New PDF release: A sensitivity analysis for nonrandomly missing categorical

By Baker S. G.

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Sample weights are computed automatically for subsequent stages of the current design. Stage Label. You can specify an optional string label for each stage. This is used in the output to help identify stagewise information. Note: The source variable list has the same contents across steps of the Wizard. In other words, variables removed from the source list in a particular step are removed from the list in all steps. Variables returned to the source list show up in all steps. Tree Controls for Navigating the Analysis Wizard At the left side of each step of the Analysis Wizard is an outline of all the steps.

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. Complex Samples Descriptives Missing Values Figure 6-3 Descriptives Missing Values dialog box Statistics for Measure Variables.

Standard error. The standard error of the estimate. „ 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. „ Expected values. The expected value of the estimate, under the hypothesis of independence of the row and column variable. „ 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.

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A sensitivity analysis for nonrandomly missing categorical data arising from a national health disab by Baker S. G.


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