Structural Equation Modeling (SEM) as a multivariate data analysis technique is considered sophisticated one and becoming popular among researchers. Literature is not consistent on one of the important matter of SEM which is related with the determination of adequacy of model fit. In view of...

Statistical inference can be described as the process of drawing conclusions about a population or process based on sample data. This chapter outlines the logic of “classical” or “frequentist” methods for such inference. Three commonly used concepts for assessing statistical error are...

Purpose: Few studies have applied count data analysis to tourist accommodation data. This study was undertaken to investigate the characteristics and to seek for the most fitting models for population total estimation in relation to tourist accommodation data.Methods: Based on the data of 10,503...

When testing multiple hypotheses, conventional techniques used for reducing false positives require all tests to be pre-specified and do not account for correlation between p-values. This makes them incompatible with sequential modelling techniques, where models are built one-at-a-time and...

The application of Structural Equation Modeling (SEM) in the business research is growing. The second-generation multivariate data analysis technique, SEM is easy to use and provides a high quality statistical analysis. Many visual SEM software programs help in a quick design of the theoretical...

I show that ambiguity-averse decision functionals matched with the multiple-prior learning model are more robust to model misspecification than the standard expected utility with Bayesian learning. However, these criteria may fail to deliver robust decisions because the multiple-prior learning...

Motivated by the increasing use of external instruments to identify structural vector autoregressions SVARs), we develop algorithms for exact finite sample inference in this class of time series models, commonly known as proxy SVARs. Our algorithms make independent draws from the...

We study how changes to the informativeness of signals in Bayesian games and single-agent decision problems affect the distribution of equilibrium actions. A more precise private signal about an unknown state of the world leads to an mean-preserving spread of an agent's beliefs. Focusing on...

Methodological research has showcased GPS technology as the new gold-standard in land area measurement in large-scale household surveys. Nonetheless, facing budget constraints, survey agencies continue to measure with GPS only plots within sampled enumeration areas or a given radius of dwelling...

In this paper, we conduct simultaneous inference of the non-parametric part of a partially linear model when the non-parametric component is a multivariate unknown function. Based on semi-parametric estimates of the model, we construct a simultaneous confidence region of the multivariate...