# Browsing by Subject "Interaction effect"

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Item Interaction and marginal effects in nonlinear models : case of ordered logit and probit models(2013-05) Lee, Sangwon, active 2013; Whittaker, Tiffany A.; Powers, Daniel A.Show more Interaction and marginal effects are often an important concern, especially when variables are allowed to interact in a nonlinear model. In a linear model, the interaction term, representing the interaction effect, is the impact of a variable on the marginal effect of another variable. In a nonlinear model, however, the marginal effect of the interaction term is different from the interaction effect. This report provides a general derivation of both effects in a nonlinear model and a linear model to clearly illustrate the difference. These differences are then demonstrated with empirical data. The empirical study shows that the corrected interaction effect in an ordered logit or probit model is substantially different from the incorrect interaction effect produced by the margins command in Stata. Based on the correct formulas, this report verifies that the interaction effect is not the same as the marginal effect of the interaction term. Moreover, we must be careful when interpreting the nonlinear models with interaction terms in Stata or any other statistical software package.Show more Item A study of courteous behavior on the University of Texas campus(2010-12) Lu, Zhou, 1978-; Stolp, Chandler; Powers, Daniel A.Show more This study focused on measuring courteous behavior on the University of Texas at Austin (UT) students on campus. This behavior was measured through analyzing various factors involved when a person opened the door for another. The goal was to determine which factors would significantly affect the probability that a person would hold a door for another. Three UT buildings with no automatic doors were selected (RLM, FAC and GRE), and 200 pairs of students at each location were observed to see whether they would open doors for others. These subjects were not disturbed during the data collection process. For each observation, the door holding conditions, genders, position (whether it was the one who opened the door or the recipient of this courteous gesture, abbreviated as recipient), distance between the person opening the door and the recipient, and the number of recipients were recorded. Descriptive statistics and logistic regression were used to analyze the data. The results showed that the probability of people opening the doors for others was significantly affected by gender, position, distance between the person opening the door and the recipient, the number of recipients, and the interaction term between gender and position. The study revealed that men had a slightly higher propensity of opening the doors for the recipients. The odds for men were a multiplicative factor of 1.09 of that for women on average, holding all other factors constant. However, women had much higher probability of having doors held open for them. The odds for men were a multiplicative factor of 0.55 of that for women on average, holding all other factors constant. In terms of the distance between the person opening the door and the recipient, for each meter increase in distance, the odds that the door would be held open would decrease by a multiplicative factor of 0.40 on average. Additionally, for each increase in number of recipients, the odds that the door would be held open would increase by a multiplicative factor of 1.32 on average.Show more