Analyze statistical data and interpret survey results from complex samples

IBM® SPSS® Complex Samples helps market researchers, public opinion researchers and social scientists make more statistically valid inferences by incorporating sample design into their survey analysis. SPSS Complex Samples provide the specialized planning tools and statistics you need when working with complex sample designs, such as stratified, clustered or multistage sampling.

Analysis plan wizard

To analyze sample data, use an analysis design created by the Analysis Plan Wizard as input into the Complex Sample Descriptives or Complex Sample Tabulate.

Analysis plan wizard

General linear models

Build linear regression and analysis of variance models to predict numerical outcomes while taking the sample design into account. The procedure estimates variances by taking into account the sample design used to select the sample, including equal probability and PPS methods, and WR and WOR sampling procedures.

General linear models

Parameter estimates

The parameter estimates show the effect of each predictor on Amount spent. The value of 518.249 for the intercept term indicates that the grocery chain can expect a shopper with a family who uses coupons from the newspaper and targeted mailings to spend $518.25, on average. Parameter estimates are useful for quantifying the effect of each model term, but the estimated marginal means tables can also make it easier to interpret the model results.

Parameter estimates

Sampling plan wizard

Specify the sampling frame to create a complex sample design used by companion procedures in the Complex Samples add-on module. To sample cases, use a sample design created by the Sampling Plan Wizard as input to the Complex Sample Selection procedure.

Sampling plan wizard

SPSS Complex Samples Screenshots

Incorporate sample design into survey analysis

  • Increase the precision of your sample or ensure a representative sample from key groups.
  • Select clusters or groups of sampling units to make your surveys more cost-effective.
  • Employ multistage sampling to select a higher-stage sample.

Retain survey planning parameters for future use

  • Publish public-use data sets that include your sampling and analysis plans.
  • Use published plans as a template in order to save decisions made when creating the plan.
  • Make plans available to others in the organization so they can replicate results or pick up where you left off.

Manage complex survey data

  • Display one-way frequency tables or two-way cross-tabulations and associated standard errors, design effects, confidence intervals and hypothesis tests.
  • Build linear regression, analysis of variance (ANOVA) and analysis of covariance (ANCOVA) models.
  • Estimate means, sums and ratios, and compute standard errors, design effects confidence intervals and hypothesis tests for samples drawn by complex sampling methods.
  • Perform binary logistic regression analysis and multiple logistic regression (MLR) analysis.
  • Apply Cox proportional hazards regression to analysis of survival times.

Use an intuitive interface and helpful wizards

  • Use the Analysis Preparation Wizard to specify how the samples are defined and how standard errors should be estimated.
  • When creating your own samples, use the Sampling Plan Wizard to define the scheme and draw the sample.
  • Use the IBM SPSS Complex Samples Selection (CSSELECT) procedure to select complex, probability-based samples from a population while mitigating the risk of over-representing or under-representing a subgroup.

SPSS Complex Samples resources

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Analyze statistical data and interpret survey results from complex samples

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