Log-Linear Modeling with the Negative Multinomial Distribution

Biometrics ◽  
1997 ◽  
Vol 53 (3) ◽  
pp. 971 ◽  
Author(s):  
Lance A. Waller ◽  
Daniel Zelterman
Keyword(s):  
Multinomial Distribution ◽  
Linear Modeling ◽  
Negative Multinomial Distribution ◽  
Log Linear

An analysis of truck-involved freeway accidents using log-linear modeling

1987 ◽  
Vol 18 (3) ◽  
pp. 121-136 ◽  
Author(s):  
Thomas F. Golob ◽  
Wilfred W. Recker
Keyword(s):  
Linear Modeling ◽  
Log Linear

Some Common Pitfalls in Causal Analysis of Categorical Data

1982 ◽  
Vol 19 (4) ◽  
pp. 461-471 ◽  
Author(s):  
Jay Magidson
Keyword(s):  
Categorical Data ◽  
Causal Analysis ◽  
Statistical Technique ◽  
Omitted Variables ◽  
Causal Interpretation ◽  
Linear Modeling ◽  
Chi Square ◽  
Interaction Detection ◽  
Biasing Effects ◽  
Log Linear

Examples of some common pitfalls in the analysis of categorical data are discussed in the context of causal interpretation of the results. Though no statistical technique can replace theory, the author shows that log-linear modeling and chi square automatic interaction detection can provide researchers with powerful tools for gaining valuable causal insights into their data. Examples include the biasing effects of omitted variables, omitted interactions, improper contrast coding, and misspecification of the structure of an hypothesized interaction.

scholarly journals Application of a Negative Multinomial Model Gives Insight into Rarity-Area Relationships

Forests ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 571
Author(s):  
Youhua Chen ◽  
Yongbin Wu ◽  
Weihua Chen ◽  
Tian Zhao ◽  
Wenyan Zhang ◽  
...  
Keyword(s):  
Poisson Distribution ◽  
Rare Species ◽  
Spatial Scales ◽  
Multinomial Distribution ◽  
Barro Colorado Island ◽  
Field Sampling ◽  
Local Sample ◽  
Negative Multinomial Distribution ◽  
Using Data ◽  
Insight Into

The distribution of individuals of different species across different sampling units is typically non-random. This distributional non-independence can be interpreted and modelled as a correlated multivariate distribution. However, this correlation cannot be modelled using a totally independent and random distribution such as the Poisson distribution. In this study, we utilized the negative multinomial distribution to overcome the problem encountered by the commonly used Poisson distribution and used it to derive insight into the implications of field sampling for rare species’ distributions. Mathematically, we derived, from the negative multinomial distribution and sampling theory, contrasting relationships between sampling area, and the proportions of locally rare and regionally rare species in ecological assemblages presenting multi-species correlated distribution. With the suggested model, we explored the cross-scale relationships between the spatial extent, the population threshold for defining the rarity of species, and the multi-species correlated distribution pattern using data from two 50-ha tropical forest plots in Barro Colorado Island (Panama) and Heishiding Provincial Reserve (Guangdong Province, China). Notably, unseen species (species with zero abundance in the studied local sample) positively contributed to the distributional non-independence of species in a local sample. We empirically confirmed these findings using the plot data. These findings can help predict rare species–area relationships at various spatial scales, potentially informing biodiversity conservation and development of optimal field sampling strategies.

Prevalence of Dystonia in Antioquia, Colombia

2016 ◽  
Vol 46 (2) ◽  
pp. 137-143 ◽  
Author(s):  
Juan Marcos Solano Atehortúa ◽  
Sandra Patricia Isaza Jaramillo ◽  
Ana Rendón Bañol ◽  
Omar Buritica Henao
Keyword(s):  
Epidemiological Studies ◽  
Demographic Characteristics ◽  
Linear Modeling ◽  
Delay In Diagnosis ◽  
True Prevalence ◽  
High Prevalence ◽  
The World ◽  
Different Types ◽  
Capture Recapture ◽  
Log Linear

Background: There are few published epidemiological studies concerning dystonia. Its true prevalence has been difficult to establish. There is no data published in Latin America on this matter. Methods: In this study the prevalence of dystonias in the Department of Antioquia (Colombia) was estimated using a capture-recapture methodology with log-linear modeling, including cases in 3 centers for neurological referrals that cover the Department of Antioquia from 2007 to 2012. Results: The overall prevalence was 712 per 1,000,000 (95% CI 487-937). Of the total of 874 patients, 79% had primary dystonias, and 75.5% had focal dystonias. The delay in diagnosis was longer for primary dystonias, with a median of 1 year. Conclusion: We found a high prevalence of dystonias in Antioquia. The frequency of the different types of dystonias, as well as the demographic characteristics of our patients, is similar to data from other populations of the world.

scholarly journals Structural equation and log-linear modeling: a comparison of methods in the analysis of a study on caregivers' health

2006 ◽  
Vol 6 (1) ◽  
Author(s):  
Bin Zhu ◽  
Stephen D Walter ◽  
Peter L Rosenbaum ◽  
Dianne J Russell ◽  
Parminder Raina
Keyword(s):  
Structural Equation ◽  
Comparison Of Methods ◽  
Linear Modeling ◽  
Log Linear
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