By Baker S. G.
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Additional info for A sensitivity analysis for nonrandomly missing categorical data arising from a national health disab
A binary response variable can be string or numeric. Number of events occurring in a set of trials. When the response is a number of events occurring in a set of trials, the dependent variable contains the number of events and you can select an additional variable containing the number of trials. Alternatively, if the number of trials is the same across all subjects, then trials may be specified using a fixed value. The number of trials should be greater than or equal to the number of events for each case.
Profile plots are created for each dependent variable. Both between-subjects factors and within-subjects factors can be used in profile plots. A profile plot of one factor shows whether the estimated marginal means are increasing or decreasing across levels. For two or more factors, parallel lines indicate that there is no interaction between factors, which means that you can investigate the levels of only one factor. Nonparallel lines indicate an interaction. Figure 3-6 Nonparallel plot (left) and parallel plot (right) 22 Chapter 3 After a plot is specified by selecting factors for the horizontal axis and, optionally, factors for separate lines and separate plots, the plot must be added to the Plots list.
Maximum-likelihood jointly estimates the scale parameter with the model effects; note that this option is not valid if the response has a negative binomial, poisson, or binomial distribution. The deviance and Pearson chi-square options estimate the scale parameter from the value of those statistics. Alternatively, you can specify a fixed value for the scale parameter. Initial values. The procedure will automatically compute initial values for parameters. Alternatively, you can specify initial values for the parameter estimates.
A sensitivity analysis for nonrandomly missing categorical data arising from a national health disab by Baker S. G.