Traditional regression analyses assume normality of observations and independence of mean and variance. However, there are many examples in science and Technology where the observations come from a skewed distribution and moreover there is a functional dependence between variance and mean. In this article, we propose a method for regression analysis under Inverse Gaussian model when th...

Many issues in strategy and technology management are categorical. Errors in classification of the dependent variable cause systematic bias in regression estimates. In the context of the linear probability model, we characterize the misclassification bias as being proportional to the difference between two measures. One is the “bias” in the explanatory variable, conditional on false negative, m...

Univariate partial least squares (PLS) is a method of modeling relationships between a Y variable and other explanatory vanables. It may be used with any number of explanatory variables, even far more than the number of observations. A simple interpretation is given that shows the method to be a straightforward and reasonable way of forming prediction equations. Its relationship to multivariate...

A new statistical profile monitoring technique to monitor and detect changes in logistic profiles with an application in the tourism industry is presented in this paper. In the statistical process control literature, profile is usually referred to as a relationship between a response variable and one or more explanatory variables. In the tourism case study presented in this paper, time is consi...

It is far from unusual for a multilevel model to contain a regressor that can be regarded as an endogenous variable. The term endogeneity as opposed to exogeneity is a familiar term in econometrics. Often it manifests itself by explanatory variable being subject to the same influences as the response variable. It is thus not exogenous in the model being fitted. More particularly it may mean tha...

Regression analyses of cross-country economic growth data are complicated by two main forms of model uncertainty: the uncertainty in selecting explanatory variables and the uncertainty in specifying the functional form of the regression function. Most discussions in the literature address these problems independently, yet a joint treatment is essential. We perform this joint treatment by extend...

An ecological correlation is a correlation based on group averages. Ecological correlations as such can be misleading, because the variability in the underlying individual data is lost by using averages. In interpretation of the results, there is a danger of committing the ecological fallacy: data is analysed at one level and inferences are made to another level (Robinson 1950). In 2-level mode...