fnets: An R Package for Network Estimation and Forecasting via Factor-Adjusted VAR Modelling

dom-owens-uob/fnets 27 Jan 2023

The package fnets for the R language implements the suite of methodologies proposed by Barigozzi et al. (2022) for the network estimation and forecasting of high-dimensional time series under a factor-adjusted vector autoregressive model, which permits strong spatial and temporal correlations in the data.

Computation 62-04

TWEETS

Standardization allows for efficient unbiased estimation in observational studies and in indirect treatment comparisons: A comprehensive simulation study

no code yet • 23 Jan 2023

We evaluate how inverse probability of treatment weighting (IPTW) and standardization-based approaches compare for obtaining marginal estimates of the odds-ratio and the hazards ratio.

Methodology

TWEETS

Improving Software Engineering in Biostatistics: Challenges and Opportunities

no code yet • 24 Jan 2023

Code that is written needs to be readable to ensure reliable software.

Computation

TWEETS

Oncology clinical trial design planning based on a multistate model that jointly models progression-free and overall survival endpoints

no code yet • 24 Jan 2023

The multistate model approach allows us to consider the joint distribution of the two endpoints and to derive quantities of interest as the correlation between overall survival and progression-free survival.

Applications Methodology

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An Adaptive-Discard-Graph for online error control

no code yet • 27 Jan 2023

Although the classical graphical procedure can be extended to the online setting, previous work has shown that it leads to low power, and other approaches, such as Adaptive-Discard (ADDIS) procedures, are preferred instead.

Methodology

TWEETS