ELIZA cgi-bash version rev. 1.90
- Medical English LInking keywords finder for the PubMed Zipped Archive (ELIZA) -

return kwic search for based out of >500 occurrences
404793 occurrences (No.42 in the rank) during 5 years in the PubMed. [no cache] 500 found
256) In this article, we discuss and examine two methods that rely on very different assumptions to estimate the CACE: a maximum likelihood ('joint') method that assumes the 'exclusion restriction,' (ER) and a propensity score-based method that relies on 'principal ignorability.' We detail the assumptions underlying each approach, and assess each methods' sensitivity to both its own assumptions and those of the other method using both simulated data and a motivating example.
--- ABSTRACT ---
PMID:21971481 DOI:10.1177/0962280211421840
2015 Statistical methods in medical research
* Assessing the sensitivity of methods for estimating principal causal effects.
- The framework of principal stratification provides a way to think about treatment effects conditional on post-randomization variables, such as level of compliance. In particular, the complier average causal effect (CACE) - the effect of the treatment for those individuals who would comply with their treatment assignment under either treatment condition - is often of substantive interest. However, estimation of the CACE is not always straightforward, with a variety of estimation procedures and underlying assumptions, but little advice to help researchers select between methods. In this article, we discuss and examine two methods that rely on very different assumptions to estimate the CACE: a maximum likelihood ('joint') method that assumes the 'exclusion restriction,' (ER) and a propensity score-based method that relies on 'principal ignorability.' We detail the assumptions underlying each approach, and assess each methods' sensitivity to both its own assumptions and those of the other method using both simulated data and a motivating example. We find that the ER-based joint approach appears somewhat less sensitive to its assumptions, and that the performance of both methods is significantly improved when there are strong predictors of compliance. Interestingly, we also find that each method performs particularly well when the assumptions of the other approach are violated. These results highlight the importance of carefully selecting an estimation procedure whose assumptions are likely to be satisfied in practice and of having strong predictors of principal stratum membership.
--- ABSTRACT END ---
[
right
kwic]
[frequency of next (right) word to based]
(1)247 on (10)3 approach (19)2 chemotherapy (28)2 physical
(2)10 method (11)3 hydrogels (20)2 computer-tailored (29)2 rehabilitation
(3)10 therapies (12)3 information (21)2 financing (30)2 retrospective
(4)5 cross-sectional (13)3 study (22)2 learning (31)2 scaffolds
(5)5 upon (14)3 techniques (23)2 methods (32)2 strategy
(6)4 survey (15)3 therapeutic (24)2 modelling (33)2 studies
(7)4 tissue (16)2 NPWT (25)2 morphometry (34)2 telephone
(8)3 CRT (17)2 RUTF (26)2 nutrient (35)2 vaccination
(9)3 anti-bullying (18)2 and (27)2 palliative

add keyword

--- WordNet output for based --- =>に基づき Overview of verb base The verb base has 3 senses (first 1 from tagged texts) 1. (75) establish, base, ground, found -- (use as a basis for; found on; "base a claim on some observation") 2. base -- (situate as a center of operations; "we will base this project in the new lab") 3. free-base, base -- (use (purified cocaine) by burning it and inhaling the fumes) Overview of adj based The adj based has 2 senses (first 2 from tagged texts) 1. (3) based -- (having a base; "firmly based ice") 2. (1) based -- (having a base of operations (often used as a combining form); "a locally based business"; "an Atlanta-based company"; "carrier-based planes") --- WordNet end ---