|
Abstract
|
The aim of this study was to use Hierarchical Loglinear Model (HLLM) in the analysis of multiway frequency tables and to interpret the main and interaction effects of this model on suicide cases.
The data set used in this study was taken from the Turkish Republic State Statistical Institute (TUIK). A total of 6479 cases in 2016 and 2018 years were used in this analysis and the analyzes were made by considering gender, year and age variables.
As a result of HLLM analysis, Year, Gender and Age, which are the main effects in suicide cases, and the
interactions of Year × Gender and Gender × Age were found significantly (P<0.05). There was a significant
decrease in the suicide cases in 2018 compared to 2016 (P<0.001). In the sum of the years 2016 and 2018, among
the age groups; 2: Suicide cases were observed in the 29-49 age group with a higher rate of 41.45%, while in the
1: 0-19 age group there were fewer suicide cases observed to 11.99%. When factor Gender is Male, factor Year
changed from 50.61% to 49.39% at 2016 and 2018, respectively. However, when factor Gender is Female, factor
Year changed from 55.71% to 44.29%. This differences in the amount of these changes caused significantly to the
interaction of the Gender×Year.
The results has showed that, the main and interaction effects of multiway frequency tables can be interpreted by
using HLLM analysis without another statistical method. Hence, it is thought that researchers may prefer HLLM
models for the multiway frequency tables.
Keywords: contingency table, frequency table, loglinear model, suicide
Language: en |