Investigation of giving behavior to united way using log-linear modeling and discriminant analysis: An empirical study

1984 ◽  
Vol 12 (3) ◽  
pp. 77-88 ◽  
Author(s):  
Arthur J. Adams ◽  
Subhash C. Lonial
Keyword(s):  
Discriminant Analysis ◽  
Empirical Study ◽  
Linear Modeling ◽  
United Way ◽  
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.

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

Rates of Hospitalization for Dehydration Following Hurricane Sandy in New Jersey

2015 ◽  
Vol 10 (2) ◽  
pp. 188-192 ◽  
Author(s):  
Joel N. Swerdel ◽  
George G. Rhoads ◽  
Nora M. Cosgrove ◽  
John B. Kostis ◽  
Keyword(s):  
Public Health ◽  
New Jersey ◽  
Electrical Power ◽  
Hurricane Sandy ◽  
Health Concern ◽  
Extreme Weather Events ◽  
Linear Modeling ◽  
Volume Depletion ◽  
New Jersey History ◽  
Log Linear

AbstractObjectiveHurricane Sandy, one of the most destructive natural disasters in New Jersey history, made landfall on October 29, 2012. Prolonged loss of electrical power and extensive infrastructure damage restricted access for many to food and water. We examined the rate of dehydration in New Jersey residents after Hurricane Sandy.MethodsWe obtained data from 2008 to 2012 from the Myocardial Infarction Data Acquisition System (MIDAS), a repository of in-patient records from nonfederal New Jersey hospitals (N=517,355). Patients with dehydration had ICD-9-CM discharge diagnosis codes for dehydration, volume depletion, and/or hypovolemia. We used log-linear modeling to estimate the change in in-patient hospitalizations for dehydration comparing 2 weeks after Sandy with the same period in the previous 4 years (2008–2011).ResultsIn-patient hospitalizations for dehydration were 66% higher after Sandy than in 2008–2011 (rate ratio [RR]: 1.66; 95% confidence interval [CI]: 1.50, 1.84). Hospitalizations for dehydration in patients over 65 years of age increased by nearly 80% after Sandy compared with 2008–2011 (RR: 1.79; 95% CI: 1.58, 2.02).ConclusionSandy was associated with a marked increase in hospitalizations for dehydration. Reducing the rate of dehydration following extreme weather events is an important public health concern that needs to be addressed, especially in those over 65 years of age. (Disaster Med Public Health Preparedness. 2016;10:188–192)

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