Inference on Finite Population Treatment Effects Under Limited Overlap

2018 ◽  
Author(s):  
Han Hong ◽  
Michael Leung ◽  
Jessie Li
Keyword(s):  
Treatment Effects ◽  
Finite Population ◽  
Population Treatment

Inference on finite-population treatment effects under limited overlap

2019 ◽  
Vol 23 (1) ◽  
pp. 32-47
Author(s):  
Han Hong ◽  
Michael P Leung ◽  
Jessie Li
Keyword(s):  
Propensity Score ◽  
Rate Of Convergence ◽  
Treatment Effects ◽  
Finite Population ◽  
Standard Methods ◽  
Population Average ◽  
Error Formulas ◽  
Local Average Treatment Effects ◽  
Local Average ◽  
Population Treatment

Summary This paper studies inference on finite-population average and local average treatment effects under limited overlap, meaning that some strata have a small proportion of treated or untreated units. We model limited overlap in an asymptotic framework, sending the propensity score to zero (or one) with the sample size. We derive the asymptotic distribution of analogue estimators of the treatment effects under two common randomization schemes: conditionally independent and stratified block randomization. Under either scheme, the limit distribution is the same and conventional standard error formulas remain asymptotically valid, but the rate of convergence is slower the faster the propensity score degenerates. The practical import of these results is two-fold. When overlap is limited, standard methods can perform poorly in smaller samples, as asymptotic approximations are inadequate owing to the slower rate of convergence. However, in larger samples, standard methods can work quite well even when the propensity score is small.

Combining single patient (N-of-1) trials to estimate population treatment effects and to evaluate individual patient responses to treatment

1997 ◽  
Vol 50 (4) ◽  
pp. 401-410 ◽  
Author(s):  
D.R. Zucker ◽  
C.H. Schmid ◽  
M.W. McIntosh ◽  
R.B. D'Agostino ◽  
H.P. Selker ◽  
...  
Keyword(s):  
Treatment Effects ◽  
Single Patient ◽  
Patient Responses ◽  
Population Treatment

OP49 MAIC-ing Use Of Trials? Study Of Matching-Adjusted Indirect Comparisons

2019 ◽  
Vol 35 (S1) ◽  
pp. 12-12
Author(s):  
Joy Leahy ◽  
Cathal Walsh
Keyword(s):  
Multiple Myeloma ◽  
Treatment Effects ◽  
Meta Analysis ◽  
Indirect Comparison ◽  
Aggregate Data ◽  
Base Case ◽  
Base Case Analysis ◽  
Adjusted Indirect Comparison ◽  
Population Treatment ◽  
Indirect Comparisons

IntroductionWhen conducting a Network Meta-Analysis (NMA) for a Health Technology Assessment (HTA), the submitting company typically will have access to Individual Patient Data (IPD) from their own trials, but only aggregate data (AgD) for the comparator. In this case, they can re-weight the IPD so that the covariate characteristics in the IPD trials match that of the AgD trials, using the increasingly popular method of Matching-Adjusted Indirect Comparison (MAIC).MethodsWe carried out a simulation study to investigate this method in a Bayesian setting. We simulated three IPD trials comparing treatments A and B (AB-IPD trials), and one aggregate data trial comparing treatments B and C (BC-AgD trial). We investigated two options of weighting covariates: 1. all three studies are weighted separately to match the BC-AgD trial (MAIC Separate Trials). 2. patients are weighted across all three IPD studies to match the BC-AgD trial, but the NMA still considers each trial separately (MAIC Pooled Trials). We compared the results of the MAIC to a standard NMA and a mixed IPD/AgD NMA. We applied these methods to a network of treatments for multiple myeloma.ResultsMAIC can provide more accurate estimates of the relative treatment effects than a standard NMA in the BC-AgD trial population. However, MAIC may decrease the accuracy of the relative treatment effects in the overall population. Treatment rankings were unchanged when applying MAIC to the multiple myeloma network.ConclusionsMAIC is beneficial as a sensitivity analysis to demonstrate that results hold across patient populations. If there is a difference in relative treatment effects attributable to population imbalances, then it is useful to be able to quantify this difference. However, we recommend using either a standard NMA or a mixed IPD/AgD NMA for the base case analysis, given the potential bias that can arise in an MAIC.

scholarly journals Estimating Population Treatment Effects From a Survey Subsample

2014 ◽  
Vol 180 (7) ◽  
pp. 737-748 ◽  
Author(s):  
Kara E. Rudolph ◽  
Iván Díaz ◽  
Michael Rosenblum ◽  
Elizabeth A. Stuart
Keyword(s):  
Treatment Effects ◽  
Population Treatment

A Phonomotor Approach to Apraxia of Speech Treatment

2020 ◽  
Vol 29 (4) ◽  
pp. 2109-2130
Author(s):  
Lauren Bislick
Keyword(s):  
Phase I ◽  
Treatment Effects ◽  
Single Case ◽  
Motor Planning ◽  
The Other ◽  
Multimodal Approach ◽  
Apraxia Of Speech ◽  
Duration Of Treatment ◽  
Treatment Gains ◽  
Future Work

Purpose This study continued Phase I investigation of a modified Phonomotor Treatment (PMT) Program on motor planning in two individuals with apraxia of speech (AOS) and aphasia and, with support from prior work, refined Phase I methodology for treatment intensity and duration, a measure of communicative participation, and the use of effect size benchmarks specific to AOS. Method A single-case experimental design with multiple baselines across behaviors and participants was used to examine acquisition, generalization, and maintenance of treatment effects 8–10 weeks posttreatment. Treatment was distributed 3 days a week, and duration of treatment was specific to each participant (criterion based). Experimental stimuli consisted of target sounds or clusters embedded nonwords and real words, specific to each participants' deficit. Results Findings show improved repetition accuracy for targets in trained nonwords, generalization to targets in untrained nonwords and real words, and maintenance of treatment effects at 10 weeks posttreatment for one participant and more variable outcomes for the other participant. Conclusions Results indicate that a modified version of PMT can promote generalization and maintenance of treatment gains for trained speech targets via a multimodal approach emphasizing repeated exposure and practice. While these results are promising, the frequent co-occurrence of AOS and aphasia warrants a treatment that addresses both motor planning and linguistic deficits. Thus, the application of traditional PMT with participant-specific modifications for AOS embedded into the treatment program may be a more effective approach. Future work will continue to examine and maximize improvements in motor planning, while also treating anomia in aphasia.

Sign in / Sign up

Export Citation Format

Share Document