1 citations · 2 across the 8 of their papers we have counts for
9 papers
Causal mediation analysis for zero-inflated longitudinal data in the presence of treatment non-compliance and multiple mediators
Saurabh Bhandari, Wreetabrata Kar, Michael J. Daniels +1
Understanding whether a digital marketing campaign is effective is central to designing effective customer engagement strategies. We analyze a large-scale, longitudinal promotional…
Using a Two-Parameter Sensitivity Analysis Framework to Efficiently Combine Randomized and Non-randomized Studies
Ruoqi Yu, Bikram Karmakar, Jessica Vandeleest +1
Causal inference is vital for informed decision-making across fields such as biomedical research and social sciences. Randomized controlled trials (RCTs) are considered the gold st…
Inferring the Effect of a Confounded Treatment by Calibrating Resistant Population's Variance
Zikun Qin, Bikram Karmakar
In a general set-up that allows unmeasured confounding, we show that the conditional average treatment effect on the treated can be identified as one of two possible values. Unlike…
Degree of Interference: A General Framework For Causal Inference Under Interference
Yuki Ohnishi, Bikram Karmakar, Arman Sabbaghi
One core assumption typically adopted for valid causal inference is that of no interference between experimental units, i.e., the outcome of an experimental unit is unaffected by t…
Robustness and Efficiency of Rosenbaum's Rank-based Estimator in Randomized Trials: A Design-based Perspective
Aditya Ghosh, Nabarun Deb, Bikram Karmakar +1
Mean-based estimators of causal effects in randomized experiments may behave poorly if the potential outcomes have a heavy tail or contain outliers. An alternative estimator propos…
Inference for a test-negative case-control study with added controls
Bikram Karmakar, Dylan Small
Test-negative designs with added controls have recently been proposed to study COVID-19. An individual is test-positive or test-negative accordingly if they took a test for a disea…
Statistical Validity and Consistency of Big Data Analytics: A General Framework
Bikram Karmakar, Indranil Mukhopadhyay
Informatics and technological advancements have triggered generation of huge volume of data with varied complexity in its management and analysis. Big Data analytics is the practic…
Univariate and data-depth based multivariate control charts using trimmed mean and winsorized standard deviation
Kushal Kr. Dey, Kumaresh Dhara, Bikram Karmakar +1
Over the years, the most popularly used control chart for statistical process control has been Shewhart's or chart along with its multivariate generalizatio…
Test for the statistical significance of a treatment effect in the presence of hidden sub-populations
Bikram Karmakar, Kumaresh Dhara, Kushal Kumar Dey +2
For testing the statistical significance of a treatment effect, we usually compare between two parts of a population, one is exposed to the treatment, and the other is not exposed…