Erratum to: A Monte Carlo simulation study comparing linear regression, beta regression, variable-dispersion beta regression and fractional logit regression at recovering average difference measures in a two sample design

Author's response to reviews Title:A Monte Carlo Simulation Study Comparing Linear Regression, Beta Regression, Variable-Dispersion Beta Regression and Fractional Logit Regression at Recovering Average Difference Measures in a Two Sample Design Authors:

A Monte Carlo simulation study comparing linear regression, beta regression, variable-dispersion beta regression and fractional logit regression at recovering average difference measures in a two sample design

BACKGROUND In biomedical research, response variables are often encountered which have bounded support on the open unit interval--(0,1). Traditionally, researchers have attempted to estimate covariate effects on these types of response data using linear regression. Alternative modelling strategies may include: beta regression, variable-dispersion beta regression, and fractional logit regression...

Finite Sample Properties of Quantile Interrupted Time Series Analysis: A Simulation Study

Interrupted Time Series (ITS) analysis represents a powerful quasi-experime-ntal design in which a discontinuity is enforced at a specific intervention point in a time series, and separate regression functions are fitted before and after the intervention point. Segmented linear/quantile regression can be used in ITS designs to isolate intervention effects by estimating the sudden/level change (...

Bayesian Inference for Spatial Beta Generalized Linear Mixed Models

In some applications, the response variable assumes values in the unit interval. The standard linear regression model is not appropriate for modelling this type of data because the normality assumption is not met. Alternatively, the beta regression model has been introduced to analyze such observations. A beta distribution represents a flexible density family on (0, 1) interval that covers symm...

A Monte Carlo simulation technique for assessment of earthquake-induced displacement of slopes

The dynamic response of slopes against earthquake is commonly characterized by the earthquake-induced displacement of slope (EIDS). The EIDS value is a function of several variables such as the material properties, slope geometry, and earthquake acceleration. This work is aimed at the prediction of EIDS using the Monte Carlo simulation method (MCSM). Hence, the parameters height, unit specific ...