Do you analyze data from survey or market research, public health datasets, or government agencies? Do you use sample survey methodology in your research, or are your data likely to come from a public-use dataset that includes complex sample designs? Are you confident that the statistical methods you use to analyze sample survey data provide you with the most accurate results?
If you're working with complex sample designs, such as stratified, clustered or multistage sampling, you need specialized statistical techniques to account for the sample design and its associated standard errors.
IBM SPSS Complex Samples (formerly called SPSS Complex Samples) is a module of IBM SPSS Statistics. It provides the specialized planning tools and statistics you need when working with sample survey data. It enables you to make more statistically valid inferences for a population by incorporating the sample design into survey analysis. You can more accurately work with numerical and categorical outcomes in complex sample designs using two algorithms for analysis and prediction. In addition, a new algorithm enables you to predict time to an event. This add-on module is an indispensable statistical tool for survey and market researchers, public opinion researchers, or social scientists, and enables you to reach more accurate conclusions when working with sample survey methodology.
Only IBM SPSS Complex Samples makes understanding and working with your complex sample survey results easy. Through the intuitive interface, you can analyze data and interpret results. When you're finished, you can publish public-use datasets and include your sampling and analysis plans. These plans act as a template and allow you to save all the decisions made when creating the plan—define it once and you're done. This saves time and improves accuracy for yourself and others who may want to plug your plans into the data to replicate results or pick up where you left off.
To begin your work in IBM SPSS Complex Samples, use the wizards, which prompt you for the many factors you must consider before you start planning. If you are creating your own samples, use the Sampling Wizard to define the scheme and draw the sample. If you're using public-use datasets that already have samples, such as those provided by the Centers for Disease Control and Prevention (CDC), use the Analysis Plan Wizard to specify how the samples were defined and how standard errors should be estimated. Once you create a sample or specify standard errors, you can create plans, analyze your data, and produce results (see diagram below for workflow).
You can use the following types of sample design information with IBM SPSS Complex Samples:
Accurate analysis of survey data is easy in IBM SPSS Complex Samples. Start with one of the wizards (which one depends on your data source) and then use the interactive interface to create plans, analyze data and interpret results.
As a researcher, you want to be confident about your results. Performing data analysis in IBM SPSS Complex Samples helps you to achieve more statistically valid inferences for populations measured in your complex sample data. IBM SPSS Complex Samples provides you with better results because, unlike most conventional statistical software, it incorporates the sample design into survey analysis. And, it easily plugs into other IBM SPSS Statistics modules so you can seamlessly work in the IBM SPSS Statistics environment.
IBM SPSS Complex Samples provides you with five procedures to analyze data from sample survey data. And you can use ordinal data in much the same way you use numeric data.
Complex Samples Descriptives (CSDESCRIPTIVES)—Estimates means, sums and ratios, and computes standard errors, design effects, confidence intervals hypothesis tests for samples drawn by complex methods. The procedure estimates variances by taking into account the sample design used to select the sample, including equal probability and probability proportionate to size (PPS) methods, using both with replacement (WR) and without replacement (WOR) sampling procedures. Optionally, CSDESCRIPTIVES performs analyses for subpopulations.
You can also use CSDESCRIPTIVES to specify how to handle missing data:
Complex Sample Tabulate (CSTABULATE)—Displays one-way frequency tables or two-way crosstabulations and associated standard errors, design effects, confidence intervals and hypothesis tests for samples drawn by complex sampling methods. The procedure estimates variances by taking into account the sample design used to select the sample, including equal probability and PPS methods, and with replacement (WR) and without replacement (WOR ) sampling procedures. Optionally, CSTABULATE creates tables for subpopulations.
Use the following statistics within the table:
Use the following statistics and tests for the entire table:
You can use CSTABULATE to specify how to handle missing data, just as you do with CSDESCRIPTIVES.
Complex Samples General Linear Models (CSGLM)—Enables you to build linear regression, analysis of variance (ANOVA), and analysis of covariance (ANCOVA) models for samples drawn by complex sampling methods. 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. Optionally, CSGLM performs analyses for subpopulations.
You can use the following statistics with CSGLM:
Hypothesis tests include:
Handle missing data using listwise deletion of missing values.
Complex Ordinals Selection (CSORDINAL)—Makes it easier to predict outcomes when you are using ordinal data. You can estimate variances, taking into account the sample design used to select the sample. And you can perform an analysis for a subpopulation. You can create models for:
The CSORDINAL procedure includes the following statistics, tests, and functionality:
Complex Samples Logistic Regression (CSLOGISTIC)—Performs binary logistic regression analysis, as well as multiple logistic regression (MLR) analysis, for samples drawn by complex sampling methods. 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. Optionally, CSLOGISTIC performs analyses for subpopulations.
You can use the following statistics with CSLOGISTIC:
Hypothesis tests include:
Handle missing data using listwise deletion of missing values.
Complex Samples Cox Regression (CSCOXREG) —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. CSCOXREG supports continuous and categorical predictors, which can be time-dependent. CSCOXREG provides an easy way of considering differences in subgroups as well as analyzing effects of a set of predictors. Also, the procedure handles data where there are multiple cases (such as patient visits, encounters, and observations) for a single subject.
You can use the following statistics with CSCOXREG:
Hypothesis tests include:
To help you through the planning stage in the analytical process, IBM SPSS Complex Samples provides you with specialized tools and procedures for working with sample survey data. And it easily plugs into other IBM SPSS Statistics modules so you can seamlessly work in the IBM SPSS Statistics environment.
Complex Samples Plan (CSPLAN)—Use this procedure to specify the sampling frame to create a complex sample design or analysis specification used by companion procedures in IBM SPSS Complex Samples. With CSPLAN, you can specify how to draw or analyze stratified, clustered or multistage complex sample designs, with or without replacement. Methods for sampling with probability proportionate to size (PPS) are also available.
Because CSPLAN does not actually extract the sample or analyze data, you sample cases using sample designs created by CSPLAN as input to the Complex Samples Selection (CSSELECT) procedure.
Sampling Plan Wizard—If you are creating your own samples, use the Sampling Plan Wizard to define the scheme and draw the sample. From there, you can create plan files that you can save and share with colleagues.
Analysis Preparation Wizard—If you're using public-use datasets that already have samples, such as those provided by the CDC, use the Analysis Plan Wizard to specify how the samples were defined and how standard errors should be estimated. From there, you can create plan files that you can save and share with colleagues.
Plan files—Once you have created plan files, you can save them and treat them as templates. This allows you to save all the decisions you made when creating the plan. This saves time and improves accuracy for yourself and others who may want to plug your plans into the data to replicate results or pick up where you left off.
IBM SPSS Complex Samples provides what you need for the data management stage when working with sample survey data. And it easily plugs into other IBM SPSS Statistics modules so you can seamlessly work in the IBM SPSS Statistics environment.
Complex Samples Selection (CSSELECT) procedure—Enables you to select complex, probability-based samples from a population. CSSELECT chooses units according to a sample design created through the CSPLAN procedure.
With this procedure, you can:
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