IBM SPSS COMPLEX SAMPLES 19 manual Complex Samples Missing Values

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Complex Samples Frequencies

„Confidence interval. A confidence interval for the estimate, using the specified level.

„Coefficient of variation. The ratio of the standard error of the estimate to the estimate.

„Unweighted count. The number of units used to compute the estimate.

„Design effect. The ratio of the variance of the estimate to the variance obtained by assuming that the sample is a simple random sample. This is a measure of the effect of specifying a complex design, where values further from 1 indicate greater effects.

„Square root of design effect. This is a measure of the effect of specifying a complex design, where values further from 1 indicate greater effects.

„Cumulative values. The cumulative estimate through each value of the variable.

Test of equal cell proportions. This produces chi-square and likelihood-ratio tests of the hypothesis that the categories of a variable have equal frequencies. Separate tests are performed for each variable.

Complex Samples Missing Values

Figure 5-3

Missing Values dialog box

Tables. This group determines which cases are used in the analysis.

„Use all available data. Missing values are determined on a table-by-table basis. Thus, the cases used to compute statistics may vary across frequency or crosstabulation tables.

„Use consistent case base. Missing values are determined across all variables. Thus, the cases used to compute statistics are consistent across tables.

Categorical Design Variables. This group determines whether user-missing values are valid or invalid.