Analyzing Repeated Categorical Response Data

2003 ◽  
pp. 455-490 ◽  
Keyword(s):  
Response Data ◽  
Categorical Response

scholarly journals The Effects of Funding Change and Reorganization on Patterns of Emergency Response in a Local Health Agency

2014 ◽  
Vol 129 (6_suppl4) ◽  
pp. 166-172 ◽  
Author(s):  
Russell G. Schuh ◽  
Michelle Basque ◽  
Margaret A. Potter
Keyword(s):  
Emergency Response ◽  
Structural Changes ◽  
Health Agency ◽  
Local Health ◽  
Local Public Health ◽  
Response Data ◽  
Equal Rate ◽  
Response Capacity ◽  
Categorical Response ◽  
Internal Function

Indicators for Stress Adaptation Analytics (ISAAC) is a protocol to measure the emergency response behavior of organizations within local public health systems. We used ISAAC measurements to analyze how funding and structural changes may have affected the emergency response capacity of a local health agency. We developed ISAAC profiles for an agency's consecutive fiscal years 2013 and 2014, during which funding cuts and organizational restructuring had occurred. ISAAC uses descriptive and categorical response data to obtain a function stress score and a weighted contribution score to the agency's total response. In the absence of an emergency, we simulated one by assuming that each function was stressed at an equal rate for each of the two years and then we compared the differences between the two years. The simulations revealed that seemingly minor personnel or budget changes in health departments can mask considerable variation in change at the internal function level.

scholarly journals A Flexible Skewed Link Model for Ordinal Outcomes: An Application to Infertility

2020 ◽  
Vol 8 (A) ◽  
pp. 119-124
Author(s):  
Mohammad Chehrazi ◽  
Seyed Hassan Saadat ◽  
Mahmoud Hajiahmadi ◽  
Mirko Spiroski
Keyword(s):  
Monte Carlo ◽  
Ordinal Data ◽  
Monte Carlo Algorithm ◽  
Link Function ◽  
Posterior Distributions ◽  
Response Data ◽  
Improper Priors ◽  
Ordinal Regression Model ◽  
Link Model ◽  
Categorical Response

BACKGROUND: An important issue in modeling categorical response data is the choice of the links. The commonly used complementary log-log link is inclined to link misspecification due to its positive and fixed skewness parameter. AIM: The objective of this paper is to introduce a flexible skewed link function for modeling ordinal data with some covariates. METHODS: We introduce a flexible skewed link model for the cumulative ordinal regression model based on Chen model. RESULTS: The main advantage suggested by the proposed links is the skewed link provide much more identifiable than the existing skewed links. The propriety of posterior distributions under proper and improper priors is explored in detail. An efficient Markov chain Monte Carlo algorithm is developed for sampling from the posterior distribution. CONCLUSION: The proposed methodology is motivated and illustrated by ovary hyperstimulation syndrome data.

2. Random-Effects Modeling of Categorical Response Data

2000 ◽  
Vol 30 (1) ◽  
pp. 27-80 ◽  
Author(s):  
Alan Agresti ◽  
James G. Booth ◽  
James P. Hobert ◽  
Brian Caffo
Keyword(s):  
Random Effects ◽  
Response Data ◽  
Categorical Response ◽  
Random Effects Modeling
Sign in / Sign up

Export Citation Format

Share Document