Abstract
This study uses a semantic structure analysis (SSA) method to construct the causal relationships among the criteria from survey data. The literatures provide a predetermined threshold value when the SSA is applied without explanation, but we use a Monte Carlo simulation based on the raw data to determine the threshold values with the significant levels of 0.05 and 0.10 for constructing the causal relationships. The results show that the causal relationships among the criteria using the suggested threshold value are too complicated, while the causal relationships by the simulated threshold values are relatively easy to be understood and used practically.
| Original language | English |
|---|---|
| Pages (from-to) | 1543-1551 |
| Number of pages | 9 |
| Journal | Communications in Statistics: Simulation and Computation |
| Volume | 43 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 2014 Jan 1 |
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All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Modelling and Simulation
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Analysis of the threshold values of semantic structure analysis in identifying causal relationships. / Shieh, Jiunn I.; Wu, Hsin-Hung; Liu, Hsiang Chuan.
In: Communications in Statistics: Simulation and Computation, Vol. 43, No. 7, 01.01.2014, p. 1543-1551.Research output: Contribution to journal › Article
TY - JOUR
T1 - Analysis of the threshold values of semantic structure analysis in identifying causal relationships
AU - Shieh, Jiunn I.
AU - Wu, Hsin-Hung
AU - Liu, Hsiang Chuan
PY - 2014/1/1
Y1 - 2014/1/1
N2 - This study uses a semantic structure analysis (SSA) method to construct the causal relationships among the criteria from survey data. The literatures provide a predetermined threshold value when the SSA is applied without explanation, but we use a Monte Carlo simulation based on the raw data to determine the threshold values with the significant levels of 0.05 and 0.10 for constructing the causal relationships. The results show that the causal relationships among the criteria using the suggested threshold value are too complicated, while the causal relationships by the simulated threshold values are relatively easy to be understood and used practically.
AB - This study uses a semantic structure analysis (SSA) method to construct the causal relationships among the criteria from survey data. The literatures provide a predetermined threshold value when the SSA is applied without explanation, but we use a Monte Carlo simulation based on the raw data to determine the threshold values with the significant levels of 0.05 and 0.10 for constructing the causal relationships. The results show that the causal relationships among the criteria using the suggested threshold value are too complicated, while the causal relationships by the simulated threshold values are relatively easy to be understood and used practically.
UR - http://www.scopus.com/inward/record.url?scp=84893938834&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893938834&partnerID=8YFLogxK
U2 - 10.1080/03610918.2012.735322
DO - 10.1080/03610918.2012.735322
M3 - Article
AN - SCOPUS:84893938834
VL - 43
SP - 1543
EP - 1551
JO - Communications in Statistics Part B: Simulation and Computation
JF - Communications in Statistics Part B: Simulation and Computation
SN - 0361-0918
IS - 7
ER -