Chapter
9
Complex Samples General LinearModel
The Complex Samples General Linear Model (CSGLM)procedure performs linear regression
analysis, as well as analysis of variance and covariance, for samplesdrawn by complex sampling
methods. Optionally, you can request analyses for a subpopulation.
Example. A grocery store chain surveyeda set of customers concerning their purchasing habits,
accordingt o a complexdesign. Givent he survey resultsa nd how much each customer spentin the
previous month, thestore wants to see if the frequency with which customers shop is related to
the amount they spend in a month, controllingfor the gender of the customer and incorporating
the sampling design.
Statistics. The procedure produces estimates, standard errors, confidence intervals,ttests, design
effects, and squareroots of design effects for model parameters, as well as the correlations and
covariances between parameter estimates. Measures of model fit and descriptive statistics for the
dependent and independent variables are also available. Additionally, you can request estimated
marginalmeans for levels of model factors and factor interactions.
Data. The dependent variableis quantitative. Factors are categorical. Covariates are quantitative
variables that are related to the dependentvariable. Subpopulation variables can be string or
numeric but should be categorical.
Assumptions. The cases in the data file represent a sample from a complex design that should
be analyzed according to the specifications in the file selected in the Complex Samples Plan
dialog box.
Obtaining a Complex Samples General Linear Model
From the menus choose:
Analyze > Complex Samples > General Linear Model...
ESelect a plan file. Optionally, select a custom joint probabilities file.
EClick Continue.
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