understand what characteristics consumers relate to most regarding product or brand.

  • Reach correct point estimates for statistics such as totals, means, and ratios, and obtain standard errors of these statistics.

  • Predict numerical and categorical outcomes from non-simple random samples

  • Take up to three stages into account when analyzing data from a multistage design.

Incorporate complex sample designs into your data analysis

Only SPSS Complex Samples makes understanding and working with your complex sample survey results easy. It is one of the most comprehensive software programs available.

SPSS Complex Samples provides you with everything you need to produce more accurate results.

  • Logistic regression: Predict categorical outcomes (such as: Who is most likely to buy my product?) while taking the sample design into account to accurately identify groups.

  • Ordinal regression: Predict ordinal outcomes such as customer satisfaction (low, medium,
    or high).

  • General linear models: Predict numerical outcomes while taking the sample design
    into account.

  • Cox regression: Applies Cox proportional
    hazards regression to analysis of survival
    times—that is, the length of time before
    the occurrence of an event for samples
    drawn by complex sampling methods.

  • Intuitive Sampling Wizard: Guides you step-by-step through the process of
    designing and drawing a sample.

  • Easy-to-use Analysis Preparation Wizard: Helps prepare public-use datasets for
    analysis, such as the National Health
    Inventory Survey data from the Centers
    for Disease Control and Prevention (CDC).

  • Easier collaboration with colleagues:
    Easily share sampling and analysis plans.

  • More accurate analyses: Enables you to
    take up to three stages into account when analyzing data from a multistage design.

  • A more precise picture of your data:
    Unlike traditional statistics, sub population assessments take other sub-populations
    into account

Use the following types of sample design information with SPSS Complex Samples:

  • Stratified sampling: Increase the precision of your sample or ensure a representative sample from key groups by choosing to sample within subgroups of the survey population. For example, subgroups might be a specific number of males or females or contain people in certain job categories, people of a certain age group, and so on.

  • Clustered sampling: Select clusters, which are groups of sampling units, for your survey. Clusters can include schools, hospitals or geographic areas with sampling units that might be students, patients, or citizens. Clustering often helps make surveys more cost-effective.

  • Multistage sampling: Select an initial or first-stage sample based on groups of elements in the population; then create a second-stage sample by drawing a sub-sample from each selected unit in the first-stage sample. By repeating this option, you can select a higher-stage sample. For example, in a face-to-face survey, you might sample individuals within households and city blocks.