The use of the logistic model in space motion sickness prediction.
The one-equation and the two-equation logistic models were used to predict tested subjects' susceptibility to motion sickness in KC-135 parabolic flights using data from other ground-based motion sickness tests. A data set containing data from 6 provocative tests, 2 vestibular function tests, and 1 motion sickness experience questionnaire from 162 subjects was used in this study. The prediction results from the logistic models were compared with those from the previously-used Bayes linear discriminant analysis procedures. The results based on this data set show that the logistic models correctly predicted substantially more cases (an average of 13%) in the data subset used for model building. In the data subset used for model cross-validation, the logistic models correctly predicted 4% and 5% more cases in the prediction of vomit or nonvomit, and of degree of susceptibility, respectively. Overall, the logistic models ranged from 53 to 65% predictions of the three endpoint parameters, whereas the Bayes linear discriminant procedure ranged from 48 to 65% correct for the cross validation sample.
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Krug International, Houston, TX 77058.
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D000328:Adult; D005260:Female; D006801:Humans; D008297:Male; D008954:Models, Biological; D009041:Motion Sickness / Q000175:diagnosis* / Q000209:etiology; D011336:Probability; D013026:Space Flight; D014724:Vestibular Function Tests; D014839:Vomiting / Q000209:etiology