Literature DB >> 10070674

Comparing several score tests for interval censored data.

M P Fay1.   

Abstract

I create a general model to perform score tests on interval censored data. Special cases of this model are the score tests of Finkelstein, Sun and Fay. Although Sun's was derived as a test for discrete data and Finkelstein's and Fay's tests were derived under a grouped continuous model, by writing all tests under one general model we see that as long as the regularity conditions hold, any of these three classes of tests may be applied to either grouped continuous or discrete data. I show the equivalence between the weighted logrank form of the general test and the form with a term for each individual, the form often used with permutation tests. From the weighted logrank form of the tests, we see that Sun's and Finkelstein's test are similar, giving constant (or approximately constant) weights to differences in survival distributions over time. In contrast, the proportional odds model (Fay's model with logistic error) gives more weight to early differences.

Mesh:

Year:  1999        PMID: 10070674     DOI: 10.1002/(sici)1097-0258(19990215)18:3<273::aid-sim19>3.0.co;2-7

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  7 in total

1.  Nonparametric test for doubly interval-censored failure time data.

Authors:  J Sun
Journal:  Lifetime Data Anal       Date:  2001-12       Impact factor: 1.588

2.  A rank test for bivariate time-to-event outcomes when one event is a surrogate.

Authors:  Pamela A Shaw; Michael P Fay
Journal:  Stat Med       Date:  2016-04-05       Impact factor: 2.373

3.  Weighted logrank tests for interval censored data when assessment times depend on treatment.

Authors:  Michael P Fay; Joanna H Shih
Journal:  Stat Med       Date:  2012-07-11       Impact factor: 2.373

4.  Wilcoxon-Mann-Whitney or t-test? On assumptions for hypothesis tests and multiple interpretations of decision rules.

Authors:  Michael P Fay; Michael A Proschan
Journal:  Stat Surv       Date:  2010

5.  A spline-based nonparametric analysis for interval-censored bivariate survival data.

Authors:  Yuan Wu; Ying Zhang; Junyi Zhou
Journal:  Stat Sin       Date:  2022-07       Impact factor: 1.330

6.  Exact and Asymptotic Weighted Logrank Tests for Interval Censored Data: The interval R package.

Authors:  Michael P Fay; Pamela A Shaw
Journal:  J Stat Softw       Date:  2010-08       Impact factor: 6.440

7.  Reevaluation of risk factors for time to subsequent events after first stroke occurrence using a new weighted all-cause effect measure.

Authors:  Ann-Kathrin Ozga; Bernhard Rauch; Frederick Palm; Christian Urbanek; Armin Grau; Heiko Becher; Geraldine Rauch
Journal:  BMC Public Health       Date:  2020-06-01       Impact factor: 3.295

  7 in total

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