Application of cumulative ratio logit model and partial proportional odds model in analyzing factors influencing hospital-ization costs for lung cancer surgery patients
Application of cumulative ratio logit model and partial proportional odds model in analyzing factors influencing hospital-ization costs for lung cancer surgery patients
Objective To illuminate the application of cumulative odds logit model and partial proportional odds model in ordinal categorical data.Methods The cumulative odds logit model and partial proportional odds model were used to fit the re-lationship between hospital costs and relative factors of lung cancer surgery.The goodness of fit of the two models was compared by the log likelihood value(-2ln L)of the models.Results When the independent variables did not fully satisfy the propor-tional odds assumption(gender x2=15.888,P＜0.001;surgical procedure x2=35.874,P＜0.001),the fitting results of the two methods were different.At different segmentation points,there was a significant difference in the relationship between hospi-talization costs and surgical procedures.The partial proportional odds model(-2ln L=5 797.112)was better than the cumula-tive odds logit model(-2ln L=5 852.420).The difference of the log likelihood values was statistically significant(P＜0.05).Conclusion In order to analyze the ordinal categorical data,the proportional odds assumption should be verified firstly.If all the independent variables satisfy the condition,the cumulative odds logit model is selected,otherwise the partial proportional odds model is used to study the data.
维普
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