Complex Samples
Work efficiently
Only SPSS Complex Samples makes understanding and working with your complex sample survey results easy. Through the intuitive interface, you can analyse 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 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 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, analyse your data and produce results.
You can 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 makes surveys more cost-effective.
- Multistage sampling : select an initial or first-stage sample based on groups of elements in your 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.