Multiple linear regression with special properties of its coefficients parameterized by exponent, logit, and multinomial functions is considered. To obtain always positive coefficients the exponential parameterization is applied. To get coefficients in an assigned range, the logistic parameterization is used. Such coefficients permit us to evaluate the impact of individual predictors in the mod...

Individuals must often choose among discrete actions with imperfect information about their payoffs. Before choosing, they have an opportunity to study the payoffs, but doing so is costly. This creates new choices such as the number of and types of questions to ask. We model these situations using the rational inattention approach to information frictions. We find that the decision maker’s opti...

In recent years, there have been important developments in the simulation analysis of the mixed multinomial logit (MMNL) model as well as in the formulation of increasingly flexible closedform models belonging to the Generalized Extreme Value (GEV) class. In this paper, we bring these developments together to propose a mixed spatially correlated logit (MSCL) model for location-related choices. ...

Road traffic crash is a cause of unnatural death and occupies fifth position in the world as per WHO records. Road crashes in India are alarming in situation while road safety is professionally lacking and politically missing. Hyderabad city, the capital of newly formed Telangana State occupies sixth position in occurrence of road crashes. An attempt is made to understan...

The study assessed the effects of agricultural practices on biodiversity in Olamaboro Local Government Are of Kogi State, Nigeria. One hundred and fifty (150) farmers (respondents) were sampled using simple random sampling technique from five council wards (30 farmers per council ward). Data collected were analyzed using descriptive statistics and Logit regression model. Results showed that 63%...

In statistics, a multinomial logit (MNL) model, also known as multinomial logistic regression, is a regression model which generalizes logistic regression by allowing more than two discrete outcomes.[1] That is, it is a model that is used to predict the probabilities of the different possible outcomes of a categorically distributed dependent variable, given a set of independent variables (which...

Despite the ordinal nature of Self-Rated Health (SRH) variable, logistic regression models or regression models have been used without adequate justification for these applications. It is shown that ordered-logit regression model is the appropriate statistical strategy to estimate SRH, whereas the Ordinary LeastSquares model leads to biased conclusions.

This paper identifies several serious problems with the widespread use of ANOVAs for the analysis of categorical outcome variables such as forced-choice variables, question-answer accuracy, choice in production (e.g. in syntactic priming research), et cetera. I show that even after applying the arcsine-square-root transformation to proportional data, ANOVA can yield spurious results. I discuss ...

Overview: Categorical Data and Graphics Methods for discrete distributions – testing goodness of fit Hanging rootograms Robust distribution plots Methods for two-way frequency tables – understanding association Fourfold displays Sieve diagrams Mosaic displays and loglinear models for n-way tables Mosaic displays Mosaic matrices Correspondence analysis and MCA Logistic and logit regression Logit...