scholarly journals Bias in estimating the causal hazard ratio when using two-stage instrumental variable methods

2015 ◽  
Vol 34 (14) ◽  
pp. 2235-2265 ◽  
Author(s):  
Fei Wan ◽  
Dylan Small ◽  
Justin E. Bekelman ◽  
Nandita Mitra
Biometrika ◽  
2017 ◽  
Vol 104 (4) ◽  
pp. 881-899 ◽  
Author(s):  
Byeong Yeob Choi ◽  
Jason P Fine ◽  
M Alan Brookhart

2020 ◽  
Vol 10 (1) ◽  
pp. 43-54
Author(s):  
Vitriyani Tri Purwaningsih

Rumah tangga yang dipimpin oleh perempuan cenderung lebih banyak berkerja pada sektor informal yang memiliki pendapatan rendah. Penelitian ini bertujuan untuk melihat kesejahteraan antara pekerja informal dan formal di antara rumah tangga yang dipimpin oleh seorang perempuan. Data yang digunakan merupakan data sekunder yang berasal dari Indonesia Family Life Survey (IFLS) 2014, dengan metode analisis Two Stage LeastSquare (2SLS) menggunakan pendekatan instrumental variable. Temuan dari penelitian ini menyatakan bahwa rumah tangga yang dikepalai oleh perempuan yang bekerja di sektor informal memiliki kesejahteraan yang lebih rendah dibandingkan dengan rumah tangga sektor formal. Usia kepala rumah tangga perempuan yang lebih dewasa, memiliki lahan pertanian dan tabungan mampu meningkatkan pengeluaran per kapita bulanan.Penelitian ini menyimpulkan bahwa adanya kesenjangan antar sektor namun kepemilikan aset dapat meningkatkan kesejahteraan di antara rumah tangga perempuan.


2019 ◽  
Vol 20 (4) ◽  
pp. e831-e851 ◽  
Author(s):  
Volker Grossmann ◽  
Aderonke Osikominu

Abstract In absence of randomized-controlled experiments, identification is often aimed via instrumental variable (IV) strategies, typically two-stage least squares estimations. According to Bayes’ rule, however, under a low ex ante probability that a hypothesis is true (e.g. that an excluded instrument is partially correlated with an endogenous regressor), the interpretation of the estimation results may be fundamentally flawed. This paper argues that rigorous theoretical reasoning is key to design credible identification strategies, the foremost, finding candidates for valid instruments. We discuss prominent IV analyses from the macro-development literature to illustrate the potential benefit of structurally derived IV approaches.


2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Arvid Sjolander ◽  
Torben Martinussen

Abstract Instrumental variables is a popular method in epidemiology and related fields, to estimate causal effects in the presence of unmeasured confounding. Traditionally, instrumental variable analyses have been confined to linear models, in which the causal parameter of interest is typically estimated with two-stage least squares. Recently, the methodology has been extended in several directions, including two-stage estimation and so-called G-estimation in nonlinear (e. g. logistic and Cox proportional hazards) models. This paper presents a new R package, ivtools, which implements many of these new instrumental variable methods. We briefly review the theory of two-stage estimation and G-estimation, and illustrate the functionality of the ivtools package by analyzing publicly available data from a cohort study on vitamin D and mortality.


Author(s):  
Meda R Sandu ◽  
Rhona Beynon ◽  
Rebecca Richmond ◽  
Diana L. Santos Ferreira ◽  
Lucy Hackshaw-McGeagh ◽  
...  

Background: Feasibility trials are preliminary trials that assess the viability and acceptability of intervention studies and the effects of the intervention on intermediate endpoints. Due to their short duration, they are unable to establish the effects of the intervention on long-term clinical outcomes. We propose a novel method that could transform the interpretation of feasibility trials using modified two-stage randomisation analyses. Methods In this two-stage process, we explored the effects of a 6-month feasibility factorial randomised controlled trial (RCT) of lycopene and green tea dietary interventions (ProDiet) on 159 serum metabolic traits in 133 men with raised PSA levels but prostate cancer (PCA) free. In the first stage, we conducted an intention-to-treat analysis, using linear regression to examine the effects of the interventions on metabolic traits, compared to the placebo group and instrumental variable analysis to assess the causal effect of the intervention on the outcomes. In the second stage, we used a two-sample Mendelian Randomization (MR) approach to assess the causal effect of metabolic traits altered by the interventions, on PCA risk, using summary statistics data from an international PCA consortium of 44,825 cancer cases and 27,904 controls. ResultsThe systemic effects of lycopene and green tea supplementation on serum metabolic profile were comparable to the effects of the respective dietary advice interventions (R2= 0.65 and 0.76 for lycopene and green tea respectively). Metabolites which were altered in response to lycopene supplementation were acetate (standard deviation difference versus placebo (β)): 0.69; 95% CI= 0.24, 1.15; p=0.003), valine (β: -0.62; -1.03, -0.02; p=0.004), pyruvate (β: -0.56; -0.95, -0.16; p=0.006), and docosahexaenoic acid (β: -0.50; -085, -0.14; p=0.006). The instrumental variable analysis showed there was no evidence that green tea altered the metabolome, but lycopene was associated with an increase in acetate (β=2.13; p=0.006) and decreases in pyruvate (β=-1.90; p=0.009), valine (β=-1.79; p=0.023), diacylglycerol (β=-1.81; p=0.026), alanine (β=-1.55; p=0.015) and DHA (p=0.097), where the regression coefficient represents the standard deviation (SD) difference in metabolite measures per unit change in lycopene (µmol/L) or EGCG (nM).Using MR, a genetically instrumented SD increase in pyruvate increased the odds of PCA by 1.29 (1.03, 1.62; p=0.027). Conclusion Using a two-stage randomization analysis in a feasibility RCT, we found that lycopene lowered levels of pyruvate, which our Mendelian randomization analysis suggests may be causally related to reduced PCA risk.


2021 ◽  
pp. 089976402110574
Author(s):  
Meg Elkins ◽  
Bronwyn Coate ◽  
Mehmet Özmen ◽  
Ashton de Silva

Volunteers are critical for many local arts and culture programs. In contrast to most research, we focus on potential rather than actual volunteers. Using data collected from an online survey of 948 participants, we explore the extent to which individuals are willing to contribute both their time and money to support community arts initiatives. Results from a binary two-stage instrumental variable (IV) probit indicate that a significant predictor of willingness to volunteer is the willingness to pay and the intangible value placed on arts activities and engagement. These findings have implications for recruitment initiatives by public and community arts organizations reliant on volunteer support.


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