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  2. Kaplan–Meier estimator - Wikipedia

    en.wikipedia.org/wiki/KaplanMeier_estimator

    An example of a KaplanMeier plot for two conditions associated with patient survival. The KaplanMeier estimator, [1] [2] also known as the product limit estimator, is a non-parametric statistic used to estimate the survival function from lifetime data. In medical research, it is often used to measure the fraction of patients living for a ...

  3. Survival analysis - Wikipedia

    en.wikipedia.org/wiki/Survival_analysis

    This example of a survival tree analysis uses the R package "rpart". [8] The example is based on 146 stage C prostate cancer patients in the data set stagec in rpart. Rpart and the stagec example are described in Atkinson and Therneau (1997), [9] which is also distributed as a vignette of the rpart package. [8] The variables in stages are:

  4. Logrank test - Wikipedia

    en.wikipedia.org/wiki/Logrank_test

    The logrank test statistic compares estimates of the hazard functions of the two groups at each observed event time. It is constructed by computing the observed and expected number of events in one of the groups at each observed event time and then adding these to obtain an overall summary across all-time points where there is an event.

  5. Epi Info - Wikipedia

    en.wikipedia.org/wiki/Epi_Info

    Epi Info has been in development for over 20 years. The first version, Epi Info 1, was originally developed by Jeff Dean while he was in high school. [3] [4] It was an MS-DOS batch file on 5.25" floppy disks and released in 1985. [5]

  6. Recurrent event analysis - Wikipedia

    en.wikipedia.org/wiki/Recurrent_event_analysis

    Recurrent event analysis is a branch of survival analysis that analyzes the time until recurrences occur, such as recurrences of traits or diseases. Recurrent events are often analyzed in social sciences and medical studies, for example recurring infections, depressions or cancer recurrences.

  7. Survival function - Wikipedia

    en.wikipedia.org/wiki/Survival_function

    The graphs below show examples of hypothetical survival functions. The x-axis is time. The y-axis is the proportion of subjects surviving. The graphs show the probability that a subject will survive beyond time t. Four survival functions. For example, for survival function 1, the probability of surviving longer than t = 2 months is 0.37. That ...

  8. Censoring (statistics) - Wikipedia

    en.wikipedia.org/wiki/Censoring_(statistics)

    An early paper to use the KaplanMeier estimator for estimating censored costs was Quesenberry et al. (1989), [3] however this approach was found to be invalid by Lin et al. [4] unless all patients accumulated costs with a common deterministic rate function over time, they proposed an alternative estimation technique known as the Lin ...

  9. Paul Meier (statistician) - Wikipedia

    en.wikipedia.org/wiki/Paul_Meier_(statistician)

    Paul Meier (July 24, 1924 – August 7, 2011) [1] was a statistician who promoted the use of randomized trials in medicine. [2] [3]Meier is known for introducing, with Edward L. Kaplan, the KaplanMeier estimator, [4] [5] a method for measuring how many patients survive a medical treatment from one duration to another, taking into account that the sampled population changes over time.