Linear Transformation Model for Interval Censoringwith a Cured Subgroup
碩士 === 淡江大學 === 統計學系碩士班 === 100 === There are numerous statistical methods reported for the analysis of right-censored failure time data in the past 30 years. In a medical follow-up study, additional problems arise in the analysis of interval censoring. For example, patients are observed periodicall...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2012
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| Online Access: | http://ndltd.ncl.edu.tw/handle/17768133608252798850 |
| Summary: | 碩士 === 淡江大學 === 統計學系碩士班 === 100 === There are numerous statistical methods reported for the analysis of right-censored failure time data in the past 30 years. In a medical follow-up study, additional problems arise in the analysis of interval censoring. For example, patients are observed periodically, we don''t know the exact onset time of the disease, thus the observed failure time falls into a time period.
In addition, we consider a data set with two populations. Some subjects (non-susceptibility) do not become events we are interested in and some subjects (susceptibility) become events we are interested in. The non-susceptible rate (cured rate) represents a combination of cure data and survival data.
This thesis considers transformation model to analysis the interval censoring data with cured proportion. The EM algorithmis developed for the estimation and simulation studies are conducted.
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