We formulate a joint statistical model for two variables: one of them is either a count variable or just zero, and the other is a regular count variable. We consider a modelling framework based on switching between a bivariate Poisson regression model and a univariate ...
Further, the CEO’s credibility and authority are threatened and diminished when they are perceived to be greedy (Conger,2005; Joutsenvirta,2013). CEOs who are perceived to be greedy likely recognize that, in the event of employee fatalities and injuries, they will be less effective in remedyi...
We analyzed the association between reaching age 65 years and utilization of T2D drugs using a Poisson regression with a dependent variable for number of T2D claims per quarter. We also used logistic regressions to examine binary dependent variables for any use of each specific class. Effects on ...
they would habitually keep detouring. However, we found that dogs always preferred the large door over the detour. This gave an interesting opportunity to compare this experiment with the one of Pongrácz et al.,37, where dogs preferred the longer...
Due to zero inflation in the data, a 2-level Poisson regression model was conducted instead of the pre-registered mixed ANOVA in order to assess group differences in the reduction of intrusions between Session 2 and Session 3, with the variable time on level 1 and the variables memory and ...
A Poisson or similar count model (quasi-Poisson, negative binomial) makes an assumption about the association between the value of a count and the variance in the count. That won't necessarily hold for this type of ranking data. It's quite possible to perform an ordinal regression with a ...
The initial values for regression coefficients and the covariance matrix are obtained from a multivariate regression fit to the complete cases only. init(initmatlist) specifies to use manually supplied initial values for the EM procedure and syntactically is identical to mcmcinit(initmatlist), ...
While Poisson regression can be used to analyze these kinds of count data, the resulting coefficient estimates are not reliable in cases of overdispersion. When drawing on a negative binomial regression, we find the alpha parameter significantly above zero (p < 0.001), indicating that a negative ...
To obtain a summary stratified IRR, we used a fixed-effects M-H type procedure as implemented in the "ir" command in STATA, which should give results similar to fitting a Poisson regression model with indicator variables for "study." This M-H approach produces a summary estimate stratified ...
C. Count data in biology-data transformation or model reformation? Ecol. Evol. 8, 3077–3085 (2018). Article PubMed PubMed Central Google Scholar Lambert, D. Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics 34, 1–14 (1992). Article Google ...