Distribution Fitting 1. Parameters Estimation under Assumption of Agreement between Observation and Model

Semiparametric Estimation on Multi-treatment Causal Effects via Cross-Fitting

Causal inference is a critical research area with multi-disciplinary origins and applications, ranging from statistics, computer science, economics, psychology to public health. In many scientific research, randomized experiments provide a golden standard for estimation of causal effects for decades. However, in many situations, randomized experiments are not feasible in practice so that practitioners need to rely on empirical investigation for causal reasoning. Causal inference via observational data is a challenging task since the knowledge of the treatment assignment mechanism is missing, w…

A matrix-based method of moments for fitting multivariate network meta-analysis models with multiple outcomes and random inconsistency effects

Random-effects meta-analyses are very commonly used in medical statistics. Recent methodological developments include multivariate (multiple outcomes) and network (multiple treatments) meta-analysis. Here we provide a new model and corresponding estimation procedure for multivariate network meta-analysis, so that multiple outcomes and treatments can be included in a single analysis. Our new multivariate model is a direct extension of a univariate model for network meta-analysis that has recently been proposed. We allow two types of unknown variance parameters in our model, which represent betw…

Overall Agreement for Multiple Raters with Replicated Measurements

Multiple raters are often needed to be used interchangeably in practice for measurement or evaluation. Assessing agreement among these multiple raters via agreement indices are necessary before their participation. While the intuitively appealing agreement indices such as coverage probability and total deviation index, and relative area under coverage probability curve, have been extended for assessing overall agreement among multiple raters, these extensions have limitations. The existing overall agreement indices either require normality and homogeneity assumptions or did not preserve the in…

Robust Fitting for Generalized Additive Models for Location, Scale and Shape

The validity of estimation and smoothing parameter selection for the wide class of generalized additive models for location, scale and shape (GAMLSS) relies on the correct specification of a likelihood function. Deviations from such assumption are known to mislead any likelihood-based inference and can hinder penalization schemes meant to ensure some degree of smoothness for non-linear effects. We propose a general approach to achieve robustness in fitting GAMLSSs by limiting the contribution of observations with low log-likelihood values. Robust selection of the smoothing parameters can be ca…

Distribution fitting 13. Analysis of independent, multiplicative effect of factors. Application to effect of essential oils extracts from plant species on bacterial species. Application to factors of antibacterial activity of plant species

A factor effect study was conducted on a set of observations at the contingency of a series of plant species and bacteria species regarding the antibacterial activity of essential oil extracts. The study reveals a very good agreement between the observations and the hypothesis of independent and multiplicative effect of plant and bacteria species factors on the antibacterial activity. Shaping of the observable to a Negative Binomial distribution allowed the separation of two convoluted Gamma distributions in the observable further assigned to the distribution of factors. Statistics of the Gamm…

用于估计条件效应及其他线性泛函的三重交叉拟合与伪结果回归

Three-way Cross-Fitting and Pseudo-Outcome Regression for Estimation of Conditional Effects and other Linear Functionals

本研究将平均处理效应估计的最新进展适配到条件平均处理效应估计中，结合三重交叉拟合与伪结果回归生成个性化效应估计，证明在结果条件期望满足平滑性条件时可实现较快收敛，为个体处理决策提供支撑。