[Application of tipping-point analysis to address missing data in clinical studies].

To use a visualized method, tipping-point analysis to address missing data in clinical study and discuss related problems. All the possible outcomes caused by missing data were listed and the tipping points where P-values of hypothesis test changed at 0.05 significant level were found out, then the ratio of P<0.05 was calculated, reflecting the reliability of the study’s result. Tipping-point analysis can be applied to both continuous and binary data to help find points where p-values are changed. The area of P<0.05 of continuous data is 93.6%, indicating that the reliability of success of the study is large; and the area of P<0.05 of binary data is 29.7%, reflecting that the reliability of success of the study is small. Tipping-point analysis, which provides a visualized evidence for decision making, is suitable for analyzing clinical studies with missing data. Key words: Tipping-point analysis; Clinical study; Missing data